Related papers: How Does Microservice Granularity Impact Energy Co…
Microservice architectures are revolutionizing both small businesses and large corporations, igniting a new era of innovation with their exceptional advantages in maintainability, reusability, and scalability. However, these benefits come…
In Federated edge learning (FEEL), energy-constrained devices at the network edge consume significant energy when training and uploading their local machine learning models, leading to a decrease in their lifetime. This work proposes novel…
This study presents an integrated energy management strategy for cost optimization in multi-energy community microgrids (MGs). The proposed approach combines storage-based peak shaving, economic dispatch of diesel generators, and efficient…
Energy efficiency has a significant influence on user experience of battery-driven devices such as smartphones and tablets. The goal of an energy model for source code is to lay a foundation for the application of energy-saving techniques…
As energy proportional computing gradually extends the success of DVFS (Dynamic voltage and frequency scaling) to the entire system, DVFS control algorithms will play a key role in reducing server clusters' power consumption. The focus of…
The microservice software architecture is more scalable and efficient than its monolithic predecessor. Despite its increasing adoption, microservices might expose security concerns and issues that are distinct from those associated with…
Serverless computing is transforming cloud application development, but the performance-cost trade-offs of control plane designs remain poorly understood due to a lack of open, cross-platform benchmarks and detailed system analyses. In this…
Power consumption plays a crucial role in on-device streaming speech recognition, significantly influencing the user experience. This study explores how the configuration of weight parameters in speech recognition models affects their…
Energy efficiency of fixed-rate transmissions is studied in the presence of queueing constraints and channel uncertainty. It is assumed that neither the transmitter nor the receiver has channel side information prior to transmission. The…
The rapid adoption of large language models (LLMs) has raised concerns about their substantial energy consumption, especially when deployed at industry scale. While several techniques have been proposed to address this, limited empirical…
To improve the environmental implications of the growing demand of computing, future applications need to improve the carbon-efficiency of computing infrastructures. State-of-the-art approaches, however, do not consider the intermittent…
In this paper we introduce a method for performance quantification of flexibility aggregation in flexibility coordination schemes (FCS), with a focus on privacy preserving hierarchical FCS. The quantification is based on two performance…
Machine learning (ML) has seen tremendous advancements, but its environmental footprint remains a concern. Acknowledging the growing environmental impact of ML this paper investigates Green ML, examining various model architectures and…
We consider allocation problems that arise in the context of service allocation in Clouds. More specifically, we assume on the one part that each computing resource is associated to a capacity constraint, that can be chosen using Dynamic…
The Cloud Computing paradigm consists in providing customers with virtual services of the quality which meets customers' requirements. A cloud service operator is interested in using his infrastructure in the most efficient way while…
The ever increasing adoption of mobile devices with limited energy storage capacity, on the one hand, and more awareness of the environmental impact of massive data centres and server pools, on the other hand, have both led to an increased…
The main memory access latency has not much improved for more than two decades while the CPU performance had been exponentially increasing until recently. Approximate memory is a technique to reduce the DRAM access latency in return of…
Measuring energy consumption is a challenging task faced by developers when building mobile apps. This paper presents EMaaS: a system that provides reliable energy measurements for mobile applications, without requiring a complex setup. It…
Microservice architecture has transformed traditional monolithic applications into lightweight components. Scaling these lightweight microservices is more efficient than scaling servers. However, scaling microservices still faces the…
Cloud applications are increasingly shifting from large monolithic services, to complex graphs of loosely-coupled microservices. Despite their advantages, microservices also introduce cascading QoS violations in cloud applications, which…