Related papers: Proactive Serverless Function Resource Management
A proper configuration of an information system can ensure accuracy and efficiency, among other system objectives. Conversely, a poor configuration can have a significant negative impact on the system's performance, reliability, and cost.…
Serverless computing, also known as Functions-as-a-Service, is a recent paradigm aimed at simplifying the programming of cloud applications. The idea is that developers design applications in terms of functions, which are then deployed on a…
Serverless computing and stream processing represent two dominant paradigms for event-driven data processing, yet both make assumptions that render them inefficient for short-running, lightweight, and unpredictable streams that require…
We consider a discrete-time system comprising a first-come-first-served queue, a non-preemptive server, and a stationary non-work-conserving scheduler. New tasks enter the queue according to a Bernoulli process with a pre-specified arrival…
In Function-as-a-Service (FaaS) serverless, large applications are split into short-lived stateless functions. Deploying functions is mutually profitable: users need not be concerned with resource management, while providers can keep their…
Large Language Models (LLMs) have revolutionized numerous domains, driving the rise of Language-Model-as-a-Service (LMaaS) platforms that process millions of queries daily. These platforms must minimize latency and meet Service Level…
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 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…
Serverless computing abstracts away server management, enabling automatic scaling and efficient resource utilization. However, cold-start latency remains a significant challenge, affecting end-to-end performance. Our preliminary study…
Serverless cloud is an innovative cloud service model that frees customers from most cloud management duties. It also offers the same advantages as other cloud models but at much lower costs. As a result, the serverless cloud has been…
In the rapidly evolving field of serverless computing, efficient function scheduling and resource scaling are critical for optimizing performance and cost. This paper presents a comprehensive review of the application of Deep Reinforcement…
Adopting serverless computing to edge networks benefits end-users from the pay-as-you-use billing model and flexible scaling of applications. This paradigm extends the boundaries of edge computing and remarkably improves the quality of…
Serverless computing increases developer productivity by removing operational concerns such as managing hardware or software runtimes. Developers, however, still need to partition their application into functions, which can be error-prone…
Serverless computing promises a scalable, reliable, and cost-effective solution for running data-intensive applications and workflows in the heterogeneous and limited-resource environment of the Edge-Cloud Continuum. However, building and…
Making serverless computing widely applicable requires detailed performance understanding. Although contemporary benchmarking approaches exist, they report only coarse results, do not apply distributed tracing, do not consider asynchronous…
Function-as-a-Service (FaaS) platforms provide scalable and cost-efficient execution but suffer from increased latency and resource overheads in complex applications comprising multiple functions, particularly due to double billing when…
Serverless computing is an emerging service model in distributed computing systems. The term captures cloud-based event-driven distributed application design and stems from its completely resource-transparent deployment model, i.e.…
We present a framework for scheduling multifunction serverless applications over a hybrid public-private cloud. A set of serverless jobs is input as a batch, and the objective is to schedule function executions over the hybrid platform to…
Recently, academics and the corporate sector have paid attention to serverless computing, which enables dynamic scalability and an economic model. In serverless computing, users only pay for the time they actually use resources, enabling…
Real-time LLM interactions demand streamed token generations, where text tokens are progressively generated and delivered to users while balancing two objectives: responsiveness (i.e., low time-to-first-token) and steady generation…