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<p>The rapid growth of mobile Internet services has placed traditional cloud computing centres under increasing pressure, including high bandwidth consumption, excessive core network backhaul traffic, and long service response delays. Mobile edge caching can move popular content closer to user terminals. However, in practical mobile edge networks, caching decisions are affected by edge node capacity, link bandwidth, content popularity variation, and conflicts among multiple stakeholders. Therefore, single-objective optimisation methods are unable to simultaneously balance user experience, network resource cost, and content distribution revenue.To address these problems, this paper constructs a multi-objective cache optimisation model for users, content providers, and network service providers. The model integrates Device-to-Device (D2D) communication and coded caching mechanisms to improve terminal collaborative service capability and cache resource reuse efficiency. Considering that cache optimisation involves conflicting objectives, complex constraints, and a large-scale solution space, this paper adopts a classical multi-objective evolutionary algorithm as the solution basis. A farthest-pairing strategy is used to enhance population diversity, while a hierarchical elimination strategy is introduced to improve inferior-solution screening ability and solution distribution uniformity, thereby obtaining more balanced caching decision schemes.In high-concurrency scenarios, the cache hit rate of the small base station (SBS) reaches 66.92%. In the dispersed popularity scenario, the response latency is only 24.36 ms, and the core network backhaul ratio of the macro base station is reduced to 11.35%. The D2D communication utilisation rate of terminals reaches 68.37%, the SBS cache resource utilisation rate reaches 72.65%, and the total network energy consumption is 0.89&#xa0;kW&#xa0;h. In summary, the proposed cache optimisation method can coordinate the interests of users, content providers, and network service providers under multi-objective constraints, thereby improving the scheduling efficiency and service adaptability of cache resources in mobile edge networks.</p>

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Cache optimization system based on multi-objective evolutionary algorithm for mobile edge networks

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月14日

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  • Guozheng Sui

摘要

The rapid growth of mobile Internet services has placed traditional cloud computing centres under increasing pressure, including high bandwidth consumption, excessive core network backhaul traffic, and long service response delays. Mobile edge caching can move popular content closer to user terminals. However, in practical mobile edge networks, caching decisions are affected by edge node capacity, link bandwidth, content popularity variation, and conflicts among multiple stakeholders. Therefore, single-objective optimisation methods are unable to simultaneously balance user experience, network resource cost, and content distribution revenue.To address these problems, this paper constructs a multi-objective cache optimisation model for users, content providers, and network service providers. The model integrates Device-to-Device (D2D) communication and coded caching mechanisms to improve terminal collaborative service capability and cache resource reuse efficiency. Considering that cache optimisation involves conflicting objectives, complex constraints, and a large-scale solution space, this paper adopts a classical multi-objective evolutionary algorithm as the solution basis. A farthest-pairing strategy is used to enhance population diversity, while a hierarchical elimination strategy is introduced to improve inferior-solution screening ability and solution distribution uniformity, thereby obtaining more balanced caching decision schemes.In high-concurrency scenarios, the cache hit rate of the small base station (SBS) reaches 66.92%. In the dispersed popularity scenario, the response latency is only 24.36 ms, and the core network backhaul ratio of the macro base station is reduced to 11.35%. The D2D communication utilisation rate of terminals reaches 68.37%, the SBS cache resource utilisation rate reaches 72.65%, and the total network energy consumption is 0.89 kW h. In summary, the proposed cache optimisation method can coordinate the interests of users, content providers, and network service providers under multi-objective constraints, thereby improving the scheduling efficiency and service adaptability of cache resources in mobile edge networks.