Geographic ad hoc networks use position information for routing. They often utilize stateless greedy forwarding and require the use of recovery algorithms when the greedy approach fails. We propose a novel idea based on virtual repositioning of nodes that allows to increase the efficiency of greedy routing and significantly increase the success of the recovery algorithm based on local information alone. We explain the problem of predicting dead ends, which the greedy algorithm may reach and bypassing voids in the network, and introduce Node Elevation Ad hoc Routing (NEAR), a solution that incorporates both virtual positioning and routing algorithms that improve performance in ad hoc networks containing voids. We demonstrate by simulations the advantages of our algorithm over other geographic ad hoc routing solutions.

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This thesis contributes a new system in support of large scale people-centric sensing applications. Over the last decade, wireless sensor networking has developed into ar-guably the most active area in networking research. The state of the art largely follows an application-specific philosophy, where modest numbers of static wirelessly-connected sensor nodes are placed in the target environment in support of a single application. In a properly engineered network, sensor nodes are well-equipped and well-positioned to best provide the connectivity and sensing required by the application. Such networks are ill-suited, however, to the demands of a new class of applications focused on providing sensor information about people, their daily lives, and their environments. These people-centric applications require the ability to both sample very detailed information on the individual scale, and to provide a view of the urban landscape- a very large scale challenge. A new approach is required. Therefore, we propose the novel MetroSense architecture in support of people-centric sensing. While incorporating static infrastructure elements, to get large scale sensing cover-age the architecture primarily makes use of devices with embedded sensors, such as mobile