TY - EJOU AU - Liu, Fang AU - Zhang, Zhenyuan AU - Wang, Zunfu AU - Xing, Yuting TI - ECC: Edge Collaborative Caching Strategy for Differentiated Services Load-Balancing T2 - Computers, Materials \& Continua PY - 2021 VL - 69 IS - 2 SN - 1546-2226 AB - Due to the explosion of network data traffic and IoT devices, edge servers are overloaded and slow to respond to the massive volume of online requests. A large number of studies have shown that edge caching can solve this problem effectively. This paper proposes a distributed edge collaborative caching mechanism for Internet online request services scenario. It solves the problem of large average access delay caused by unbalanced load of edge servers, meets users’ differentiated service demands and improves user experience. In particular, the edge cache node selection algorithm is optimized, and a novel edge cache replacement strategy considering the differentiated user requests is proposed. This mechanism can shorten the response time to a large number of user requests. Experimental results show that, compared with the current advanced online edge caching algorithm, the proposed edge collaborative caching strategy in this paper can reduce the average response delay by 9%. It also increases the user utility by 4.5 times in differentiated service scenarios, and significantly reduces the time complexity of the edge caching algorithm. KW - Edge collaborative caching; differentiated service; cache replacement strategy; load balancing DO - 10.32604/cmc.2021.018303