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A distributed computing system is able to perform data computation and distribution of results at the same time. The input task is divided into blocks, which are then sent to system participants that offer their resources in order to perform calculations. Next, a partial result is sent back by the participants to the task manager (usually one central node). In the case when system participants want to get the final result, the central node may become overloaded, especially if many nodes request the result at the same time. In this paper we propose a novel distributed computation system, which does not use the central node as the source of the final result, but assumes that partial results are sent between system participants. This way we avoid overloading the central node, as well as network congestion. There are two major types of distributed computing systems: grids and Peer-to-Peer (P2P) computing systems. In this work we focus on the latter case. Consequently, we assume that the computing system works on the top of an overlay network. We present a complete description of the P2P computing system, considering both computation and result distribution. To verify the proposed architecture we develop our own simulator. The obtained results show the system performance expressed by the operation cost for various types of network flows: unicast, anycast and Peer-to-Peer. Moreover, the simulations prove that our computing system provides about 66% lower cost compared to a centralized computing system.


Computer and Systems Architecture | Computer Engineering | Electrical and Computer Engineering | Engineering


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