Socialaware Mobile Road Side Unit for Content Distribution in Vehicular Social Networks Network operators are more than ever overwhelmed by increased capital investments and operational costs incurred due to the explosive mobile data traffic growth. An efficient strategy in managing operational expenditure within limits without sacrificing enduser satisfaction is to offload the traffic of content dissemination from the network backbone to local roadside units (RSUs). Allocating suitable subsets of contents to each RSU cache so as to maximize the hit ratio of requests made by vehicular entities is an optimization problem of paramount value. In this paper, we address the issue of content dissemination in a sociallyaware hybrid environment with mobile endusers, wherein an overlay network comprising of a social network over a cellular vehicular network is considered. In this setting, vehicles represent the mobile nodes that obtain requested contents either from base station or from local RSUs, if available. By employing a mobile RSU that accounts for the social characteristics of the underlying network, we introduce a novel approach for content distribution in an urban environment. Results from simulation experiments reveal an average improvement of 6% in network throughput for the proposed method as compared to conventional content dissemination counterparts.

Mobile Offloading in Vehicular Networks: A RewardBased Incentive Caching Scheme The massive growth of mobile vehicles arises immense mobile traffic demand on the current cellular communication system. To cope with this challenge, a new transmission pattern that vehicle nodes cache some data contents in advance and provide data access for future requests via direct contacts has become an appealing solution for data offloading. However due to the limited resources, the fact that vehicle nodes might not be willing to assist data caching and transfer is plausible. Therefore in this paper, we build a rewardbased cachingoffloading framework, which efficiently offload cellular traffic by exploiting the storage capability and contact opportunity among vehicle nodes. The whole framework is divided into request phase and caching phase, an auction mechanism which comprises the bidding strategy, the responseforbids strategy, and the prediction method is designed in the former phase and the optimal caching decision can be derived by solving a 0xe2x80x931 knapsack problem in the latter phase. We conduct simulations on timeevolving topology traces, which validates the feasibility and efficiency of the proposed offloading paradigm.