Towards an improved heuristic genetic algorithm for static content delivery in cloud storage. (July 2018)

• Record Type: Journal Article
• Authors: Zheng, Zhigao; Zheng, Zunxin
• Is Part Of: Computers & electrical engineering. Volume 69(2018)
• Page Start: 422
• Page End: 434
• Publication Date: 2018-07
• Subjects: Cloud storage -- Static content delivery -- Resource management model -- Cost model -- Genetic algorithm; 00-01 -- 99-00; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2017.06.011
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: A key challenge in computer networking is how to organize network topology effectively among a large number of servers in the cloud storage system. In a cloud environment, the topology, which is different from the underlying topology, may be established in any form at any potential edge peers. The cloud content delivery network (CDN) always faces problems of complex distributed path creation, cache update, load balancing, etc. To address the problem as a static content delivery, we propose an Improved Heuristic Genetic Algorithm for Static Content Delivery in Cloud Storage (IHGA-SCDCS) based on a resource management model and cost model. The static content delivery in cloud storage is abstracted into mathematical model for set solving problem, which is then solved by an improved Genetic Algorithm (GA). Finally, the optimal solution is reduced to an optimal content delivery program. The simulation experiment, based on CloudSim, shows that IHGA-SCDCS can effectively obtain optimal solution while reducing delivery cost.