Decentralized Mechanism for Edge Node Allocation in Access Network: An Experimental Evaluation

Jesus Calle-Cancho, Carlos Cañada, Rafael Pastor-Vargas, Mercedes E. Paoletti and Juan M. Haut ()
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Jesus Calle-Cancho: Department of Computing and Telematics Engineering, University of Extremadura, 10001 Cáceres, Spain
Carlos Cañada: Department of Technology of Computers and Communications, University of Extremadura, 10001 Cáceres, Spain
Rafael Pastor-Vargas: Deparment of Communication and Control Systems, School of Computer Science Engineering, National Distance Education University (UNED), 28040 Madrid, Spain
Mercedes E. Paoletti: Department of Technology of Computers and Communications, University of Extremadura, 10001 Cáceres, Spain
Juan M. Haut: Department of Technology of Computers and Communications, University of Extremadura, 10001 Cáceres, Spain

Future Internet, 2024, vol. 16, issue 9, 1-13

Abstract: With the rapid advancement of the Internet of Things and the emergence of 6G networks in smart city environments, a growth in the generation of data, commonly known as big data, is expected to consequently lead to higher latency. To mitigate this latency, mobile edge computing has been proposed to alleviate a portion of the workload from mobile devices by offloading it to nearby edge servers equipped with appropriate computational resources. However, existing solutions often exhibit poor performance when confronted with complex network topologies. Thus, this paper introduces a decentralized mechanism aimed at determining the locations of network edge nodes in such complex network topologies, characterized by lengthy execution times. Our proposal provides performance improvements and offers scalability and flexibility as networks become more complex. Experimental evaluations are conducted using the Shanghai Telecom dataset to validate our proposed approach.

Keywords: next-generation networks; mobile edge computing; decentralized mechanism (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2024
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