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The opportunistic computing paradigm is extremely valuable to modern technical and scientific endeavors, as it can support the demand for large and steady amounts of computing capacity. The applications of opportunistic computing environments often require independent and intensive processing over different data sets, characterizing themselves as BoT applications. Opportunistic computing systems, however, usually employ centralized approaches to do task allocation, a problematic situation on sizable settings. This paper proposes and evaluates a peer-to-peer technique that allows the self-scheduling of tasks without any central controller whatsoever, aiming at opportunistic computing scenarios running BoT applications. Its key is to employ range query capabilities of search overlays like Skip Graphs as an infrastructure for fully distributed allocation decisions. Experimental results obtained in a message-passing simulator consisting of 5,000 nodes and 75,000 tasks show that central points of failure were eliminated and communication bottlenecks were highly alleviated, subject to some congestion characteristics of the search overlay.