Browsing by Author "Thampi, S.M."
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Item An agent based peer-to-peer network with thesaurus based searching, and load balancing(2005) Thampi, S.M.; Chandrasekaran, K.This paper describes a search mechanism for files in an unstructured peer-to-peer network. Most of the existing P2P architectures cannot autonomously locate services on the P2P network. Peers can hardly work and cooperate as a team. Using well-designed agents can improve the efficiency of the operations and data communication in the P2P applications. In the proposed system, agents are residing on peers and almost take care of every thing. They receive a problem from the user or other agents, send each job to the responsible agents and merge the sub-solution gathered from them to present a final solution. The communication among nodes takes place through mobile agents. The key features include content matching, parallel downloads, agent based load balancing and thesaurus based searching. � 2005 IEEE.Item An agent based peer-to-peer network with thesaurus based searching, and load balancing(2005) Thampi, S.M.; Chandra Sekaran, K.This paper describes a search mechanism for files in an unstructured peer-to-peer network. Most of the existing P2P architectures cannot autonomously locate services on the P2P network. Peers can hardly work and cooperate as a team. Using well-designed agents can improve the efficiency of the operations and data communication in the P2P applications. In the proposed system, agents are residing on peers and almost take care of every thing. They receive a problem from the user or other agents, send each job to the responsible agents and merge the sub-solution gathered from them to present a final solution. The communication among nodes takes place through mobile agents. The key features include content matching, parallel downloads, agent based load balancing and thesaurus based searching. © 2005 IEEE.Item Autonomous data replication using Q-learning for unstructured P2P networks(2007) Thampi, S.M.; Chandra, Sekaran, K.Resource discovery is an important problem in unstructured peer-to-peer networks as there is no centralized index where to search for information about resources. The solution for the problem is to use a search algorithm that locates the resources based on the local information about the network. Efficient data sharing in a peer-to-peer system is complicated by uneven node failure, unreliable network connectivity and limited bandwidth. A well-known technique for improving availability is replication. If multiple copies of data exist on independent nodes, then the chances of at least one copy being accessible are increased. Replication increases robustness. In this paper, we present a novel technique based on Q-learning for replicating objects to other nodes. � 2007 IEEE.Item Autonomous data replication using Q-learning for unstructured P2P networks(2007) Thampi, S.M.; Chandra Sekaran, K.C.Resource discovery is an important problem in unstructured peer-to-peer networks as there is no centralized index where to search for information about resources. The solution for the problem is to use a search algorithm that locates the resources based on the local information about the network. Efficient data sharing in a peer-to-peer system is complicated by uneven node failure, unreliable network connectivity and limited bandwidth. A well-known technique for improving availability is replication. If multiple copies of data exist on independent nodes, then the chances of at least one copy being accessible are increased. Replication increases robustness. In this paper, we present a novel technique based on Q-learning for replicating objects to other nodes. © 2007 IEEE.Item Elephants journey towards successful resource discovery in unstructured P2P networks(2009) Thampi, S.M.; Chandra, S.K.This paper presents a resource discovery scheme for decentralised unstructured P2P file sharing applications. The scheme utilises the principles underlying elephants migration from dry place to green fields for food. Hence, the proposed approach is a bio-inspired swarm intelligence based search technique. The aim of the technique is to route a query from a node to suitable peers in the network to find the required object. For this, the scheme divides the resource available areas in the network as wet areas and dry areas. The wet areas are resource fertile areas and dry areas have very limited resources. When a node is located in a dry area, its queries are propagated to wet areas for increasing the performance of resource discovery process. At the same time, the powerful nodes try to make the dry area into a resource lush one so that nodes that have moved to wet area return home for resource discovery. Simulation results show that the proposed scheme significantly increases query success rate and reduces the network traffic as the resources are effectively distributed to well-performing nodes. � 2009 IEEE.Item Elephants journey towards successful resource discovery in unstructured P2P networks(2009) Thampi, S.M.; Chandra, S.K.This paper presents a resource discovery scheme for decentralised unstructured P2P file sharing applications. The scheme utilises the principles underlying elephants migration from dry place to green fields for food. Hence, the proposed approach is a bio-inspired swarm intelligence based search technique. The aim of the technique is to route a query from a node to suitable peers in the network to find the required object. For this, the scheme divides the resource available areas in the network as wet areas and dry areas. The wet areas are resource fertile areas and dry areas have very limited resources. When a node is located in a dry area, its queries are propagated to wet areas for increasing the performance of resource discovery process. At the same time, the powerful nodes try to make the dry area into a resource lush one so that nodes that have moved to wet area return home for resource discovery. Simulation results show that the proposed scheme significantly increases query success rate and reduces the network traffic as the resources are effectively distributed to well-performing nodes. © 2009 IEEE.Item Q-feedan effective solution for the free-riding problem in unstructured P2P networks(2010) Thampi, S.M.; Sekaran K, C.This paper presents a solution for reducing the ill effects of free-riders in decentralised unstructured P2P networks. An autonomous replication scheme is proposed to improve the availability and enhance system performance. Q-learning is widely employed in different situations to improve the accuracy in decision making by each peer. Based on the performance of neighbours of a peer, every neighbour is awarded different levels of ranks. At the same time a low-performing node is allowed to improve its rank in different ways. Simulation results show that Q-learning-based free riding control mechanism effectively limits the services received by free-riders and also encourages the low-performing neighbours to improve their position. The popular files are autonomously replicated to nodes possessing required parameters. Due to this improvement of quantity of popular files, free riders are given opportunity to lift their position for active participation in the network for sharing files. Q-feed effectively manages queries from free riders and reduces network traffic significantly. © 2010 S. M. Thampi and C. Sekaran K.Item Q-learning based collaborative load balancing using distributed search for unstructured P2P networks(2008) Thampi, S.M.; Sekaran, K, C.Peer-to-peer structures are becoming more and more popular and an exhilarating new class of ground-breaking, internet-based data management systems. Query load balancing is an important problem for the efficient operation of unstructured P2P networks. The key issue is to identify overloaded peers and reassign their loads to others. This paper proposes a novel mobile agent based two-way load balancing technique for dynamic unstructured P2P networks. In this scheme, target peers are selected based on the result of reinforcement learning. Simulation results indicate that our technique manages the load on peers effectively and increases the search performance significantly. �2008 IEEE.Item Q-learning based collaborative load balancing using distributed search for unstructured P2P networks(2008) Thampi, S.M.; Sekaran K, C.Peer-to-peer structures are becoming more and more popular and an exhilarating new class of ground-breaking, internet-based data management systems. Query load balancing is an important problem for the efficient operation of unstructured P2P networks. The key issue is to identify overloaded peers and reassign their loads to others. This paper proposes a novel mobile agent based two-way load balancing technique for dynamic unstructured P2P networks. In this scheme, target peers are selected based on the result of reinforcement learning. Simulation results indicate that our technique manages the load on peers effectively and increases the search performance significantly. ©2008 IEEE.