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Congestion‐aware multiaccess edge computing collaboration model for 5G
Author(s) -
Salama Gerges M.,
Ismail Alshimaa H.,
Soliman Tarek Abed,
Hamed Hesham F.A.,
ElBahnasawy Nirmeen A.
Publication year - 2020
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.4446
Subject(s) - cloud computing , computer science , energy consumption , enhanced data rates for gsm evolution , throughput , edge computing , distributed computing , computer network , efficient energy use , green computing , telecommunications , wireless , operating system , ecology , electrical engineering , biology , engineering
Summary In 5G cloud computing, the most notable and considered design issues are the energy efficiency and delay. The majority of the recent studies were dedicated to optimizing the delay issue by leveraging the edge computing concept, while other studies directed its efforts towards realizing a green cloud by minimizing the energy consumption in the cloud. Active queue management‐based green cloud model (AGCM) as one of the recent green cloud models reduced the delay and energy consumption while maintaining a reliable throughput. Multiaccess edge computing (MEC) was established as a model for the edge computing concept and achieved remarkable enhancement to the delay issue. In this paper, we present a handoff scenario between the two cloud models, AGCM and MEC, to acquire the potential gain of such collaboration and investigate its impact on the cloud fundamental constraints; energy consumption, delay, and throughput. We examined our proposed model with simulation showing great enhancement for the delay, energy consumption, and throughput over either model when employed separately.