Tootfinder

A Domain-specific Language and Architecture for Detecting Process Activities from Sensor Streams in IoT
Ronny Seiger, Daniel Locher, Marco Kaufmann, Aaron F. Kurz
https://arxiv.org/abs/2507.00686

A Domain-specific Language and Architecture for Detecting Process Activities from Sensor Streams in IoT
Modern Internet of Things (IoT) systems are equipped with a plethora of sensors providing real-time data about the current operations of their components, which is crucial for the systems' internal control systems and processes. However, these data are often too fine-grained to derive useful insights into the execution of the larger processes an IoT system might be part of. Process mining has developed advanced approaches for the analysis of business processes that may also be used in the conte…

Zero-Trust Foundation Models: A New Paradigm for Secure and Collaborative Artificial Intelligence for Internet of Things
Kai Li, Conggai Li, Xin Yuan, Shenghong Li, Sai Zou, Syed Sohail Ahmed, Wei Ni, Dusit Niyato, Abbas Jamalipour, Falko Dressler, Ozgur B. Akan
https://arxiv.org/abs/2505.23792

Zero-Trust Foundation Models: A New Paradigm for Secure and Collaborative Artificial Intelligence for Internet of Things
This paper focuses on Zero-Trust Foundation Models (ZTFMs), a novel paradigm that embeds zero-trust security principles into the lifecycle of foundation models (FMs) for Internet of Things (IoT) systems. By integrating core tenets, such as continuous verification, least privilege access (LPA), data confidentiality, and behavioral analytics into the design, training, and deployment of FMs, ZTFMs can enable secure, privacy-preserving AI across distributed, heterogeneous, and potentially adversari…

"The Hague Declaration on Knowledge Discovery in the Digital Age" was published around 10 years ago. Very interesting, how things have changed since then. TDM for research is still in its infancy, and reuse in the context of #ai has caused a backlash against most of the 6 principles of the Declaration. Tellingly, the Declaration is only accessible via the internet archive:

Distributed Intelligence in the Computing Continuum with Active Inference
Victor Casamayor Pujol, Boris Sedlak, Tommaso Salvatori, Karl Friston, Schahram Dustdar
https://arxiv.org/abs/2505.24618

Distributed Intelligence in the Computing Continuum with Active Inference
The Computing Continuum (CC) is an emerging Internet-based computing paradigm that spans from local Internet of Things sensors and constrained edge devices to large-scale cloud data centers. Its goal is to orchestrate a vast array of diverse and distributed computing resources to support the next generation of Internet-based applications. However, the distributed, heterogeneous, and dynamic nature of CC platforms demands distributed intelligence for adaptive and resilient service management. Th…

There's another layer to this as well, I think. Any social media feed interlaces horrible things with wonderful things in a completely contextually devoid list. A funny cat picture and a traumatic picture or video of violence are both "rated" in the same way, with the same imaginary internet points, without any differentiation between good and bad.
I feel like this is also cooking our brains a bit.

Optimizing Server Load Distribution in Multimedia IoT Environments through LSTM-Based Predictive Algorithms
Somaye Imanpour, Ahmadreza Montazerolghaem, Saeed Afshari
https://arxiv.org/abs/2505.24806

Optimizing Server Load Distribution in Multimedia IoT Environments through LSTM-Based Predictive Algorithms
The Internet of Multimedia Things (IoMT) represents a significant advancement in the evolution of IoT technologies, focusing on the transmission and management of multimedia streams. As the volume of data continues to surge and the number of connected devices grows exponentially, internet traffic has reached unprecedented levels, resulting in challenges such as server overloads and deteriorating service quality. Traditional computer network architectures were not designed to accommodate this ra…

Distributed gradient methods under heavy-tailed communication noise
Manojlo Vukovic, Dusan Jakovetic, Dragana Bajovic, Soummya Kar
https://arxiv.org/abs/2505.24464

Distributed gradient methods under heavy-tailed communication noise
We consider a standard distributed optimization problem in which networked nodes collaboratively minimize the sum of their locally known convex costs. For this setting, we address for the first time the fundamental problem of design and analysis of distributed methods to solve the above problem when inter-node communication is subject to \emph{heavy-tailed} noise. Heavy-tailed noise is highly relevant and frequently arises in densely deployed wireless sensor and Internet of Things (IoT) network…

The Internet needs more of this, and fewer Nazis. That would truly be a better world.
I appreciate that he hired a real person, rather than AI slop.
https://ericwbailey.website/published/you-must-listen-to-rfc-2119/

You MUST listen to RFC 2119
It turns out you can just pay people to do things.

E-WAN: Efficient Communication in Energy Harvesting Low-Power Networks
Naomi Stricker, David Blaser, Andres Gomez, Lothar Thiele
https://arxiv.org/abs/2506.23788

E-WAN: Efficient Communication in Energy Harvesting Low-Power Networks
The ever-increasing number of distributed embedded systems in the context of the Internet of Things (IoT), Wireless Sensor Networks (WSN), and Cyber-Physical Systems (CPS) rely on wireless communication to collect and exchange data. Nodes can employ single-hop communication which, despite its ease, may necessitate energy-intensive long-range communication to cover long distances. Conversely, multi-hop communication allows for more energy-efficient short-range communication since nodes can rely …

This https://arxiv.org/abs/2406.15119 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSD_…

Breaking Resource Barriers in Speech Emotion Recognition via Data Distillation
Speech emotion recognition (SER) plays a crucial role in human-computer interaction. The emergence of edge devices in the Internet of Things (IoT) presents challenges in constructing intricate deep learning models due to constraints in memory and computational resources. Moreover, emotional speech data often contains private information, raising concerns about privacy leakage during the deployment of SER models. To address these challenges, we propose a data distillation framework to facilitate…

Performance Measurements in the AI-Centric Computing Continuum Systems
Praveen Kumar Donta, Qiyang Zhang, Schahram Dustdar
https://arxiv.org/abs/2506.22884

Performance Measurements in the AI-Centric Computing Continuum Systems
Over the Eight decades, computing paradigms have shifted from large, centralized systems to compact, distributed architectures, leading to the rise of the Distributed Computing Continuum (DCC). In this model, multiple layers such as cloud, edge, Internet of Things (IoT), and mobile platforms work together to support a wide range of applications. Recently, the emergence of Generative AI and large language models has further intensified the demand for computational resources across this continuum…

Our company sells products to test internet protocol implementations under unusual, but possible, situations. (Many fail.)
We sell worldwide, so we have to attach various code numbers to identify the type of product to the import/export (tariff/duty) government agents who make sure that things coming into their countries pay the proper fees.
Well, that list of code numbers appears to have been created in the 1970s and not updated since. So if you are selling a VHS VCR or a Fax m…

Wireless Home Automation Using Social Networking Websites
Divya Alok Gupta, Dwith Chenna, B. Aditya Vighnesh Ramakanth
https://arxiv.org/abs/2506.22482 htt…

Wireless Home Automation Using Social Networking Websites
With the advent of Internet of Things, Wireless Home Automation Systems WHAS are gradually gaining popularity. These systems are faced with multiple challenges such as security; controlling a variety of home appliances with a single interface and user friendliness. In this paper we propose a system that uses secure authentication systems of social networking websites such as Twitter, tracks the end-users activities on the social network and then control his or her domestic appliances. At the en…

A Mixed-Signal Photonic SRAM-based High-Speed Energy-Efficient Photonic Tensor Core with Novel Electro-Optic ADC
Md Abdullah-Al Kaiser, Sugeet Sunder, Ajey P. Jacob, Akhilesh R. Jaiswal
https://arxiv.org/abs/2506.22705

A Mixed-Signal Photonic SRAM-based High-Speed Energy-Efficient Photonic Tensor Core with Novel Electro-Optic ADC
The rapid surge in data generated by Internet of Things (IoT), artificial intelligence (AI), and machine learning (ML) applications demands ultra-fast, scalable, and energy-efficient hardware, as traditional von Neumann architectures face significant latency and power challenges due to data transfer bottlenecks between memory and processing units. Furthermore, conventional electrical memory technologies are increasingly constrained by rising bitline and wordline capacitance, as well as the resi…

Distributed Iterative ML and Message Passing for Grant-Free Cell-Free Massive MIMO Systems
Zilu Zhao, Christian Forsch, Laura Cottatellucci, Dirk Slock
https://arxiv.org/abs/2507.21363

Distributed Iterative ML and Message Passing for Grant-Free Cell-Free Massive MIMO Systems
Cell-Free (CF) Massive Multiple-Input Multiple-Output (MaMIMO) is considered one of the leading candidates for enabling next-generation wireless communication. With the growing interest in the Internet of Things (IoT), the Grant-Free (GF) access scheme has emerged as a promising solution to support massive device connectivity. The integration of GF and CF-MaMIMO introduces significant challenges, particularly in designing distributed algorithms for activity detection and pilot contamination mit…

