arXiv subjects

Chiara Caiazza

Publications and source records attributed to Chiara Caiazza.

4 recordsLinked to original sources

arXiv2025

Measuring the Energy of Smartphone Communications in the Edge-Cloud Continuum: Approaches, Challenges, and a Case Study

As computational resources are placed at different points in the edge-cloud continuum, not only the responsiveness on the client side is affected, but also the energy spent during communications. We summarize the main approaches used to estimate the energy consumption of smartphones and the main difficulties that are typically encountered. A case study then shows how such approaches can be put into practice. Results show that the edge is favorable in terms of energy consumption, compared to more remote locations.

cs.NI↗

arXiv2025

Energy consumption of smartphones and IoT devices when using different versions of the HTTP protocol

HTTP is frequently used by smartphones and IoT devices to access information and Web services. Nowadays, HTTP is used in three major versions, each introducing significant changes with respect to the previous one. We evaluated the energy consumption of the major versions of the HTTP protocol when used in the communication between energy-constrained devices and cloud-based or edge-based services. Experimental results show that in a machine-to-machine communication scenario, for the considered client devices - a smartphone and a Single Board Computer - and for a number of cloud/edge services and facilities, HTTP/3 frequently requires more energy than the previous versions of the protocol. The focus of our analysis is on machine-to-machine communication, but to obtain a broader view we also considered a client-server interaction pattern that is more browsing-like. In this case, HTTP/3 can be more energy efficient than the other versions.

cs.NI↗

arXiv2023

Measurement-Driven Design and Runtime Optimization in Edge Computing: Methodology and Tools

Edge computing is projected to become the dominant form of cloud computing in the future because of the significant advantages it brings to both users (less latency, higher throughput) and telecom operators (less Internet traffic, more local management). However, to fully unlock its potential at scale, system designers and automated optimization systems alike will have to monitor closely the dynamics of both processing and communication facilities. Especially the latter is often neglected in current systems since network performance in cloud computing plays only a minor role. In this paper, we propose the architecture of MECPerf, which is a solution to collect network measurements in a live edge computing domain, to be collected for offline provisioning analysis and simulations, or to be provided in real-time for on-line system optimization. MECPerf has been validated in a realistic testbed funded by the European Commission (Fed4Fire+), and we describe here a summary of the results, which are fully available as open data and through a Python library to expedite their utilization. This is demonstrated via a use case involving the optimization of a system parameter for migrating clients in a federated edge computing system adopting the GSMA platform operator concept.

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arXiv2021

Edge Computing vs Centralized Cloud: Impact of Communication Latency on the Energy Consumption of LTE Terminal Nodes

Edge computing brings several advantages, such as reduced latency, increased bandwidth, and improved locality of traffic. One aspect that is not sufficiently understood is to what extent the different communication latency experienced in the edge-cloud continuum impacts on the energy consumption of clients. We studied the energy consumption of a request-response communication scheme when an LTE node communicates with edge-based or cloud-based servers. Results show that the reduced latency of edge servers bring significant benefits in terms of energy consumption. Experiments also show how the energy savings brought by edge computing are influenced by the prevalent direction of data transfer (upload vs download), load of the server, and daytime/nighttime operation.

cs.NI↗