Tag: edge

Master’s Thesis Explores User Behavior’s Impact on Digital Service Energy Consumption

Posted on by bennyakesson

Just before the end of summer, Nsidibe Onoyom Bassey, master student at the Vrije Universiteit Amsterdam, has successfully defended her thesis “Impact of Users’ Behavior on Digital Service Energy Consumption“. Congratulations on the defense and completing your studies Nsidibe!

This work was supervised by Ana Lucia Varbanescu and myself in the context of our research project Energy Labels for Digital Services, which studies the energy consumption of applications distributed over the compute continuum. In particular, the research addresses the growing concerns over energy consumption in the ICT sector, which poses challenges to achieving net-zero emissions. While ICT solutions are often seen as efficient and low-cost, their energy impact is significant, particularly due to the high demand for digital services, such as online shopping. Energy consumption in the digital domain is largely driven by hardware, software, and infrastructure, but the role of user behavior in influencing this consumption is often overlooked. The thesis focuses on understanding how user behavior affects energy consumption in digital services, using a commonly used open-source online shop implemented as microservices as a case study. The energy consumption on both the client and server side is studied and experiments are conducted with different client browsers, user interactions, and number of users. Based on the experiments, an analytical model is proposed to estimate the energy impact of user behavior on the server side and recommendations are made to both users and developers for how to limit energy consumption.

Paper on Multi-Application Energy Analysis in Edge Computing Accepted at FMEC 2024

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Good news everyone! Our paper “Analysing Per-Application Energy Consumption in a Multi-Application Computing Continuum” was accepted at the 9th International Conference on Fog and Mobile Edge Computing (FMEC 2024). This paper was first-authored by Saeedeh Baneshi, a PhD student at the University of Amsterdam, and complements her earlier work “Estimating the Energy Consumption of Applications in the Computing Continuum with iFogSim“. Congratulations on another accepted paper Saeedeh!

The paper addresses the challenge of analyzing the energy consumption of applications distributed over edge devices and data centers in the compute continuum. The goal is to enable stakeholders, such as cloud providers, developers, users, and researchers, to improve energy efficiency, optimize resource usage, and reduce the environmental impact of such applications. To this end, the work proposes a fine-grained simulation approach for analyzing application energy behavior in edge/cloud environments, based on the iFogSim framework. The three main contributions of the work are: 1) An extension is proposed to iFogSim’s energy model to also consider the energy consumption of communication, 2) iFogSim’s reporting is improved to collect finer-grained data, an essential improvement for analysis of multi-application scenarios, and 3) The effectiveness of the approach is demonstrated by evaluating different multi-application scenarios and configurations for a distributed video surveillance application.

Advancing Sustainability: Paper Accepted on Estimating Energy Consumption of Applications in the Computing Continuum

Posted on by bennyakesson

I am happy to please that the paper “Estimating the Energy Consumption of Applications in the Computing Continuum with iFogSim” was accepted at the International Workshop on Converged Computing (WOCC). The paper is first-authored by Saaedeh Baneshi and is the first publication to come out of the project Energy Labels for Digital Services. Congratulations Saaedeh!

The paper explains how digital services – applications that often span the entire computing continuum – have become an essential part of our daily lives, but they can have a significant energy cost, raising sustainability concerns. Measuring the energy consumption of such applications is challenging due to the distributed nature of the system and the application. As such, simulation techniques are promising solutions to estimate energy consumption, and several simulators are available for modeling the cloud and fog computing environment. The paper investigates iFogSim’s effectiveness in analyzing the end-to-end energy consumption of applications in the computing continuum through two case studies. We design different scenarios for each case study to map application modules to devices along the continuum, including the Edge-Cloud collaboration architecture, and compare them with the two placement policies native to iFogSim: Cloud-only and Edge-ward policies. We observe iFogSim’s limitations in reporting energy consumption, and improve its ability to report energy consumption from an application’s perspective; this enables additional insight into an application’s energy consumption, thus enhancing the usability of iFogSim in evaluating the end-to-end energy consumption of digital services.

Vacancy for a PhD in Energy Labels for Digital Services

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Back in July, I announced that our project proposal “Zero-Waste Computing: Energy Labels for Digital Services” was granted for the Science and Design PhD program at the University of Amsterdam. Now, the Parallel Computing Systems (PCS) group  is looking for a suitable PhD candidate for this project. Among other things, this involves modelling and monitoring to determine how energy is consumed in digital services whose computations are distributed over device, edge, and cloud.

Find a more detailed description of the vacancy, as well as instructions for how to apply here. The application period ends on October 18.

Project Proposal about Energy Labels for Digital Services Granted

Posted on by bennyakesson

It is my pleasure to announce our project proposal entitled “Zero-Waste Computing: Energy Labels for Digital Services” has been granted for the Science and Design PhD program at the University of Amsterdam. Ana Lucia Varbanescu is the main applicant for this project, with Anuj Pathania and myself as co-applicants. The project proposal was supported by Surf, ESI (TNO), Barcelona Supercomputing Center, and ASTRON.

The project addresses the issue that digital services are getting increasingly prevalent in society and are vital to the Dutch economy, already reaching 60% of GDP. However, they come with a significant, rapidly-increasing energy cost, raising sustainability concerns, since a mid-size datacenter alone consumes as much energy as a small town. However, datacenters are only the final link in a digital chain. Users interacting with devices — mobile phones, tablets, or laptops — trigger entire digital chains, combining multiple communicating computing layers and data transfers: from the device itself, through the edge, to the datacenter. Each layer has its own computing infrastructure (see figure). At each layer, decisions are made about how, where and when applications are running and/or data are transferred. These decisions have a significant impact on the user-perceived quality-of-service (QoS), but also on the energy consumption – per layer, and for the entire digital chain. The energy footprint of different devices along the chain might be known, but the actual energy consumed by the application is unknown, because it depends on infrastructure choices, and on user QoS requirements, and on mapping decisions made on the edge and in the datacenter. Thus, the energy efficiency, i.e., the amount of energy consumed to perform the actual task at hand, is largely unknown, for most digital chains.

We argue that the first step to reduce waste in computing is to quantify the energy efficiency of end-to-end digital chains. Our project focuses on designing an integrated framework (i.e., the methods, metrics, and tools) for this quantification effort. Specifically, we aim to define a reference architecture of digital chains, use it to define an analytical digital-chain energy-efficiency model that exposes the factors that impact energy efficiency along the chain, and support it with a high-level functional simulator to assess different operational scenarios and parameters that affect the energy efficiency of digital chains.

This is a small project funding only a single PhD student. More momentum is required to further advance this area and make a step from only monitoring the energy consumption of digital chains to also include actuation, e.g. energy minimization through workload redistribution, subject to performance constraints. We are currently looking for interested parties to collaborate with us on this topic in future project proposals.