Shilling Like It’s 1999: Ars, Anthropic, and the Internet of Other People’s Things https://musictechpolicy.com/2025/08/16/shilling-like-its-1999-ars-anthropic-and-the-internet-of-other-peoples-things/

Shilling Like It’s 1999: Ars, Anthropic, and the Internet of Other People’s Things
Ars Technica covers a massive AI copyright lawsuit with quotes from “public interest” groups tied to Google funding. This piece exposes the shill network, dismantles the ‘ownership is too har…

Securing the Internet of Medical Things (IoMT): Real-World Attack Taxonomy and Practical Security Measures
Suman Deb, Emil Lupu, Emm Mic Drakakis, Anil Anthony Bharath, Zhen Kit Leung, Guang Rui Ma, Anupam Chattopadhyay
https://arxiv.org/abs/2507.19609

Securing the Internet of Medical Things (IoMT): Real-World Attack Taxonomy and Practical Security Measures
The Internet of Medical Things (IoMT) has the potential to radically improve healthcare by enabling real-time monitoring, remote diagnostics, and AI-driven decision making. However, the connectivity, embedded intelligence, and inclusion of a wide variety of novel sensors expose medical devices to severe cybersecurity threats, compromising patient safety and data privacy. In addition, many devices also have direct capacity - individually or in conjunction with other IoMT devices - to perform act…

Google Workspace is full of dire warnings about how you can try things but they won't work for a long time (maybe). Sometimes that's because of DNS and Internet caching problems. Sometimes it's because Google made a decision in 2001 it was OK to store data in databases that didn't commit immediately and they thought it was OK to show the user inconsistent state. Twenty-four years later that awful decision persists, even if my data doesn't.

Innovative Research on IoT Architecture and Robotic Operating Platforms: Applications of Large Language Models and Generative AI
Huiwen Han
https://arxiv.org/abs/2506.22477

Innovative Research on IoT Architecture and Robotic Operating Platforms: Applications of Large Language Models and Generative AI
This paper introduces an innovative design for robotic operating platforms, underpinned by a transformative Internet of Things (IoT) architecture, seamlessly integrating cutting-edge technologies such as large language models (LLMs), generative AI, edge computing, and 5G networks. The proposed platform aims to elevate the intelligence and autonomy of IoT systems and robotics, enabling them to make real-time decisions and adapt dynamically to changing environments. Through a series of compelling…

Movable Antennas-aided Wireless Energy Transfer for the Internet of Things
Osmel Mart\'inez Rosabal, Onel Alcaraz L\'opez, Marco Di Renzo, Richard Demo Souza, Hirley Alves
https://arxiv.org/abs/2506.21966

Movable Antennas-aided Wireless Energy Transfer for the Internet of Things
Recent advancements in movable antennas (MAs) technology create new opportunities for 6G and beyond wireless systems. MAs are promising for radio frequency wireless energy transfer because they can dynamically adjust antenna positions, improving energy efficiency and scalability. This work aims to minimize the power consumed by an analog beamforming power beacon equipped with independently-controlled MAs (IMAs) for charging multiple single-antenna devices. To this end, we enforce a minimum sepa…

On the Role of Color Temperature and Color Rendering Index of White-Light LEDs on the Theoretical Efficiency Limit of Indoor Photovoltaics
Aditi Sharma, Alexander A. Guaman, Jason A. R\"ohr
https://arxiv.org/abs/2506.20811

On the Role of Color Temperature and Color Rendering Index of White-Light LEDs on the Theoretical Efficiency Limit of Indoor Photovoltaics
As the Internet of Things (IoT) continues to grow, the demand for sustainable indoor power sources is increasing. Indoor photovoltaics (IPVs), which are currently in development, present a renewable solution but need to be designed to match specific light sources. While previous studies have emphasized the role of white-light LED color temperature (CT) in determining IPV efficiency and optimum bandgap energy, the role of color rendering index (CRI) remains less understood. In this study, we emp…

A Knowledge Distillation-empowered Adaptive Federated Reinforcement Learning Framework for Multi-Domain IoT Applications Scheduling
Zhiyu Wang, Mohammad Goudarzi, Mingming Gong, Rajkumar Buyya
https://arxiv.org/abs/2508.21328

A Knowledge Distillation-empowered Adaptive Federated Reinforcement Learning Framework for Multi-Domain IoT Applications Scheduling
The rapid proliferation of Internet of Things (IoT) applications across heterogeneous Cloud-Edge-IoT environments presents significant challenges in distributed scheduling optimization. Existing approaches face issues, including fixed neural network architectures that are incompatible with computational heterogeneity, non-Independent and Identically Distributed (non-IID) data distributions across IoT scheduling domains, and insufficient cross-domain collaboration mechanisms. This paper proposes…

An object-centric core metamodel for IoT-enhanced event logs
Yannis Bertrand, Christian Imenkamp, Lukas Malburg, Matthias Ehrendorfer, Marco Franceschetti, Joscha Gr\"uger, Francesco Leotta, J\"urgen Mangler, Ronny Seiger, Agnes Koschmider, Stefanie Rinderle-Ma, Barbara Weber, Estefania Serral
https://arxiv.org/abs/250…

An object-centric core metamodel for IoT-enhanced event logs
Advances in Internet-of-Things (IoT) technologies have prompted the integration of IoT devices with business processes (BPs) in many organizations across various sectors, such as manufacturing, healthcare and smart spaces. The proliferation of IoT devices leads to the generation of large amounts of IoT data providing a window on the physical context of BPs, which facilitates the discovery of new insights about BPs using process mining (PM) techniques. However, to achieve these benefits, IoT dat…

FAST-LoRa: An Efficient Simulation Framework for Evaluating LoRaWAN Networks and Transmission Parameter Strategies
Laura Acosta Garc\'ia, Juan Aznar Poveda, Fabian Margreiter, Antonio-Javier Garc\'ia S\'anchez, Joan Garc\'ia Haro, Thomas Fahringer, Jos\'e Lorente L\'opez, Jos\'e-V\'ictor Rodr\'iguez
https://

FAST-LoRa: An Efficient Simulation Framework for Evaluating LoRaWAN Networks and Transmission Parameter Strategies
The Internet of Things (IoT) has transformed many industries, and LoRaWAN (Long Range Wide Area Network), built on LoRa (Long Range) technology, has become a crucial solution for enabling scalable, low-cost, and energy-efficient communication in wide-area networks. Simulation tools are essential for optimizing the transmission parameters and, therefore, the energy efficiency and performance of LoRaWAN networks. While existing simulation frameworks accurately replicate real-world scenarios by in…

The unsettling rise of athlete stalkers, plus an NFL QB debate https://www.nytimes.com/athletic/6548086/2025/08/12/the-unsettling-rise-of-athlete-stalkers-plus-an-nfl-qb-debate/

Enhancing IoT Intrusion Detection Systems through Adversarial Training
Karma Gurung, Ashutosh Ghimire, Fathi Amsaad
https://arxiv.org/abs/2507.19739 https://

Enhancing IoT Intrusion Detection Systems through Adversarial Training
The augmentation of Internet of Things (IoT) devices transformed both automation and connectivity but revealed major security vulnerabilities in networks. We address these challenges by designing a robust intrusion detection system (IDS) to detect complex attacks by learning patterns from the NF-ToN-IoT v2 dataset. Intrusion detection has a realistic testbed through the dataset's rich and high-dimensional features. We combine distributed preprocessing to manage the dataset size with Fast Gradie…

Protect your privacy – browsers and search engines
 
Surveillance has always been a core part of fascist regimes. This is still true today, but is even more dangerous due to new data aggregation and AI technologies. The Internet sites you visit and the things you search for become a part of the larger surveillance database of your activities. You can take action now to reduce the risk to yourself, your friends and your loved ones while you browse the Internet. You should start now …

Digital Twin Technologies in Predictive Maintenance: Enabling Transferability via Sim-to-Real and Real-to-Sim Transfer
Sizhe Ma, Katherine A. Flanigan, Mario Berg\'es
https://arxiv.org/abs/2507.18449

Digital Twin Technologies in Predictive Maintenance: Enabling Transferability via Sim-to-Real and Real-to-Sim Transfer
The advancement of the Internet of Things (IoT) and Artificial Intelligence has catalyzed the evolution of Digital Twins (DTs) from conceptual ideas to more implementable realities. Yet, transitioning from academia to industry is complex due to the absence of standardized frameworks. This paper builds upon the authors' previously established functional and informational requirements supporting standardized DT development, focusing on a crucial aspect: transferability. While existing DT research…

