An Intelligent Caching and Replacement Strategy Based on Cache Profit Model for Space-Ground Integrated Network
Li Yang, Cheng Chi, Chengsheng Pan, Yaowen Qi
Abstract
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Li Yang, Cheng Chi, Chengsheng Pan, Yaowen Qi
Abstract
Open-access reader
Compared with the stable states of the ground networks, the space-ground integrated networks (SGIN) have limited resources, high transmission delay, and vulnerable topology, which make traditional caching strategies unable to adapt to the complex space network environment. An intelligent and efficient caching strategy is required to improve the edge service capabilities of satellites. Therefore, we investigate these problems in this paper and make the following contributions. First, the content value evaluation model based on classification and regression tree is proposed to solve the problem of “what to cache” by describing the cache value of content, which considers the multidimensional content characteristics. Second, we propose a cache decision strategy based on the node caching cost model to answer “where to cache.” This strategy modified the genetic algorithm to adapt the 0-1 knapsack problem under SDN architecture, which greatly improved the cache hit rate and the network service quality. Finally, we propose a cache replacement strategy by establishing an effective service time model between the satellite and ground transmission link, which solves the problem of “when to replace.” Numerical results demonstrate that the proposed strategy in SGIN can improve the nodes’ cache hit rate and reduce the network transmission delay and transmission hops.
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Compared with the stable states of the ground networks, the space-ground integrated networks (SGIN) have limited resources, high transmission delay, and vulnerable topology, which make traditional caching strategies unable to adapt to the complex space network environment. An intelligent and efficient caching strategy is required to improve the edge service capabilities of satellites. Therefore, we investigate these problems in this paper and make the following contributions. First, the content value evaluation model based on classification and regression tree is proposed to solve the problem of “what to cache” by describing the cache value of content, which considers the multidimensional content characteristics. Second, we propose a cache decision strategy based on the node caching cost model to answer “where to cache.” This strategy modified the genetic algorithm to adapt the 0-1 knapsack problem under SDN architecture, which greatly improved the cache hit rate and the network service quality. Finally, we propose a cache replacement strategy by establishing an effective service time model between the satellite and ground transmission link, which solves the problem of “when to replace.” Numerical results demonstrate that the proposed strategy in SGIN can improve the nodes’ cache hit rate and reduce the network transmission delay and transmission hops.
Key concepts: Computer science, Cache, Knapsack problem, Cache algorithms, Smart Cache, Computer network, Cache invalidation, Quality of service