Related papers: Comprehensive Review of Performance Optimization S…
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…
By virtue of its great utility in solving real-world problems, optimization modeling has been widely employed for optimal decision-making across various sectors, but it requires substantial expertise from operations research professionals.…
With the continuous increase of online services as well as energy costs, energy consumption becomes a significant cost factor for the evaluation of data center operations. A significant contributor to that is the performance of database…
This article provides a survey of academic literature about field programmable gate array (FPGA) and their utilization for energy efficiency acceleration in data centers. The goal is to critically present the existing FPGA energy…
We aim to maximize the energy efficiency, gauged as average energy cost per job, in a large-scale server farm with various storage or/and computing components modeled as parallel abstracted servers. Each server operates in multiple power…
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…
Serverless computing is increasingly adopted for its ability to manage complex, event-driven workloads without the need for infrastructure provisioning. However, traditional resource allocation in serverless platforms couples CPU and…
Optimized data transfer services are highly demanded nowadays, due to the large amounts of data which are frequently being produced and accessed. In this paper we consider several data transfer service optimization problems (optimal server…
The serverless scheduling problem poses a new challenge to Cloud service platform providers because it is rather a job scheduling problem than a traditional resource allocation or request load balancing problem. Traditionally, elastic cloud…
In recent years, the rapid expansion of Internet of Things (IoT) nodes and devices has seamlessly integrated technology into everyday life, amplifying the demand for optimized computing solutions. To meet the critical Quality of Service…
Serverless computing is an emerging cloud computing paradigm that enables developers to build applications at the function level, known as serverless applications. Amazon Web Services (AWS), the leading provider in this domain, provides the…
Edge computing is an emerging paradigm to enable low-latency applications, like mobile augmented reality, because it takes the computation on processing devices that are closer to the users. On the other hand, the need for highly scalable…
Serverless computing has gained popularity in edge computing due to its flexible features, including the pay-per-use pricing model, auto-scaling capabilities, and multi-tenancy support. Complex Serverless-based applications typically rely…
Serverless computing is an approach to cloud computing that allows programmers to run serverless functions in response to external events. Serverless functions are priced at sub-second granularity, support transparent elasticity, and…
Data is both the key enabler and a major bottleneck for machine learning in autonomous driving. Effective model training requires not only large quantities of sensor data but also balanced coverage that includes rare yet safety-critical…
An increasing number of Analytics-as-a-Service solutions has recently seen the light, in the landscape of cloud-based services. These services allow flexible composition of compute and storage components, that create powerful data ingestion…
Accurate prediction of application performance is critical for enabling effective scheduling and resource management in resource-constrained dynamic edge environments. However, achieving predictable performance in such environments remains…
Increasing popularity of the serverless computing approach has led to the emergence of new cloud infrastructures working in Container-as-a-Service (CaaS) model like AWS Fargate, Google Cloud Run, or Azure Container Instances. They introduce…
The Function-as-a-Service (FaaS) execution model increases developer productivity by removing operational concerns such as managing hardware or software runtimes. Developers, however, still need to partition their applications into FaaS…
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…