Optimizing Indoor RIS-Aided Physical-Layer Security: A Codebook-Generation Methodology and Measurement-Based Analysis
Dimitris Kompostiotis, Dimitris Vordonis, Vassilis Paliouras, George C. Alexandropoulos
https://arxiv.org/abs/2506.22082

Optimizing Indoor RIS-Aided Physical-Layer Security: A Codebook-Generation Methodology and Measurement-Based Analysis
Sixth-Generation (6G) wireless networks aim to support innovative Internet-of-Things (IoT) applications that demand faster and more secure data transmission. While higher Open Systems Interconnection (OSI) layers employ measures like encryption and secure protocols to address data security, Physical-Layer Security (PLS) focuses on preventing information leakage to EavesDroppers (EDs) and mitigating the effects of jammers and spoofing attacks. In this context, the emerging technology of Reconfig…

The Internet IS a *set* of physical things that can be blown up by bombs.
However, where there used to be about a dozen places where you’d need to plant a substantial bomb to wreck the Internet, while now there are hundreds you’d need to hit simultaneously to affect most users. It isn’t even really feasible to figure out where those places all are, because the live interconnections are so complex and the fallback links are entirely invisible normally.

jwz (@jwz@mastodon.social)
Attached: 1 image I am really enjoying this series W0rldtr33, which takes the positions that A) the Internet is very literally evil, and B) the Internet is a physical thing that can be blown up with bombs... https://jwz.org/b/ykoy

AdapSCA-PSO: An Adaptive Localization Algorithm with AI-Based Hybrid SCA-PSO for IoT WSNs
Ze Zhang, Qian Dong, Wenhan Wang
https://arxiv.org/abs/2507.22317 https://

AdapSCA-PSO: An Adaptive Localization Algorithm with AI-Based Hybrid SCA-PSO for IoT WSNs
The accurate localization of sensor nodes is a fundamental requirement for the practical application of the Internet of Things (IoT). To enable robust localization across diverse environments, this paper proposes a hybrid meta-heuristic localization algorithm. Specifically, the algorithm integrates the Sine Cosine Algorithm (SCA), which is effective in global search, with Particle Swarm Optimization (PSO), which excels at local search. An adaptive switching module is introduced to dynamically s…

An Efficient Recommendation Filtering-based Trust Model for Securing Internet of Things
Muhammad Ibn Ziauddin, Rownak Rahad Rabbi, SM Mehrab, Fardin Faiyaz, Mosarrat Jahan
https://arxiv.org/abs/2508.17304

An Efficient Recommendation Filtering-based Trust Model for Securing Internet of Things
Trust computation is crucial for ensuring the security of the Internet of Things (IoT). However, current trust-based mechanisms for IoT have limitations that impact data security. Sliding window-based trust schemes cannot ensure reliable trust computation due to their inability to select appropriate window lengths. Besides, recent trust scores are emphasized when considering the effect of time on trust. This can cause a sudden change in overall trust score based on recent behavior, potentially …

STL-GO: Spatio-Temporal Logic with Graph Operators for Distributed Systems with Multiple Network Topologies
Yiqi Zhao, Xinyi Yu, Bardh Hoxha, Georgios Fainekos, Jyotirmoy V. Deshmukh, Lars Lindemann
https://arxiv.org/abs/2507.15147

STL-GO: Spatio-Temporal Logic with Graph Operators for Distributed Systems with Multiple Network Topologies
Multi-agent systems (MASs) consisting of a number of autonomous agents that communicate, coordinate, and jointly sense the environment to achieve complex missions can be found in a variety of applications such as robotics, smart cities, and internet-of-things applications. Modeling and monitoring MAS requirements to guarantee overall mission objectives, safety, and reliability is an important problem. Such requirements implicitly require reasoning about diverse sensing and communication modalit…

So farewell then Pinetime Watch 🪦.
It isn't showing any signs of charging. even after a completely-flat battery reset. Last hope gone.
Now nobody at all is running my custom software I think, and I have no way to fix the bugs.
Could replace it, but I'm not really paying any attention to the things it measures anyway. Heartrate is too unreliable to be useful and steps seems likely to be counting my leg-jiggles since I tend to hit 10,000 most days without trying or leaving the flat.
The software which tracks my time and mood is probably better running on the phone really. Easier to add notes and detail. Can't really input text from a watch. Location data can be added in ways the watch couldn't.
So back to not wearing a watch at all I think. Who needs it now we all carry pocket watches with internet and telephony.
#pineTime #smartWatch

GroupNL: Low-Resource and Robust CNN Design over Cloud and Device
Chuntao Ding, Jianhang Xie, Junna Zhang, Salman Raza, Shangguang Wang, Jiannong Cao
https://arxiv.org/abs/2506.12335

GroupNL: Low-Resource and Robust CNN Design over Cloud and Device
It has become mainstream to deploy Convolutional Neural Network (CNN) models on ubiquitous Internet of Things (IoT) devices with the help of the cloud to provide users with a variety of high-quality services. Most existing methods have two limitations: (i) low robustness in handling corrupted image data collected by IoT devices; and (ii) high consumption of computational and transmission resources. To this end, we propose the Grouped NonLinear transformation generation method (GroupNL), which g…

AirBreath Sensing: Protecting Over-the-Air Distributed Sensing Against Interference
Zhanwei Wang, Mingyao Cui, Huiling Yang, Qunsong Zeng, Min Sheng, Kaibin Huang
https://arxiv.org/abs/2508.11267

AirBreath Sensing: Protecting Over-the-Air Distributed Sensing Against Interference
A distinctive function of sixth-generation (6G) networks is the integration of distributed sensing and edge artificial intelligence (AI) to enable intelligent perception of the physical world. This resultant platform, termed integrated sensing and edge AI (ISEA), is envisioned to enable a broad spectrum of Internet-of-Things (IoT) applications, including remote surgery, autonomous driving, and holographic telepresence. Recently, the communication bottleneck confronting the implementation of an …

Exploring the Convergence of HCI and Evolving Technologies in Information Systems
Rajan Das Gupta, Ashikur Rahman, Md Imrul Hasan Showmick, Md. Yeasin Rahat, Md. Jakir Hossen
https://arxiv.org/abs/2506.08549

Exploring the Convergence of HCI and Evolving Technologies in Information Systems
Modern technology driven information systems are part of our daily lives. However, this deep integration poses new challenges to the human computer interaction (HCI) professionals. With the rapid growth of mobile and cloud computing and the Internet of Things (IoT), the demand for HCI specialists to design user-friendly and adaptable interfaces has never been more pressing. Especially for diverse user groups such as children, the elderly and people with disabilities who need interfaces tailored…

Communicating Smartly in Molecular Communication Environments: Neural Networks in the Internet of Bio-Nano Things
Jorge Torres G\'omez, Pit Hofmann, Lisa Y. Debus, Osman Tugay Ba\c{s}aran, Sebastian Lotter, Roya Khanzadeh, Stefan Angerbauer, Bige Deniz Unluturk, Sergi Abadal, Werner Haselmayr, Frank H. P. Fitzek, Robert Schober, Falko Dressler
ht…

Communicating Smartly in Molecular Communication Environments: Neural Networks in the Internet of Bio-Nano Things
Recent developments in the Internet of Bio-Nano Things (IoBNT) are laying the groundwork for innovative applications across the healthcare sector. Nanodevices designed to operate within the body, managed remotely via the internet, are envisioned to promptly detect and actuate on potential diseases. In this vision, an inherent challenge arises due to the limited capabilities of individual nanosensors; specifically, nanosensors must communicate with one another to collaborate as a cluster. Aiming…

Energy Management and Wake-up for IoT Networks Powered by Energy Harvesting
David Ernesto Ruiz-Guirola, Samuel Montejo-Sanchez, Israel Leyva-Mayorga, Zhu Han, Petar Popovski, Onel L. A. Lopez
https://arxiv.org/abs/2508.13825

Energy Management and Wake-up for IoT Networks Powered by Energy Harvesting
The rapid growth of the Internet of Things (IoT) presents sustainability challenges such as increased maintenance requirements and overall higher energy consumption. This motivates self-sustainable IoT ecosystems based on Energy Harvesting (EH). This paper treats IoT deployments in which IoT devices (IoTDs) rely solely on EH to sense and transmit information about events/alarms to a base station (BS). The objective is to effectively manage the duty cycling of the IoTDs to prolong battery life a…

From Moose:

An Efficient Lightweight Blockchain for Decentralized IoT
Faezeh Dehghan Tarzjani, Mostafa Salehi
https://arxiv.org/abs/2508.19219 https://arxiv.org/pdf/25…

