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A task offloading optimization strategy in MEC ‐based smart cities
Author(s) -
Li Shuangyuan
Publication year - 2020
Publication title -
internet technology letters
Language(s) - English
Resource type - Journals
ISSN - 2476-1508
DOI - 10.1002/itl2.158
Subject(s) - mobile edge computing , computer science , server , heuristic , task (project management) , enhanced data rates for gsm evolution , energy consumption , optimization problem , smart city , distributed computing , efficient energy use , mobile device , computer network , embedded system , internet of things , engineering , telecommunications , artificial intelligence , algorithm , electrical engineering , systems engineering , operating system
The Mobile Edge Computing (MEC) technology can greatly facilitate the development of smart cities, as a result, MEC‐based smart cities have attracted much attention from some global research communities. In such filed, there is always a non‐negligible challenge, that is, efficient task offloading from mobile devices to edge servers. To this end, this letter proposes a task offloading optimization strategy to make a tradeoff between energy consumption and response time, including the modeling of two sub‐objectives and a heuristic bi‐objective optimization algorithm. The proposed strategy is simulated and the experimental results demonstrate that it is more efficient compared to the the‐state‐of‐the‐art strategy.

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