Visible to the public GDGCA: A Gene Driven Cache Scheduling Algorithm in Information-Centric Network

TitleGDGCA: A Gene Driven Cache Scheduling Algorithm in Information-Centric Network
Publication TypeConference Paper
Year of Publication2020
AuthorsLin, X., Zhang, Z., Chen, M., Sun, Y., Li, Y., Liu, M., Wang, Y., Liu, M.
Conference Name2020 IEEE 3rd International Conference on Information Systems and Computer Aided Education (ICISCAE)
KeywordsAccurate Poisson stream, cache capacity, cache storage, Content analysis, content cache replacement, Data models, data popularity, Distributed cache scheduling, future network architecture, GDGCA, gene driven cache scheduling algorithm, gene driven greedy caching algorithm, greedy algorithms, ICN, ICN edge router, ICN environment, ICN scenario, information centered concept, Information Centric Networks, information distribution scheduling algorithm, information entropy, information epilepsy, Information Gene, information gene value, information-centric network, information-centric networking, Internet, optimal simulation model, Poisson data volumes, pubcrawl, QoE index, Resiliency, resource allocation, satisfaction degree, Scalability, scheduling, Scheduling algorithms, self-caching network, simulation, Stochastic processes, telecommunication network routing, telecommunication scheduling, Throughput, user-centered concept
AbstractThe disadvantages and inextensibility of the traditional network require more novel thoughts for the future network architecture, as for ICN (Information-Centric Network), is an information centered and self-caching network, ICN is deeply rooted in the 5G era, of which concept is user-centered and content-centered. Although the ICN enables cache replacement of content, an information distribution scheduling algorithm is still needed to allocate resources properly due to its limited cache capacity. This paper starts with data popularity, information epilepsy and other data related attributes in the ICN environment. Then it analyzes the factors affecting the cache, proposes the concept and calculation method of Gene value. Since the ICN is still in a theoretical state, this paper describes an ICN scenario that is close to the reality and processes a greedy caching algorithm named GDGCA (Gene Driven Greedy Caching Algorithm). The GDGCA tries to design an optimal simulation model, which based on the thoughts of throughput balance and satisfaction degree (SSD), then compares with the regular distributed scheduling algorithm in related research fields, such as the QoE indexes and satisfaction degree under different Poisson data volumes and cycles, the final simulation results prove that GDGCA has better performance in cache scheduling of ICN edge router, especially with the aid of Information Gene value.
Citation Keylin_gdgca_2020