An Efficient Lightweight Blockchain for Decentralized IoT
The Internet of Things (IoT) is applied in various fields, and the number of physical devices connected to the IoT is increasingly growing. There are significant challenges to the IoT's growth and development, mainly due to the centralized nature and large-scale IoT networks. The emphasis on the decentralization of IoT's architecture can overcome challenges to IoT's capabilities. A promising decentralized platform for IoT is blockchain. Owing to IoT devices' limited resources, traditional conse…

An Efficient Hardware Implementation of Elliptic Curve Point Multiplication over $GF(2^m)$ on FPGA
Ruby Kumari, Tapas Rout, Babul Saini, Jai Gopal Pandey, Abhijit Karmakar
https://arxiv.org/abs/2506.12359

An Efficient Hardware Implementation of Elliptic Curve Point Multiplication over $GF(2^m)$ on FPGA
Elliptic Curve Cryptography (ECC) is widely accepted for ensuring secure data exchange between resource-limited IoT devices. The National Institute of Standards and Technology (NIST) recommended implementation, such as B-163, is particularly well-suited for Internet of Things (IoT) applications. Here, Elliptic Curve Point Multiplication (ECPM) is the most time-critical and resource-intensive operation due to the finite field multiplier. This paper proposes a new implementation method of finite …

Co-Design of Sensing, Communications, and Control for Low-Altitude Wireless Networks
Haijia Jin, Jun Wu, Weijie Yuan, Fan Liu, Yuanhao Cui
https://arxiv.org/abs/2506.20970

Co-Design of Sensing, Communications, and Control for Low-Altitude Wireless Networks
The rapid advancement of Internet of Things (IoT) services and the evolution toward the sixth generation (6G) have positioned unmanned aerial vehicles (UAVs) as critical enablers of low-altitude wireless networks (LAWNs). This work investigates the co-design of integrated sensing, communication, and control ($\mathbf{SC^{2}}$) for multi-UAV cooperative systems with finite blocklength (FBL) transmission. In particular, the UAVs continuously monitor the state of the field robots and transmit thei…

RL-based Adaptive Task Offloading in Mobile-Edge Computing for Future IoT Networks
Ziad Qais Al Abbasi, Khaled M. Rabie, Senior Member, Xingwang Li, Senior Member, Wali Ullah Khan, Asma Abu Samah
https://arxiv.org/abs/2506.22474

RL-based Adaptive Task Offloading in Mobile-Edge Computing for Future IoT Networks
The Internet of Things (IoT) has been increasingly used in our everyday lives as well as in numerous industrial applications. However, due to limitations in computing and power capabilities, IoT devices need to send their respective tasks to cloud service stations that are usually located at far distances. Having to transmit data far distances introduces challenges for services that require low latency such as industrial control in factories and plants as well as artificial intelligence assiste…

Joint UAV Trajectory Planning and LEO Satellite Selection for Data Offloading in Space-Air-Ground Integrated Networks
Boran Wang, Ziye Jia, Can Cui, Qihui Wu
https://arxiv.org/abs/2506.12750

Joint UAV Trajectory Planning and LEO Satellite Selection for Data Offloading in Space-Air-Ground Integrated Networks
With the development of low earth orbit (LEO) satellites and unmanned aerial vehicles (UAVs), the space-air-ground integrated network (SAGIN) becomes a major trend in the next-generation networks. However, due to the instability of heterogeneous communication and time-varying characteristics of SAGIN, it is challenging to meet the remote Internet of Things (IoT) demands for data collection and offloading. In this paper, we investigate a two-phase hierarchical data uplink model in SAGIN. Specifi…

A Language-Agnostic Logical Relation for Message-Passing Protocols
Tesla Zhang, Sonya Simkin, Rui Li, Yue Yao, Stephanie Balzer
https://arxiv.org/abs/2506.10026

A Language-Agnostic Logical Relation for Message-Passing Protocols
Today's computing landscape has been gradually shifting to applications targeting distributed and *heterogeneous* systems, such as cloud computing and Internet of Things (IoT) applications. These applications are predominantly *concurrent*, employ *message-passing*, and interface with *foreign objects*, ranging from externally implemented code to actual physical devices such as sensors. Verifying that the resulting systems adhere to the intended protocol of interaction is challenging -- the usu…

This https://arxiv.org/abs/2501.07148 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

Implementing LoRa MIMO System for Internet of Things
Bandwidth constraints limit LoRa implementations. Contemporary IoT applications require higher throughput than that provided by LoRa. This work introduces a LoRa Multiple Input Multiple Output (MIMO) system and a spatial multiplexing algorithm to address LoRa's bandwidth limitation. The transceivers in the proposed approach modulate the signals on distinct frequencies of the same LoRa band. A Frequency Division Multiplexing (FDM) method is used at the transmitters to provide a wider MIMO channe…

NIST is done standardizing #ASCON, an encryption and hashing algorithm. I count that as a big win for #IoT security, in particular because the last review round's raised concerns were heeded and there is now a 32-bit tag mode usable for applications such as 802.15.4 link-layer security.
Congratulations…

NIST Finalizes ‘Lightweight Cryptography’ Standard to Protect Small Devices
Four related algorithms are now ready for use to protect data created and transmitted by the Internet of Things and other electronics

A Computer Vision and Depth Sensor-Powered Smart Cane for Real-Time Obstacle Detection and Navigation Assistance for the Visually Impaired
Sunkalp Chandra, Umang Sharma, Devesh Khilnani
https://arxiv.org/abs/2508.16698

A Computer Vision and Depth Sensor-Powered Smart Cane for Real-Time Obstacle Detection and Navigation Assistance for the Visually Impaired
Visual impairment impacts more than 2.2 billion people worldwide, and it greatly restricts independent mobility and access. Conventional mobility aids - white canes and ultrasound-based intelligent canes - are inherently limited in the feedback they can offer and generally will not be able to differentiate among types of obstacles in dense or complex environments. Here, we introduce the IoT Cane, an internet of things assistive navigation tool that integrates real-time computer vision with a tr…

Energy-Efficient Index and Code Index Modulations for Spread CPM Signals in Internet of Things
Long Yuan, Wenkun Wen, Junlin Liu, Peiran Wu, Minghua Xia
https://arxiv.org/abs/2508.10290

Energy-Efficient Index and Code Index Modulations for Spread CPM Signals in Internet of Things
The evolution of Internet of Things technologies is driven by four key demands: ultra-low power consumption, high spectral efficiency, reduced implementation cost, and support for massive connectivity. To address these challenges, this paper proposes two novel modulation schemes that integrate continuous phase modulation (CPM) with spread spectrum (SS) techniques. We begin by establishing the quasi-orthogonality properties of CPM-SS sequences. The first scheme, termed IM-CPM-SS, employs index m…

CITADEL: Continual Anomaly Detection for Enhanced Learning in IoT Intrusion Detection
Elvin Li, Onat Gungor, Zhengli Shang, Tajana Rosing
https://arxiv.org/abs/2508.19450 https:…

CITADEL: Continual Anomaly Detection for Enhanced Learning in IoT Intrusion Detection
The Internet of Things (IoT), with its high degree of interconnectivity and limited computational resources, is particularly vulnerable to a wide range of cyber threats. Intrusion detection systems (IDS) have been extensively studied to enhance IoT security, and machine learning-based IDS (ML-IDS) show considerable promise for detecting malicious activity. However, their effectiveness is often constrained by poor adaptability to emerging threats and the issue of catastrophic forgetting during c…

Spatially Correlated Blockage Aware Placement of RIS in IIoT Networks
Rashmi Kumari, Gourab Ghatak, Abhishek K. Gupta
https://arxiv.org/abs/2508.16946 https://

Spatially Correlated Blockage Aware Placement of RIS in IIoT Networks
We study the impact of deploying reconfigurable intelligent surfaces (RISs) in mitigating coverage gaps and enhancing transmission reliability in an industrial internet of things (IIoT) network. First, we consider a single blockage scenario and characterize the correlation between blocking events of the base station (BS)-user and the RIS-user links and study its impact on the probability of establishing a viable reflected link. Then, by considering multiple blockages, we derive the distribution…

Constant Modulus Waveforms for IoT-Centric Integrated Sensing and Communications
Tian Han, Shalanika Dayarathna, Rajitha Senanayake, Peter Smith, Aryan Kaushik, Alain Mourad, Richard A. Stirling-Gallacher, Jamie Evans
https://arxiv.org/abs/2506.21078

