Adaptive Agent Communities For Providing Services In Dynamic Networks

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Title: Adaptive Agent Communities For Providing Services In Dynamic Networks
Author: Mallesh, Nayantara
Abstract: New network applications are being created everyday to accommodate diverse user needs . Delivering services to the user in a timely manner taking into account network conditions , resources allocated and network load is a challenge . Multiprotocol Label Switching attempts to overcome best -effort service by providing a method for routing traffic around network congestion , resource reservation and quality of service (QoS ) capabilities . IntServ and DiffServ are two other QoS models in use today . IntServ provides per -flow guarantee of quality while DiffServ is based on aggregate service classes . Adaptive Network Service (ANS ) is a community of adaptive , collaborating agents residing in the network that aims to provide enhanced performance , better quality of service and improved efficiency of network resources . ANS agents are distributed across the network and are strategically located to provide services and monitor network conditions . ANS agents gather network information in these locations and exchange this information with other agents in the community . Awareness of current network status enables the agent community to efficiently allocate resources and provide services in response to incoming user requests . Sharing information allows agents in one part of the network to be aware of conditions in other parts of the network . ANS uses this information to route user data flows away from congested network areas . The agents also share resource utilization information in different ANS nodes . Routing user connections to different service points based on current resource utilization leads to efficient use of resources . In our implementation we provide a TCP based service for transferring bulk data from a source to a destination . When a user contacts ANS , ANS first determines the best available node to service the user request . The ANS node to service the request is determined before the start of data flow and is selected on the basis of i ) least congestion around the ANS node and ii ) maximum availability of resources in the ANS node . This thesis describes an architecture for ANS and derives a mathematical model for ANS's bulk data transfer service while presenting simulation results for a various experiments demonstrating the benefits of using ANS . Simulation results and model estimates show that ANS is able to achieve superior data transfer throughput compared to connections that do not use ANS scheme . Simulation results show that use of ANS improves data transfer performance by a factor of 2 in low traffic conditions and by a factor of up to 3 .8 times in high traffic conditions . Future work in this direction includes introducing new services into the ANS framework and improving ANS agent intelligence to deliver these services in a user friendly way . We intend to enhance ANS for applications in pervasive computing environments .
URI: http : / /hdl .handle .net /10106 /58
Date: 2007-08-23

Citation

Adaptive Agent Communities For Providing Services In Dynamic Networks. Available electronically from http : / /hdl .handle .net /10106 /58 .

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