Joint Optimization of Energy Consumption and Packet Scheduling for Mobile Edge Computing in Cyber-Physical Networks | Zendy

Yibo Yang | Zendy; Yongkui Ma | Zendy; Wei Xiang | Zendy; Xuemai Gu | Zendy; Honglin Zhao | Zendy

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Joint Optimization of Energy Consumption and Packet Scheduling for Mobile Edge Computing in Cyber-Physical Networks

Author(s) -

Yibo Yang,

Yongkui Ma,

Wei Xiang,

Xuemai Gu,

Honglin Zhao

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2810115

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

Due to advances in Internet of Things technologies, mobile devices have become an inseparable part of human life. The limited executing capabilities of mobile devices along with constrained energy remain as barriers in front of this expectation. To address these challenges, mobile edge computing (MEC) is considered as a promising computing model to offer computing ability to mobile users in fifth-generation networks. In this paper, we jointly create an optimization problem to minimize the combination of energy cost and packet congestion. By adopting a promoted-by-probability scheme, we efficiently control packet congestion of different priority packets transmitted to MEC. An improved krill herd metaheuristic optimization algorithm is presented to obtain optimal results for minimizing the total overhead of MEC in terms of energy consumption and queuing congestion. The evaluation study demonstrates that our proposal performs efficiently in terms of energy consumption and execution delay.

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