The Internet is experiencing a fast expansion at its edges. The wide availability of heterogeneous resources at the Edge is pivotal in the definition and extension of traditional Cloud solutions toward supporting the development of new applications. However, the dynamic and distributed nature of these resources poses new challenges for the optimization of the behaviour of the system. New decentralized and self-organizing methods are needed to face the needs of the Edge/Cloud scenario and to optimize the exploitation of Edge resources. In this paper we propose a distributed and adaptive solution that reduces the number of replicas of application services that are executed throughout the system, all the while ensuring that the latency constraints of applications are met, thus allowing to also meet the end users' QoS requirements. Experimental evaluations through simulation show the effectiveness of the proposed approach.

Latency preserving self-optimizing placement at the edge

Ferrucci L;Mordacchini M;Coppola M;Carlini E;Kavalionak H;Dazzi P
2021

Abstract

The Internet is experiencing a fast expansion at its edges. The wide availability of heterogeneous resources at the Edge is pivotal in the definition and extension of traditional Cloud solutions toward supporting the development of new applications. However, the dynamic and distributed nature of these resources poses new challenges for the optimization of the behaviour of the system. New decentralized and self-organizing methods are needed to face the needs of the Edge/Cloud scenario and to optimize the exploitation of Edge resources. In this paper we propose a distributed and adaptive solution that reduces the number of replicas of application services that are executed throughout the system, all the while ensuring that the latency constraints of applications are met, thus allowing to also meet the end users' QoS requirements. Experimental evaluations through simulation show the effectiveness of the proposed approach.
2021
Istituto di informatica e telematica - IIT
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
978-1-4503-8384-4
Self-optimizing application placement
Application model
Optimization Techniques for Resource Management
Edge computing
Cloud computing
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/399968
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