Dynamic Placement Strategy for Edge Servers Under Improved Snake Optimization Algorithm

doi:10.19678/j.issn.1000-3428.0069008

Abstract

Abstract:

In recent years, Mobile Edge Computing (MEC) has attracted significant attention from academia and industry because it provides users with low-latency and high-reliability services. The deployment of edge servers plays a crucial role in implementing MEC applications and has important research value. Selecting appropriate placement locations not only meets the computational requirements but also improves system resource utilization and reduces deployment costs. This paper investigates the edge server placement problem under time-varying network conditions. First, edge servers are divided into two categories: static and dynamic. Subsequently, an Improved Snake Optimization (ISO) algorithm is proposed to determine the number and placement locations of servers at each moment to meet the transmission latency requirements for data offloading within a certain range. Finally, an interior point method is employed to further reduce service costs. Experimental results demonstrate that the proposed approach can dynamically deploy edge servers while achieving a reduction in service costs of approximately 20%-43% compared to classical algorithms under the same experimental conditions.

Key words: Mobile Edge Computing (MEC), server placement, linear programming, Snake Optimization (SO) alogrithm, Internet of Things (IoT)

摘要：

移动边缘计算(MEC)可为用户提供低延迟和高可靠性的服务, 近年来受到了学术界和工业界的广泛关注。边缘服务器部署是MEC应用实施的关键环节, 具有重要的研究价值, 选择合适的放置位置不仅能够满足计算需求, 还可以提高系统的资源利用率, 降低部署成本。因此, 对时变网络状态下的边缘服务器放置问题进行研究。首先, 将边缘服务器划分为静态服务器和动态服务器两类; 然后, 提出一种改进的蛇优化(ISO)算法来确定每个时刻边缘服务器的部署数量和放置位置, 以满足一定范围内用户卸载数据的传输延迟要求; 最后, 利用内点法进一步降低服务成本。实验结果表明, 所提方法能够动态地部署边缘服务器, 同时与经典算法相比, 在相同的实验条件下所提方法能够减少20%~43%的服务成本。

关键词: 移动边缘计算, 服务器放置, 线性规划, 蛇优化算法, 物联网

WU Xiaofeng, YUAN Peiyan. Dynamic Placement Strategy for Edge Servers Under Improved Snake Optimization Algorithm[J]. Computer Engineering, 2025, 51(6): 255-265.

武小丰, 袁培燕. 一种改进蛇优化算法的边缘服务器动态放置策略[J]. 计算机工程, 2025, 51(6): 255-265.

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Figures/Tables 17

Fig.1 Server placement scenario

Fig.2 The procedure of ISO algorithm

Fig.3 Schematic diagram 1 before location update

Fig.4 Schematic diagram 1 after location update

Fig.5 Schematic diagram 2 before location update

Fig.6 Schematic diagram 2 after location update

Fig.7 Schematic diagram of minimum movement distance

Fig.8 The impact of computing power on costs

Fig.9 The impact of computing power on latency

Fig.10 The impact of coverage on costs

Fig.11 The impact of coverage on latency

Fig.12 The impact of task quantity on costs

Fig.13 The impact of task quantity on latency

Fig.14 The impact of different algorithms on latency

Fig.15 The impact of different algorithms on costs

Fig.16 The impact of different algorithms on latency

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