Constant Modulus Waveforms for IoT-Centric Integrated Sensing and Communications
Integrated sensing and communications (ISAC) is considered a key enabler to support application scenarios such as the Internet-of-Things (IoT) in which both communications and sensing play significant roles. Multi-carrier waveforms, such as orthogonal frequency division multiplexing (OFDM), have been considered as good candidates for ISAC due to their high communications data rate and good time bandwidth property for sensing. Nevertheless, their high peak-to-average-power-ratio (PAPR) values le…

$AutoGuardX$: A Comprehensive Cybersecurity Framework for Connected Vehicles
Muhammad Ali Nadeem, Bishwo Prakash Pokharel, Naresh Kshetri, Achyut Shankar, Gokarna Sharma
https://arxiv.org/abs/2508.18155

$AutoGuardX$: A Comprehensive Cybersecurity Framework for Connected Vehicles
The rapid integration of Internet of Things (IoT) and interconnected systems in modern vehicles not only introduced a new era of convenience, automation, and connected vehicles but also elevated their exposure to sophisticated cyber threats. This is especially evident in US and Canada, where cyber-enabled auto theft has surged in recent years, revealing the limitations of existing security measures for connected vehicles. In response, this paper proposes $AutoGuardX$, a comprehensive cybersecur…

QTCAJOSA: Low-Complexity Joint Offloading and Subchannel Allocation for NTN-Enabled IoMT
Alejandro Flores C., Konstantinos Ntontin, Ashok Bandi, Symeon Chatzinotas
https://arxiv.org/abs/2507.13242

QTCAJOSA: Low-Complexity Joint Offloading and Subchannel Allocation for NTN-Enabled IoMT
In this work, we consider the resource allocation problem for task offloading from Internet of Medical Things (IoMT) devices, to a non-terrestrial network. The architecture considers clusters of IoMT devices that offload their tasks to a dedicated unmanned aerial vehicle (UAV) serving as a multi-access edge computing (MEC) server, which can compute the task or further offload it to an available high-altitude platform station (HAPS) or to a low-earth orbit (LEO) satellite for remote computing. W…

A Survey on Cloud-Edge-Terminal Collaborative Intelligence in AIoT Networks
Jiaqi Wu, Jing Liu, Yang Liu, Lixu Wang, Zehua Wang, Wei Chen, Zijian Tian, Richard Yu, Victor C. M. Leung
https://arxiv.org/abs/2508.18803

A Survey on Cloud-Edge-Terminal Collaborative Intelligence in AIoT Networks
The proliferation of Internet of things (IoT) devices in smart cities, transportation, healthcare, and industrial applications, coupled with the explosive growth of AI-driven services, has increased demands for efficient distributed computing architectures and networks, driving cloud-edge-terminal collaborative intelligence (CETCI) as a fundamental paradigm within the artificial intelligence of things (AIoT) community. With advancements in deep learning, large language models (LLMs), and edge c…

Temperature-Resilient Reconfigurable PUF with Dual-Pulse Modulation based on SOT-MRAM Chip
Min Wang, Chuanpeng Jiang, Zhaohao Wang, Zhengyi Hou, Zhongkui Zhang, Yuanfu Zhao, Hongxi Liu, Weisheng Zhao
https://arxiv.org/abs/2508.16405

Temperature-Resilient Reconfigurable PUF with Dual-Pulse Modulation based on SOT-MRAM Chip
In the Internet of Things (IoT) era, hardware-based security solutions have become an emerging choice for enhancing end-terminal information security. As one of the hardware technologies, physical unclonable functions (PUFs) utilize the inherent variations in the manufacturing process to generate cryptographic keys. Reconfigurable PUFs (rPUFs), characterized by updating cryptographic keys, offer enhanced security ability for protecting massive amounts of data in dynamic operational scenarios. T…

Optimized Arithmetic Coding for Efficient Data Compression in the Resource-Constrained Internet of Things(IoT)
Vatsala Upadhyay, J. Kokila, Abhishek Vaish
https://arxiv.org/abs/2508.08840

Optimized Arithmetic Coding for Efficient Data Compression in the Resource-Constrained Internet of Things(IoT)
The Internet of Things (IoT) generates vast amounts of heterogeneous data, ranging from sensor readings to log alerts and images, that pose challenges to storage and data transmission in resource-constrained environments. In this context, lossless data compression techniques, like Arithmetic Coding, offer an effective solution owing to their high compression ratio. However, the standard Arithmetic Coding technique is computationally intensive, leading to high memory and processing overhead. Thi…

MOHAF: A Multi-Objective Hierarchical Auction Framework for Scalable and Fair Resource Allocation in IoT Ecosystems
Kushagra Agrawal, Polat Goktas, Anjan Bandopadhyay, Debolina Ghosh, Junali Jasmine Jena, Mahendra Kumar Gourisaria
https://arxiv.org/abs/2508.14830

MOHAF: A Multi-Objective Hierarchical Auction Framework for Scalable and Fair Resource Allocation in IoT Ecosystems
The rapid growth of Internet of Things (IoT) ecosystems has intensified the challenge of efficiently allocating heterogeneous resources in highly dynamic, distributed environments. Conventional centralized mechanisms and single-objective auction models, focusing solely on metrics such as cost minimization or revenue maximization, struggle to deliver balanced system performance. This paper proposes the Multi-Objective Hierarchical Auction Framework (MOHAF), a distributed resource allocation mech…

Dynamic Temporal Positional Encodings for Early Intrusion Detection in IoT
Ioannis Panopoulos, Maria-Lamprini A. Bartsioka, Sokratis Nikolaidis, Stylianos I. Venieris, Dimitra I. Kaklamani, Iakovos S. Venieris
https://arxiv.org/abs/2506.18114

Dynamic Temporal Positional Encodings for Early Intrusion Detection in IoT
The rapid expansion of the Internet of Things (IoT) has introduced significant security challenges, necessitating efficient and adaptive Intrusion Detection Systems (IDS). Traditional IDS models often overlook the temporal characteristics of network traffic, limiting their effectiveness in early threat detection. We propose a Transformer-based Early Intrusion Detection System (EIDS) that incorporates dynamic temporal positional encodings to enhance detection accuracy while maintaining computati…

A Contemporary Survey on Fluid Antenna Systems: Fundamentals and Networking Perspectives
Hanjiang Hong, Kai-Kit Wong, Hao Xu, Xinghao Guo, Farshad Rostami Ghadi, Yu Chen, Yin Xu, Chan-Byoung Chae, Baiyang Liu, Kin-Fai Tong, Yangyang Zhang
https://arxiv.org/abs/2506.13317

A Contemporary Survey on Fluid Antenna Systems: Fundamentals and Networking Perspectives
The explosive growth of teletraffic, fueled by the convergence of cyber-physical systems and data-intensive applications, such as the Internet of Things (IoT), autonomous systems, and immersive communications, demands a multidisciplinary suite of innovative solutions across the physical and network layers. Fluid antenna systems (FAS) represent a transformative advancement in antenna design, offering enhanced spatial degrees of freedom through dynamic reconfigurability. By exploiting spatial fle…

LoRaIN: A Constructive Interference-Assisted Reliable and Energy-Efficient LoRa Indoor Network
Mahbubur Rahman, Abusayeed Saifullah
https://arxiv.org/abs/2506.16409

LoRaIN: A Constructive Interference-Assisted Reliable and Energy-Efficient LoRa Indoor Network
LoRa is a promising communication technology for enabling the next-generation indoor Internet of Things applications. Very few studies, however, have analyzed its performance indoors. Besides, these indoor studies investigate mostly the RSSI and SNR of the received packets at the gateway, which, as we show, may not unfold the poor performance of LoRa and its MAC protocol, LoRaWAN, indoors in terms of reliability and energy-efficiency. In this paper, we extensively evaluate the performance of Lo…

SAFER-D: A Self-Adaptive Security Framework for Distributed Computing Architectures
Marco Stadler, Michael Vierhauser, Michael Riegler, Daniel Waghubinger, Johannes Sametinger
https://arxiv.org/abs/2506.16545

SAFER-D: A Self-Adaptive Security Framework for Distributed Computing Architectures
The rise of the Internet of Things and Cyber-Physical Systems has introduced new challenges on ensuring secure and robust communication. The growing number of connected devices increases network complexity, leading to higher latency and traffic. Distributed computing architectures (DCAs) have gained prominence to address these issues. This shift has significantly expanded the attack surface, requiring additional security measures to protect all components -- from sensors and actuators to edge n…

Talk with the Things: Integrating LLMs into IoT Networks
Alakesh Kalita
https://arxiv.org/abs/2507.17865 https://arxiv.org/pdf/2507.17865

