FellowMe Cache: Fog Computing approach to enhance (QoE) in Internet of Vehicles

Abstract

Among metrics that highly affect video quality and quality of experience (QoE), we can cite the delay and cost transmission caused by mobile network overhead. Moreover, Information centric networking (ICN) is a new architecture that is proposed as a technique that offers very high throughput rates and very low latency, especially in QoE sensitive applications such as multimedia content delivery for the future communication networks. Indeed, unused memory in user equipment can be used to cache contents and afford it to the other nearby users on demand. This caching method is considered as one of the most promising solutions to enhance the QoE of users. On the other hand, one of the major research goals is to improve caching nodes decision based on nodes’ characteristics. In this paper, we propose a new programmable architecture named FollowMeCache based on Software Defined Network (SDN), ICN approaches and Fog Computing for cache node selection using the Connected Dominating Sets (CDS) in order to reduce the download delay and cost for the users’ requested video. In fact, we define cache node selection algorithm based on Influence factor to elect the appropriate nodes from the CDS set to build the cache. This metric takes into consideration the connectivity degree, Zone of Interest (ZI), node capacity, user preference and its location. In order to evaluate the proposed solution, we define a smart event use case. The performance evaluation is conducted by using network simulator and the obtained results show that our approach can give significant gain in terms of network throughput and the transmission delay.