Reducing Network Overhead with Common Junction Methodology

In structured and unstructured Peer-to-Peer (P2P) systems, frequent joining and leaving of peer nodes causes topology mismatch between the P2P logical overlay network and the physical underlay network. This topology mismatch problem generates high volumes of redundant traffic in the network. This paper presents Common Junction Methodology (CJM) to reduce network overhead by optimize the overlay traffic at underlay level. CJM finds common junction between available paths, and traffic is only routed through the common junction and not through the conventional identified paths. CJM does not alter overlay topology and performs without affecting the search scope of the network. Simulation results show that CJM resolves the mismatch problem and significantly reduces redundant P2P traffic up to 87% in the best case for the simulated network. CJM can be implemented over structured or unstructured P2P networks, and also reduces the response time by 53% approximately for the network.

Reducing Network Overhead with Common Junction Methodology

In structured and unstructured Peer-to-Peer (P2P) systems, frequent joining and leaving of peer nodes causes topology mismatch between the P2P logical overlay network and the physical underlay network. This topology mismatch problem generates high volumes of redundant traffic in the network. This paper presents Common Junction Methodology (CJM) to reduce network overhead by optimize the overlay traffic at underlay level. CJM finds common junction between available paths, and traffic is only routed through the common junction and not through the conventional identified paths. CJM does not alter overlay topology and performs without affecting the search scope of the network. Simulation results show that CJM resolves the mismatch problem and significantly reduces redundant P2P traffic up to 87% in the best case for the simulated network. CJM can be implemented over structured or unstructured P2P networks, and also reduces the response time by 53% approximately for the network.