Knowledge Agora



Similar Articles

Title An improved Top-K algorithm for edge servers deployment in smart city
ID_Doc 38245
Authors Qin, ZS; Xu, F; Xie, Y; Zhang, ZY; Li, GJ
Title An improved Top-K algorithm for edge servers deployment in smart city
Year 2021
Published Transactions On Emerging Telecommunications Technologies, 32, 8
Abstract In smart city IoT applications, the deployment of edge servers has problems such as unbalanced servers load and low servers utilization. Therefore, we study the edge servers deployment problem in mobile edge computing environments for smart cities through an improved Top-K algorithm in this paper. This algorithm comprehensively considering the distance between base stations and edge servers, the weight ratio of base stations in the base station cluster, the coverage of edge servers, and the upper limit of computing tasks, which aims to reduce the access delay of tasks and deployment cost of edge servers, balance the load among edge servers, improve quality of user experience (QoE), and quality of service (QoS) of the smart city. Firstly, deploy an edge server at the base station with the most tasks and divide base station clusters according to the minimum distance strategy. Then, the location of edge servers adjusted according to the cumulative sum of the weight ratio of base station tasks and distance product in each base station cluster. Finally, the simulation results show that the deployment strategy in this paper is better than other methods in terms of server utilization, load balancing and cost, and is slightly better than other algorithms in terms of delay.
PDF

Similar Articles

ID Score Article
41971 Wang, SG; Zhao, YL; Xu, JL; Yuan, J; Hsu, CH Edge server placement in mobile edge computing(2019)
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
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
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
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)
37841 Souza, A; Wen, ZY; Cacho, N; Romanovsky, A; James, P; Ranjan, R Using Osmotic Services Composition for Dynamic Load Balancing of Smart City Applications(2018)
36717 Hossain, SKA; Rahman, MA; Hossain, MA Edge computing framework for enabling situation awareness in IoT based smart city(2018)
44655 Qureshi, B; Kawlaq, K; Koubaa, A; Saeed, B; Younis, M A Commodity SBC-Edge Cluster for Smart Cities(2019)
39467 Sahoo, S; Sahoo, KS; Sahoo, B; Gandomi, AH An Auction based Edge Resource Allocation Mechanism for IoT-enabled Smart Cities(2020)
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
Scroll