Body Sensor Networks have gained a lot of research interest lately for the variety of applications they can serve. In such networks where nodes might hold critical information about people's lives, designing efficient routing schemes is very important to guarantee data delivery with the lowest delay and energy consumption. Even though some cluster-based routing schemes were proposed in the literature, none of them offer a complete solution that guarantees energy and delay efficient routing in BSN. In this paper, we propose a robust clusterbased algorithm that increases the routing efficiency through every step of the routing process: cluster formation, cluster head election, and routing operation of data to the sink. The proposed algorithm is compared to existing cluster-based schemes, and MATLAB simulations are performed to assess the performance of the proposed algorithm with respect to delay and energy consumption.

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Crowdsourcing mobile applications are of increasing importance due to their suitability in providing personalized and better matching replies. Crowdsourcing location based services inherit the querying mechanism from its legacy predecessors and this is where the threat lays. In this paper we are going to prove mathematically that the mechanism with highest privacy level "Footprint" does not satisfy the privacy level needed by crowdsourced location based services and then prove that higher privacy level and lower overhead is achieved when these services are implemented in Operator centric mobile cloud architecture.

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