Talk with the Things: Integrating LLMs into IoT Networks
The convergence of Large Language Models (LLMs) and Internet of Things (IoT) networks open new opportunities for building intelligent, responsive, and user-friendly systems. This work presents an edge-centric framework that integrates LLMs into IoT architectures to enable natural language-based control, context-aware decision-making, and enhanced automation. The proposed modular and lightweight Retrieval Augmented Generation (RAG)-based LLMs are deployed on edge computing devices connected to I…

A Model Aware AIGC Task Offloading Algorithm in IIoT Edge Computing
Xin Wang, Xiao Huan Li, Xun Wang
https://arxiv.org/abs/2507.11560 https://

A Model Aware AIGC Task Offloading Algorithm in IIoT Edge Computing
The integration of the Industrial Internet of Things (IIoT) with Artificial Intelligence-Generated Content (AIGC) offers new opportunities for smart manufacturing, but it also introduces challenges related to computation-intensive tasks and low-latency demands. Traditional generative models based on cloud computing are difficult to meet the real-time requirements of AIGC tasks in IIoT environments, and edge computing can effectively reduce latency through task offloading. However, the dynamic n…

Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions
Ruichen Zhang, Guangyuan Liu, Yinqiu Liu, Changyuan Zhao, Jiacheng Wang, Yunting Xu, Dusit Niyato, Jiawen Kang, Yonghui Li, Shiwen Mao, Sumei Sun, Xuemin Shen, Dong In Kim
https://arxiv.org/abs/2508.18725

Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions
The rapid expansion of sixth-generation (6G) wireless networks and the Internet of Things (IoT) has catalyzed the evolution from centralized cloud intelligence towards decentralized edge general intelligence. However, traditional edge intelligence methods, characterized by static models and limited cognitive autonomy, fail to address the dynamic, heterogeneous, and resource-constrained scenarios inherent to emerging edge networks. Agentic artificial intelligence (Agentic AI) emerges as a transf…

Towards Sustainable Computing: Exploring Energy Consumption Efficiency of Alternative Configurations and Workloads in an Open Source Messaging System
Maria Voreakou, George Kousiouris, Mara Nikolaidou
https://arxiv.org/abs/2506.10693

Towards Sustainable Computing: Exploring Energy Consumption Efficiency of Alternative Configurations and Workloads in an Open Source Messaging System
Energy consumption in current large scale computing infrastructures is becoming a critical issue, especially with the growing demand for centralized systems such as cloud environments. With the advancement of microservice architectures and the Internet of Things, messaging systems have become an integral and mainstream part of modern computing infrastructures, carrying out significant workload in a majority of applications. In this paper, we describe an experimental process to explore energy-ba…

How To Mitigate And Defend Against DDoS Attacks In IoT Devices
Ifiyemi Leigha, Basak Comlekcioglu, Maria Pilar Bezanilla
https://arxiv.org/abs/2507.11772 h…

How To Mitigate And Defend Against DDoS Attacks In IoT Devices
Distributed Denial of Service (DDoS) attacks have become increasingly prevalent and dangerous in the context of Internet of Things (IoT) networks, primarily due to the low-security configurations of many connected devices. This paper analyzes the nature and impact of DDoS attacks such as those launched by the Mirai botnet, and proposes layered mitigation strategies tailored to IoT environments. Key solutions explored include IPv6 Unique Local Addresses (ULA), edge computing, software-defined ne…

Spatio-Temporal Information Freshness for Remote Source Monitoring in IoT Systems
Andrea Munari, Federico Chiariotti, Leonardo Badia, Petar Popovski
https://arxiv.org/abs/2506.04804

Spatio-Temporal Information Freshness for Remote Source Monitoring in IoT Systems
The widespread adoption of age of information (AoI) as a meaningful and analytically tractable information freshness metric has led to a wide body of work on the timing performance of Internet of things (IoT) systems. However, the spatial correlation inherent to environmental monitoring has been mostly neglected in the recent literature, due to the significant modeling complexity it introduces. In this work, we address this gap by presenting a model of spatio-temporal information freshness, con…

RIS-assisted ISAC Systems for Industrial Revolution 6.0: Exploring the Near-field and Far-field Coexistence
Seonghoon Yoo, Jaemin Jung, Seongah Jeong, Jinkyu Kang, Markku Juntti, Joonhyuk Kang
https://arxiv.org/abs/2507.07643

RIS-assisted ISAC Systems for Industrial Revolution 6.0: Exploring the Near-field and Far-field Coexistence
The Industrial Internet of Things (IIoT) has emerged as a key technology for realizing the vision of Industry 6.0, requiring the seamless integration of diverse connected devices. In particular, integrated sensing and communication (ISAC) plays a critical role in supporting real-time control and automation within IIoT systems. In this paper, we explore reconfigurable intelligent surface (RIS)-assisted ISAC systems for IIoT in the coexistence of near-field and far-field regions. The system consi…

Distributed system perspective on Backscatter systems
Jincheng Guan, Jun Zhang
https://arxiv.org/abs/2506.04833 https://arxiv.org/pdf…

Distributed system perspective on Backscatter systems
Backscatter system is a system based on backscatter communication technology, which is a low cost, low power consumption and easy to deploy communication technology. At present, the backscatter technology is mainly applied to RFID tags and the Internet of Things and other fields. With the rapid development of the Internet of Things, the application of backscatter systems is increasing. Moreover, the backscatter system is essentially a distributed system, but existing research rarely conducts st…

Load-Altering Attacks Against Power Grids: A Case Study Using the GB-36 Bus System Open Dataset
Syed Irtiza Maksud, Subhash Lakshminarayana
https://arxiv.org/abs/2508.08945 http…

Load-Altering Attacks Against Power Grids: A Case Study Using the GB-36 Bus System Open Dataset
The growing digitalization and the rapid adoption of high-powered Internet-of-Things (IoT)-enabled devices (e.g., EV charging stations) have increased the vulnerability of power grids to cyber threats. In particular, the so-called Load Altering Attacks (LAAs) can trigger rapid frequency fluctuations and potentially destabilize the power grid. This paper aims to bridge the gap between academic research and practical application by using open-source datasets released by grid operators. It investi…

A Grant-free Coded Random Access Scheme for Near-field Communications
Enrico Testi, Giulia Torcolacci, Nicol\`o Decarli, Davide Dardari, Enrico Paolini
https://arxiv.org/abs/2508.15673

A Grant-free Coded Random Access Scheme for Near-field Communications
The industrial Internet of things (IIoT) is revolutionizing industrial processes by facilitating massive machine-type communications among countless interconnected devices. To efficiently handle the resulting large-scale and sporadic traffic, grant-free random access protocols-especially coded random access (CRA)-have emerged as scalable and reliable solutions. At the same time, advancements in wireless hardware, including extremely large-scale MIMO arrays and high-frequency communication (e.g.…

Lightweight and High-Throughput Secure Logging for Internet of Things and Cold Cloud Continuum
Saif E. Nouma, Attila A. Yavuz
https://arxiv.org/abs/2506.08781

Lightweight and High-Throughput Secure Logging for Internet of Things and Cold Cloud Continuum
The growing deployment of resource-limited Internet of Things (IoT) devices and their expanding attack surfaces demand efficient and scalable security mechanisms. System logs are vital for the trust and auditability of IoT, and offloading their maintenance to a Cold Storage-as-a-Service (Cold-STaaS) enhances cost-effectiveness and reliability. However, existing cryptographic logging solutions either burden low-end IoT devices with heavy computation or create verification delays and storage inef…

Energy-Efficient Real-Time Job Mapping and Resource Management in Mobile-Edge Computing
Chuanchao Gao, Niraj Kumar, Arvind Easwaran
https://arxiv.org/abs/2506.12686

Energy-Efficient Real-Time Job Mapping and Resource Management in Mobile-Edge Computing
Mobile-edge computing (MEC) has emerged as a promising paradigm for enabling Internet of Things (IoT) devices to handle computation-intensive jobs. Due to the imperfect parallelization of algorithms for job processing on servers and the impact of IoT device mobility on data communication quality in wireless networks, it is crucial to jointly consider server resource allocation and IoT device mobility during job scheduling to fully benefit from MEC, which is often overlooked in existing studies.…

Low-Power and Accurate IoT Monitoring Under Radio Resource Constraint
Takaho Shimokasa, Hiroyuki Yomo, Federico Chiariotti, Junya Shiraishi, Petar Popovski
https://arxiv.org/abs/2507.15338

Low-Power and Accurate IoT Monitoring Under Radio Resource Constraint
This paper investigates how to achieve both low-power operations of sensor nodes and accurate state estimation using Kalman filter for internet of things (IoT) monitoring employing wireless sensor networks under radio resource constraint. We consider two policies used by the base station to collect observations from the sensor nodes: (i) an oblivious policy, based on statistics of the observations, and (ii) a decentralized policy, based on autonomous decision of each sensor based on its instant…

