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Wireless sensor networks (WSNs) are usually assigned tasks for a single application. Recently, the concept of shared sensor networks, which support multiple concurrent applications, has emerged, reducing the deployment and administrative costs, and increasing the usability and efficiency of the network. Supporting task allocation for multiple concurrent applications in sensor networks (such as target tracking, event detection, etc.) requires sharing applications' tasks (such as sensing, computation, etc.) and available network resources. In this paper, we model the distributed task allocation problem for multiple concurrent applications using a reverse combinatorial auction, in which the bidders (sensor nodes) bid the cost value (in terms available resources) for accomplishing the subset of the applications' tasks. The main objective is to maximize the network lifetime by sharing tasks and network resources among applications, while enhancing the overall application QoS (e.g., deadline). We also propose a heuristic two-phase winner determination protocol to solve the combinatorial reverse auction problem. Simulation results show that the proposed scheme offers efficiency and network scalability.