Related papers: Making Serverless Computing Extensible: A Case Stu…
Serverless computing has emerged as a new execution model which gained a lot of attention in cloud computing thanks to the latest advances in containerization technologies. Recently, serverless has been adopted at the edge, where it can…
In Function as a Service (FaaS), a serverless computing variant, customers deploy functions instead of complete virtual machines or Linux containers. It is the cloud provider who maintains the runtime environment for these functions. FaaS…
Wireless sensor network (WSN) has been developed for decades and have performed well in the performance, power consumption, and congestion control. However, the following problems have not been addressed, such as inaccurate cost estimation…
Current proprietary and open-source serverless platforms follow opinionated, hardcoded scheduling policies to deploy the functions to be executed over the available workers. Such policies may decrease the performance and the security of the…
Recent Serverless workloads tend to be largescaled/CPU-memory intensive, such as DL, graph applications, that require dynamic memory-to-compute resources provisioning. Meanwhile, recent solutions seek to design page management strategies…
Serverless computing abstracts away server management, enabling automatic scaling, efficient resource utilization, and cost-effective pricing models. However, despite these advantages, it faces the significant challenge of cold-start…
Aggregated HPC resources have rigid allocation systems and programming models which struggle to adapt to diverse and changing workloads. Consequently, HPC systems fail to efficiently use the large pools of unused memory and increase the…
This review paper synthesizes the latest research on performance optimization strategies for serverless applications deployed on AWS Lambda. By examining recent studies, we highlight the challenges, solutions, and best practices for…
Current Serverless abstractions (e.g., FaaS) poorly support non-functional requirements (e.g., QoS and constraints), are provider-dependent, and are incompatible with other cloud abstractions (e.g., databases). As a result, application…
Serverless computing is an emerging cloud computing paradigm for developing applications at the function level, known as serverless functions. Due to the highly dynamic execution environment, multiple identical runs of the same serverless…
Serverless computing promises convenient abstractions for developing and deploying functions that execute in response to events. In such Function-as-a-Service (FaaS) platforms, scheduling is an integral task, but current scheduling…
The increasing demand for computational power in big data and machine learning has driven the development of distributed training methodologies. Among these, peer-to-peer (P2P) networks provide advantages such as enhanced scalability and…
Serverless computing has become a new trending paradigm in cloud computing, allowing developers to focus on the development of core application logic and rapidly construct the prototype via the composition of independent functions. With the…
With the ever-increasing usage of serverless computing in both industry and academia, it is essential to understand the mechanisms that power the underlying platforms. As serverless is more than ten years old, there are different platforms…
The serverless cloud computing model offers a framework where the service provider abstracts the underlying infrastructure management from developers. In this serverless model, FaaS provides an event-driven, function-oriented computing…
Serverless computing allows developers to break their code into small components, known as functions, which are automatically managed by a service provider. Being lightweight and modular, serverless functions have been increasingly employed…
Graph processing systems are essential for analyzing large-scale data with complex relationships, yet most existing frameworks rely on statically provisioned clusters, resulting in poor elasticity and inefficient resource utilization under…
Serverless computing simplifies deployment and scaling, yet cold-start latency remains a major performance bottleneck. Unlike prior work that treats mitigation as a black-box optimization, we study cold starts as a developer-visible design…
Microservice and serverless computing systems open up massive versatility and opportunity to distributed and datacenter-scale computing. In the meantime, the deployments of modern datacenter resources are moving to disaggregated…
Serverless computing platforms currently rely on basic pricing schemes that are static and do not reflect customer feedback. This leads to significant inefficiencies from a total utility perspective. As one of the fastest-growing cloud…