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A New Heuristic Computation Offloading Method Based on Cache-Assisted Model
Author(s) -
Junhua Wu,
Cang Fan,
Guangshun Li,
Zhuqing Xu,
Zhenyu Jin,
Yuanwang Zheng
Publication year - 2022
Publication title -
wireless communications and mobile computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.42
H-Index - 64
eISSN - 1530-8677
pISSN - 1530-8669
DOI - 10.1155/2022/3501329
Subject(s) - computer science , cache , server , computation offloading , mobile edge computing , cache algorithms , cache invalidation , smart cache , heuristic , distributed computing , edge computing , cloud computing , computer network , cpu cache , operating system , artificial intelligence
Mobile edge computing (MEC) solves the high latency problem of cloud computing by offloading tasks to edge servers. Due to limited resources, it is necessary to improve the efficiency of computation offloading. However, there is a lot of redundant data transmission between MEC servers and users in the existing methods. Additional data transmission increases the task processing delay. To reduce the total delay, a new cache-assisted computation offloading strategy is proposed. In response to a large number of similar requests from users, a new cache management mechanism is designed. This mechanism can select reusable calculation results more accurately in the cache space through an approximate matching method and improve the cache hit ratio. Then, aiming at the problem of offloading efficiency, the delay optimization problem is transformed into an optimal path problem, a cost function is defined to determine the optimal offloading position, and an improved path planning method is used to plan the optimal offloading path. The simulation results indicate that the proposed scheme can improve the cache hit ratio and reduce the total processing delay of tasks compared with other standard schemes.

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