Tootfinder

Raptor: Distributed Scheduling for Serverless Functions
Kevin Exton, Maria Read
https://arxiv.org/abs/2403.16457 https://arxiv.org/pd…

Raptor: Distributed Scheduling for Serverless Functions
Serverless platforms that poorly schedule function requests inspire developers to implement workarounds to issues like high cold start latencies, poor fault tolerance, and limited support for parallel processing. These solutions litter environments with idle containers and add unnecessary pressure to the already underperforming scheduling services. An effective serverless scheduling policy should encourage developers to write small and reusable snippets of code, and give operators the freedom t…

Araucaria: Simplifying INC Fault Tolerance with High-Level Intents
Ricardo Parizotto, Israat Haque, Alberto Schaeffer-Filho
https://arxiv.org/abs/2404.11728

Araucaria: Simplifying INC Fault Tolerance with High-Level Intents
Network programmability allows modification of fine-grain data plane functionality. The performance benefits of data plane programmability have motivated many researchers to offload computation that previously operated only on servers to the network, creating the notion of in-network computing (INC). Because failures can occur in the data plane, fault tolerance mechanisms are essential for INC. However, INC operators and developers must manually set fault tolerance requirements using domain kno…

Raptor: Distributed Scheduling for Serverless Functions
Kevin Exton, Maria Read
https://arxiv.org/abs/2403.16457 https://arxiv.org/pd…

Raptor: Distributed Scheduling for Serverless Functions
Serverless platforms that poorly schedule function requests inspire developers to implement workarounds to issues like high cold start latencies, poor fault tolerance, and limited support for parallel processing. These solutions litter environments with idle containers and add unnecessary pressure to the already underperforming scheduling services. An effective serverless scheduling policy should encourage developers to write small and reusable snippets of code, and give operators the freedom t…

Self-healing Nodes with Adaptive Data-Sharding
Ayush Thakur, Sanskar Chauhan, Ilisha Tomar, Vaibhavi Paul, Deepak Gupta
https://arxiv.org/abs/2405.00004 ht…

Self-healing Nodes with Adaptive Data-Sharding
Data sharding, a technique for partitioning and distributing data among multiple servers or nodes, offers enhancements in the scalability, performance, and fault tolerance of extensive distributed systems. Nonetheless, this strategy introduces novel challenges, including load balancing among shards, management of node failures and data loss, and adaptation to evolving data and workload patterns. This paper proposes an innovative approach to tackle these challenges by empowering self-healing nod…