Parallel Processing Framework on a P2P System Using Map and Reduce Primitives
This paper presents a parallel processing framework for structured Peer-To-Peer (P2P) networks. A parallel processing task is expressed using Map and Reduce primitives inspired by functional programming models. The Map and Reduce tasks are distributed to a subset of nodes within a P2P network for execution by using a self-organizing multicast tree. The distribution latency cost of multicast method is O(log(N)), where N is a number of target nodes for task processing. Each node getting a task performs the Map task, and the task result is summarized and aggregated in a distributed fashion at each node of the multicast tree during the Reduce task.