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With the advances of communications, computing, and positioning technologies, mobile devices have been regarded as mobile computing platforms for various kinds of location-based and human-computation services. However, most existing applications regard each device as a sensor or focus on services with the computation on a single device. In contrast, this paper leverages a group of mobile devices as a collaborative and distributed search platform. Specifically, we propose a search system with mobile devices for rescue and patrol operations. The system utilizes mobile devices to find and assign the search route to each searcher in a collaborative and distributed manner. Given the roads to be searched in an area and the candidate start locations, our system minimizes the time required to search the whole area and guarantees that each road will be searched at least once. We first formulate the k-Person Search Problem for k mobile devices and prove that the problem is NP-Hard. To find the optimal solutions, we propose a centralized algorithm for a special case and an Integer Linear Programming formulation for general cases. We also devise an approximation algorithm. The algorithms can be used to dispatch the searchers before the operation starts. Moreover, to support online adaptation, we formulate the Path Refinement Problem for path exchange among searchers and propose a distributed algorithm to adaptively adjust the paths after the search starts. We also implement the proposed algorithms in mobile devices as a collaborative and distributed search system and demonstrate the efficiency of our algorithms with computation simulations and field trials.