LOCASS: Local Optimal Caching Algorithm With Social Selfishness for Mixed Cooperative and Selfish Devices

Abstract

Device caching has emerged as a promising solution to alleviate backhaul overload in future wireless networks with mixed cooperative and selfish devices. The behaviors of these devices actually represent the inherent social-network characteristics of their users, i.e., people treat each other differently according to the closeness of their social relationships. In this paper, the concept of social selfishness is adopted to capture the social characteristics in mobile device caching. Devices can be cooperative or be selfish in dynamic content sharing environments according to their social tie strengths, just like their users tend to cooperate with their friends and show selfishness to strangers. Based on social selfishness, a novel device caching game model is proposed to analyze the limited resource and privacy issues in a typical mobile caching scenario. Then, a local optimal caching algorithm with social selfishness (LOCASS) is developed to address these challenging problems. Analytical results show that LOCASS can approach Nash equilibrium of the game, and therefore, achieving the best caching strategy for mixed cooperative and selfish devices. Further, extensive simulation results show that LOCASS offers much better performance, in terms of average offloading ratio and resource utilization, than traditional random, Most-popular-content and Greedy caching algorithms. Besides, under LOCASS, devices with low degrees are most likely to store popular contents, while devices with high degrees are more willing to store those comparatively unpopular contents and fetch popular ones from their cooperative-devices.

Keywords

• Device caching
• social selfishness
• offloading ratio
• Nash equilibrium