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Collaborative Data Caching and Computation Offloading for Multi-Service Mobile Edge Computing

delete2021-09-01
delete73
PRE
AI
H
Hao Feng
S
Songtao Guo *
L
Li Yang
杨园园 cover
杨园园 (Yuanyuan Yang)
DOI:10.1109/TVT.2021.3099303delete
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Abstract

Abstract

En 中文
Mobile edge computing (MEC) can use wireless access network (RAN) to provide the services required by user's information technology (IT) and cloud computing functions nearby, which can create a high-performance and low latency service environment. Performing task offloading and data caching at access points (APs) in a cooperative manner can reduce the heavy backhaul load and the retransmission of content downloading. However, in edge networks (ENs), how to maximize storage utilization while reducing service latency and energy consumption is still a key issue, because the heterogeneity of ENs and the uneven distribution of users make it difficult to determine which MEC server and what data should be cached. In this paper, we study a two-tier MEC system, which enables data caching and computing offloading policy to minimize the network cost at the user equipment (UE) side, while satisfying the constraints of task offloading deadline, the cache capacity at APs and the computing capability of MEC servers. The optimization problem is formulated as a mixed integer nonlinear program (MINLP) problem. In order to solve the problem, we transform it into an equivalent task offloading convex optimization problem by fixing an optimization variable. Furthermore, we solve a cache placement problem by dynamic programming (DP) algorithm. Then we propose a distributed collaborative data caching and computing offloading (CDCCO) iterative algorithm. Simulation results demonstrate that our proposed CDCCO algorithm can significantly reduce the network cost and achieve better performance than other existing schemes.
Keywords:
Task analysis
Servers
Delays
Cloud computing
Heuristic algorithms
Edge computing
Collaboration
Collaborative Data Caching
Multi-user Computation Offloading
Convex Optimization
Mobile Edge Computing

Journal

IEEE Transactions on Vehicular Technology cover
IEEE Transactions on Vehicular Technology
IF:
7.1
Papers:
1.8W
Citations:
6.6W

Organization

S
southwest university - china
Scholars:
2.6W
Papers: 1.9W
Citations: 21
C
Chongqing University
Scholars:
5.1W
Papers: 4.1W
Citations: 6.0W
S
state university of new york (suny) system
Scholars:
6.5W
Papers: 5.8W
Citations: 65
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Cited Papers

Cited Papers

Energy-Efficient Resource Allocation for Mobile-Edge Computation Offloading
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Mobile Edge Computing: A Survey
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errAbbas, Nasir; Zhang, Yan; Taherkordi, Amir; Skeie, Tor
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Superradiance in Black Hole Physics
err2015-01-01
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errRichard Brito; Vitor Cardoso; Paolo Pani
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Collaborative Mobile Edge Computing in 5G Networks: New Paradigms, Scenarios, and Challenges
err2017-04-01
err504
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errTran, Tuyen X.; Hajisami, Abolfazl; Pandey, Parul; Pompili, Dario
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LeaD: Large-Scale Edge Cache Deployment Based on Spatio-Temporal WiFi Traffic Statistics
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errLyu, Feng; Ren, Ju; Cheng, Nan; Yang, Peng; Li, Minglu; Zhang, Yaoxue; Shen, Xuemin Sherman
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INTELLIGENT TASK OFFLOADING IN VEHICULAR EDGE COMPUTING NETWORKS
err2020-08-01
err107
PREAI
errGuo, Hongzhi; Liu, Jiajia; Ren, Ju; Zhang, Yanning
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researcher View more