Reporte de vulnerabilidades en IIoT. Proyecto DEFENDER
Pedro Almansa Jim\'enez, Lorenzo Fern\'andez Maim\'o, \'Angel Luis Per\'ales G\'omez
https://arxiv.org/abs/2507.10819

Reporte de vulnerabilidades en IIoT. Proyecto DEFENDER
The main objective of this technical report is to conduct a comprehensive study on devices operating within Industrial Internet of Things (IIoT) environments, describing the scenarios that define this category and analysing the vulnerabilities that compromise their security. To this end, the report seeks to identify and examine the main classes of IIoT devices, detailing their characteristics, functionalities, and roles within industrial systems. This analysis enables a better understanding of …

Reinforcement Learning-Based Policy Optimisation For Heterogeneous Radio Access
Anup Mishra, \v{C}edomir Stefanovi\'c, Xiuqiang Xu, Petar Popovski, Israel Leyva-Mayorga
https://arxiv.org/abs/2506.15273

Reinforcement Learning-Based Policy Optimisation For Heterogeneous Radio Access
Flexible and efficient wireless resource sharing across heterogeneous services is a key objective for future wireless networks. In this context, we investigate the performance of a system where latency-constrained internet-of-things (IoT) devices coexist with a broadband user. The base station adopts a grant-free access framework to manage resource allocation, either through orthogonal radio access network (RAN) slicing or by allowing shared access between services. For the IoT users, we propos…

Physical Layer Challenge-Response Authentication between Ambient Backscatter Devices
Yifan Zhang, Yongchao Dang, Masoud Kaveh, Zheng Yan, Riku J\"antti, Zhu Han
https://arxiv.org/abs/2506.18767

Physical Layer Challenge-Response Authentication between Ambient Backscatter Devices
Ambient backscatter communication (AmBC) has become an integral part of ubiquitous Internet of Things (IoT) applications due to its energy-harvesting capabilities and ultra-low-power consumption. However, the open wireless environment exposes AmBC systems to various attacks, and existing authentication methods cannot be implemented between resource-constrained backscatter devices (BDs) due to their high computational demands.To this end, this paper proposes PLCRA-BD, a novel physical layer chal…

6G Infrastructures for Edge AI: An Analytical Perspective
Kurt Horvath, Shpresa Tuda, Blerta Idrizi, Stojan Kitanov, Fisnik Doko, Dragi Kimovski
https://arxiv.org/abs/2506.10570

6G Infrastructures for Edge AI: An Analytical Perspective
The convergence of Artificial Intelligence (AI) and the Internet of Things has accelerated the development of distributed, network-sensitive applications, necessitating ultra-low latency, high throughput, and real-time processing capabilities. While 5G networks represent a significant technological milestone, their ability to support AI-driven edge applications remains constrained by performance gaps observed in real-world deployments. This paper addresses these limitations and highlights criti…

The Trip to ZigBee Backscatter across a Decade, a Systematic Review
Yang Liu
https://arxiv.org/abs/2506.13822 https://arxiv.org/pdf/2…

The Trip to ZigBee Backscatter across a Decade, a Systematic Review
The field of backscatter communication has undergone a profound transformation, evolving from a niche technology for radio-frequency identification (RFID) into a sophisticated paradigm poised to enable a truly battery-free Internet of Things (IoT). This evolution is built upon a deepening understanding of the fundamental principles governing these ultra-low-power links. Modern backscatter systems are no longer simple reflectors of continuous waves but are increasingly designed to interact with …

Decoding and Engineering the Phytobiome Communication for Smart Agriculture
Fatih Gulec, Hamdan Awan, Nigel Wallbridge, Andrew W. Eckford
https://arxiv.org/abs/2508.03584 https:…

Decoding and Engineering the Phytobiome Communication for Smart Agriculture
Smart agriculture applications, integrating technologies like the Internet of Things and machine learning/artificial intelligence (ML/AI) into agriculture, hold promise to address modern challenges of rising food demand, environmental pollution, and water scarcity. Alongside the concept of the phytobiome, which defines the area including the plant, its environment, and associated organisms, and the recent emergence of molecular communication (MC), there exists an important opportunity to advanc…

A Robust Cross-Domain IDS using BiGRU-LSTM-Attention for Medical and Industrial IoT Security
Afrah Gueriani, Hamza Kheddar, Ahmed Cherif Mazari, Mohamed Chahine Ghanem
https://arxiv.org/abs/2508.12470 …

A Robust Cross-Domain IDS using BiGRU-LSTM-Attention for Medical and Industrial IoT Security
The increased Internet of Medical Things IoMT and the Industrial Internet of Things IIoT interconnectivity has introduced complex cybersecurity challenges, exposing sensitive data, patient safety, and industrial operations to advanced cyber threats. To mitigate these risks, this paper introduces a novel transformer-based intrusion detection system IDS, termed BiGAT-ID a hybrid model that combines bidirectional gated recurrent units BiGRU, long short-term memory LSTM networks, and multi-head att…

Backscattering-Based Security in Wireless Power Transfer Applied to Battery-Free BLE Sensors
Taki Eddine Djidjekh (INSA Toulouse, LAAS-MINC), Ga\"el Loubet (LAAS-MINC, INSA Toulouse), Alexandru Takacs (LAAS-MINC, UT)
https://arxiv.org/abs/2507.13042

Backscattering-Based Security in Wireless Power Transfer Applied to Battery-Free BLE Sensors
The integration of security and energy efficiency in Internet of Things systems remains a critical challenge, particularly for battery-free and resource-constrained devices. This paper explores the scalability and protocol-agnostic nature of a backscattering-based security mechanism by integrating it into Bluetooth Low Energy battery-free Wireless Sensor Network. The proposed approach leverages the Wireless Power Transfer link, traditionally used for energy harvesting, to generate additional id…

Qualitative Assessment of Low Power Wide Area Network Protocols and their Security Aspect
Wesley dos Reis Bezerra, Lais Machado Bezerra, Carlos Becker Westphal
https://arxiv.org/abs/2507.08677

Qualitative Assessment of Low Power Wide Area Network Protocols and their Security Aspect
There are currently many communication options in the Internet of Things, even in particular areas such as constrained and battery-powered devices, such as Low Power Wide Area Networks. Understanding the differences and characteristics of each option is a challenge, even for professionals and researchers in the field. To meet this need, this work analyses the qualitative characteristics of Low Power Wide Area Network protocols and the challenges and opportunities of using constrained devices fo…

Optimizing Federated Learning for Scalable Power-demand Forecasting in Microgrids
Roopkatha Banerjee, Sampath Koti, Gyanendra Singh, Anirban Chakraborty, Gurunath Gurrala, Bhushan Jagyasi, Yogesh Simmhan
https://arxiv.org/abs/2508.08022

Optimizing Federated Learning for Scalable Power-demand Forecasting in Microgrids
Real-time monitoring of power consumption in cities and micro-grids through the Internet of Things (IoT) can help forecast future demand and optimize grid operations. But moving all consumer-level usage data to the cloud for predictions and analysis at fine time scales can expose activity patterns. Federated Learning~(FL) is a privacy-sensitive collaborative DNN training approach that retains data on edge devices, trains the models on private data locally, and aggregates the local models in the…

Data-driven Trust Bootstrapping for Mobile Edge Computing-based Industrial IoT Services
Prabath Abeysekara, Hai Dong
https://arxiv.org/abs/2508.12560 https://

Data-driven Trust Bootstrapping for Mobile Edge Computing-based Industrial IoT Services
We propose a data-driven and context-aware approach to bootstrap trustworthiness of homogeneous Internet of Things (IoT) services in Mobile Edge Computing (MEC) based industrial IoT (IIoT) systems. The proposed approach addresses key limitations in adapting existing trust bootstrapping approaches into MEC-based IIoT systems. These key limitations include, the lack of opportunity for a service consumer to interact with a lesser-known service over a prolonged period of time to get a robust measur…

Duty-Cycling is Not Enough in Constrained IoT Networking: Revealing the Energy Savings of Dynamic Clock Scaling
Michel Rottleuthner, Thomas C. Schmidt, Matthias W\"ahlisch
https://arxiv.org/abs/2508.09620

Duty-Cycling is Not Enough in Constrained IoT Networking: Revealing the Energy Savings of Dynamic Clock Scaling
Minimizing energy consumption of low-power wireless nodes is a persistent challenge from the constrained Internet of Things (IoT). In this paper, we start from the observation that constrained IoT devices have largely different hardware (im-)balances than full-scale machines. We find that the performance gap between MCU and network throughput on constrained devices enables minimal energy delay product (EDP) for IoT networking at largely reduced clock frequencies. We analyze the potentials by in…

