| Title | Edge server placement in mobile edge computing |
|---|---|
| ID_Doc | 41971 |
| Authors | Wang, SG; Zhao, YL; Xu, JL; Yuan, J; Hsu, CH |
| Title | Edge server placement in mobile edge computing |
| Year | 2019 |
| Published | |
| Abstract | With the rapid increase in the development of the Internet of Things and 5G networks in the smart city context, a large amount of data (i.e., big data) is expected to be generated, resulting in increased latency for the traditional cloud computing paradigm. To reduce the latency, mobile edge computing has been considered for offloading a part of the workload from mobile devices to nearby edge servers that have sufficient computation resources. Although there has been significant research in the field of mobile edge computing, little attention has been given to understanding the placement of edge servers in smart cities to optimize the mobile edge computing network performance. In this paper, we study the edge server placement problem in mobile edge computing environments for smart cities. First, we formulate the problem as a multi-objective constraint optimization problem that places edge servers in some strategic locations with the objective to make balance the workloads of edge servers and minimize the access delay between the mobile user and edge server. Then, we adopt mixed integer programming to find the optimal solution. Experimental results based on Shanghai Telecom's base station dataset show that our approach outperforms several representative approaches in terms of access delay and workload balancing. (C) 2018 Elsevier Inc. All rights reserved. |
Similar Articles
| ID | Score | Article |
|---|---|---|
41902
|
Zhao, XB; Zeng, Y; Ding, HW; Li, B; Yang, ZJ Optimize the placement of edge server between workload balancing and system delay in smart city(2021)Peer-To-Peer Networking And Applications, 14, 6 | |
| 38245
|
Qin, ZS; Xu, F; Xie, Y; Zhang, ZY; Li, GJ An improved Top-K algorithm for edge servers deployment in smart city(2021)Transactions On Emerging Telecommunications Technologies, 32, 8 | |
| 40402
|
Liu, ZR A Multi-joint Optimisation Method for Distributed Edge Computing Resources in IoT-Based Smart Cities(2023)Journal Of Grid Computing, 21, 4 | |
| 45381
|
Peng, K; Liu, PC; Tao, P; Huang, QJ Security-Aware computation offloading for Mobile edge computing-Enabled smart city(2021)Journal Of Cloud Computing-Advances Systems And Applications, 10, 1 | |
| 40221
|
Mahmood, OA; Abdellah, AR; Muthanna, A; Koucheryavy, A Distributed Edge Computing for Resource Allocation in Smart Cities Based on the IoT(2022)Information, 13, 7 | |
| 44598
|
Kuang, L; Gong, T; OuYang, SY; Gao, HH; Deng, SG Offloading decision methods for multiple users with structured tasks in edge computing for smart cities(2020) | |
| 39467
|
Sahoo, S; Sahoo, KS; Sahoo, B; Gandomi, AH An Auction based Edge Resource Allocation Mechanism for IoT-enabled Smart Cities(2020) | |
| 39889
|
Salih, HS; Jaber, MM; Ali, MH; Abd, SK; Alkhayyat, A; Malik, RQ Application of edge computing-based information-centric networking in smart cities(2023) | |
| 40568
|
Lv, ZH; Chen, DL; Lou, RR; Wang, QJ Intelligent edge computing based on machine learning for smart city(2021) | |
| 43402
|
Madamori, O; Max-Onakpoya, E; Erhardt, GD; Baker, CE Enabling Opportunistic Low-cost Smart Cities By Using Tactical Edge Node Placement(2021) |