Abstract
Social media traffic is considered the primary source of Internet traffic. Such traffic is largely facilitated by mobile devices. Consequently, cellular networks tend to experience significantly high traffic load, and mobile users tend to incur high cellular costs. In order to alleviate such effects, we strive to allow social media users to have more reliance on vehicular rather than cellular networks for data access. However, this can be impeded by the high delay and low packet delivery ratio often associated with content access from remote data providers in vehicular networks. Thus, we introduce the Vehicular Optimal Proactive Caching (VOPC) benchmark to quantify the potential gains of predictive proactive caching in improving the quality of Internet services in vehicular networks. In VOPC, we exploit the fact that some users tend to exhibit a somewhat predictable behavior in terms of the type and time of social media access during the daily route they follow, as well as the period of encounter with road segments along that route. Such a predictable behavior is utilized to pre-cache the data at parked vehicles to be proactively procured by requesters as they pass by. The objective is to maximize cache hits by assigning replicas to caching spots that yield maximum certainty in their spatiotemporal availability for requesters. This is while sustaining a cache capacity limit. VOPC formulates the caching problem as an integer linear programming optimization problem and can thus act as an upper bound on reachable potential. Performance evaluation substantiates the ability of VOPC to act as a benchmark that can quantify the potential gains of the heuristic-based predictive caching scheme in terms of delay, packet delivery ratio, and cache hit ratio.
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