Toward a Lightweight, Scalable, and Parallel Secure Encryption Engine
Rasha Karakchi, Rye Stahle-Smith, Nishant Chinnasami, Tiffany Yu
https://arxiv.org/abs/2506.15070

Toward a Lightweight, Scalable, and Parallel Secure Encryption Engine
The exponential growth of Internet of Things (IoT) applications has intensified the demand for efficient, high-throughput, and energy-efficient data processing at the edge. Conventional CPU-centric encryption methods suffer from performance bottlenecks and excessive data movement, especially in latency-sensitive and resource-constrained environments. In this paper, we present SPiME, a lightweight, scalable, and FPGA-compatible Secure Processor-in-Memory Encryption architecture that integrates t…

Age of Information Optimization in Laser-charged UAV-assisted IoT Networks: A Multi-agent Deep Reinforcement Learning Method
Geng Sun, Likun Zhang, Jiahui Li, Jing Wu, Jiacheng Wang, Zemin Sun, Changyuan Zhao, Victor C. M. Leung
https://arxiv.org/abs/2507.08429

Age of Information Optimization in Laser-charged UAV-assisted IoT Networks: A Multi-agent Deep Reinforcement Learning Method
The integration of unmanned aerial vehicles (UAVs) with Internet of Things (IoT) networks offers promising solutions for efficient data collection. However, the limited energy capacity of UAVs remains a significant challenge. In this case, laser beam directors (LBDs) have emerged as an effective technology for wireless charging of UAVs during operation, thereby enabling sustained data collection without frequent returns to charging stations (CSs). In this work, we investigate the age of informa…

Extreme Learning Machine Based System for DDoS Attacks Detections on IoMT Devices
Nelly Elsayed, Lily Dzamesi, Zag ElSayed, Murat Ozer
https://arxiv.org/abs/2507.05132

Extreme Learning Machine Based System for DDoS Attacks Detections on IoMT Devices
The Internet of Medical Things (IoMT) represents a paradigm shift in the healthcare sector, enabling the interconnection of medical devices, sensors, and systems to enhance patient monitoring, diagnosis, and management. The rapid evolution of IoMT presents significant benefits to the healthcare domains. However, there is a rapid increase in distributed denial of service (DDoS) attacks on the IoMT networks due to several vulnerabilities in the IoMT-connected devices, which negatively impact pati…

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initial toot: https://mastoxiv.page/@arXiv_csNI_…

Extending Internet Access Over LoRa for Internet of Things and Critical Applications
LoRa bridges the gap between remote locations and mainstream networks, enabling large-scale Internet of Things (IoT) deployments. Despite the recent advancements around LoRa, Internet access over this technology is still largely unexplored. Most existing solutions only handle packets within the local LoRa network and do not interact with web applications. This limits the scalability and the ability to deliver essential web services in disconnected regions. This work proposes and implements ILoR…

Age of Information in Unreliable Tandem Queues
Muthukrishnan Senthilkumar, Aresh Dadlani, Hina Tabassum
https://arxiv.org/abs/2506.09245 https://

Age of Information in Unreliable Tandem Queues
Stringent demands for timely information delivery, driven by the widespread adoption of real-time applications and the Internet of Things, have established the age of information (AoI) as a critical metric for quantifying data freshness. Existing AoI models often assume multi-hop communication networks with fully reliable nodes, which may not accurately capture scenarios involving node transmission failures. This paper presents an analytical framework for two configurations of tandem queue syst…

Physical Layer-Based Device Fingerprinting for Wireless Security: From Theory to Practice
Junqing Zhang, Francesco Ardizzon, Mattia Piana, Guanxiong Shen, Stefano Tomasin
https://arxiv.org/abs/2506.09807

Physical Layer-Based Device Fingerprinting for Wireless Security: From Theory to Practice
The identification of the devices from which a message is received is part of security mechanisms to ensure authentication in wireless communications. Conventional authentication approaches are cryptography-based, which, however, are usually computationally expensive and not adequate in the Internet of Things (IoT), where devices tend to be low-cost and with limited resources. This paper provides a comprehensive survey of physical layer-based device fingerprinting, which is an emerging device a…

User Head Movement-Predictive XR in Immersive H2M Collaborations over Future Enterprise Networks
Sourav Mondal, Elaine Wong
https://arxiv.org/abs/2507.15254

User Head Movement-Predictive XR in Immersive H2M Collaborations over Future Enterprise Networks
The evolution towards future generation of mobile systems and fixed wireless networks is primarily driven by the urgency to support high-bandwidth and low-latency services across various vertical sectors. This endeavor is fueled by smartphones as well as technologies like industrial internet of things, extended reality (XR), and human-to-machine (H2M) collaborations for fostering industrial and social revolutions like Industry 4.0/5.0 and Society 5.0. To ensure an ideal immersive experience and…

Spectral Feature Extraction for Robust Network Intrusion Detection Using MFCCs
HyeYoung Lee, Muhammad Nadeem, Pavel Tsoi
https://arxiv.org/abs/2507.10622 h…

Spectral Feature Extraction for Robust Network Intrusion Detection Using MFCCs
The rapid expansion of Internet of Things (IoT) networks has led to a surge in security vulnerabilities, emphasizing the critical need for robust anomaly detection and classification techniques. In this work, we propose a novel approach for identifying anomalies in IoT network traffic by leveraging the Mel-frequency cepstral coefficients (MFCC) and ResNet-18, a deep learning model known for its effectiveness in feature extraction and image-based tasks. Learnable MFCCs enable adaptive spectral f…

Arbiter PUF: Uniqueness and Reliability Analysis Using Hybrid CMOS-Stanford Memristor Model
Tanvir Rahman, A. B. M. Harun-ur Rashid
https://arxiv.org/abs/2507.04461

Arbiter PUF: Uniqueness and Reliability Analysis Using Hybrid CMOS-Stanford Memristor Model
In an increasingly interconnected world, protecting electronic devices has grown more crucial because of the dangers of data extraction, reverse engineering, and hardware tampering. Producing chips in a third-party manufacturing company can let hackers change the design. As the Internet of Things (IoT) proliferates, physical attacks happen more, and conventional cryptography techniques do not function well. In this paper, we investigate the design and assessment of PUFs using the Stanford Memri…

Self-Sustaining Multi-Sensor LoRa-Based Activity Monitoring for Community Workout Parks
Victor Luder, Michele Magno
https://arxiv.org/abs/2506.03203 https:…

Self-Sustaining Multi-Sensor LoRa-Based Activity Monitoring for Community Workout Parks
With the rise of the Internet of Things (IoT), more sensors are deployed around us, covering a wide range of applications from industry and agriculture to urban environments such as smart cities. Throughout these applications the sensors collect data of various characteristics and support city planners and decision-makers in their work processes, ultimately maximizing the impact of public funds. This paper introduces the design and implementation of a self-sustaining wireless sensor node design…

System Security Framework for 5G Advanced /6G IoT Integrated Terrestrial Network-Non-Terrestrial Network (TN-NTN) with AI-Enabled Cloud Security
Sasa Maric, Rasil Baidar, Robert Abbas, Sam Reisenfeld
https://arxiv.org/abs/2508.05707

System Security Framework for 5G Advanced /6G IoT Integrated Terrestrial Network-Non-Terrestrial Network (TN-NTN) with AI-Enabled Cloud Security
The integration of Terrestrial Networks (TN) and Non-Terrestrial Networks (NTN), including 5G Advanced/6G and the Internet of Things (IoT) technologies, using Low Earth Orbit (LEO) satellites, high-altitude platforms (HAPS), and Unmanned Aerial Vehicles (UAVs), is redefining the landscape of global connectivity. This paper introduces a new system-level security framework for 5G Advanced/6G IoT-integrated TN-NTN architectures with AI-native-enabled cloud security. Due to the heterogeneity, scale…

Hybrid LLM-Enhanced Intrusion Detection for Zero-Day Threats in IoT Networks
Mohammad F. Al-Hammouri, Yazan Otoum, Rasha Atwa, Amiya Nayak
https://arxiv.org/abs/2507.07413

Hybrid LLM-Enhanced Intrusion Detection for Zero-Day Threats in IoT Networks
This paper presents a novel approach to intrusion detection by integrating traditional signature-based methods with the contextual understanding capabilities of the GPT-2 Large Language Model (LLM). As cyber threats become increasingly sophisticated, particularly in distributed, heterogeneous, and resource-constrained environments such as those enabled by the Internet of Things (IoT), the need for dynamic and adaptive Intrusion Detection Systems (IDSs) becomes increasingly urgent. While traditi…