Dharmistha D. Vishwakarma

Development and Simulation of Artificial Neural Network Based Decision on Parametric Values for Performance Optimization of Reactive Routing Protocol for MANET Using Qualnet

Collection of wireless nodes like mobile, laptops, palmtops etc. can creates a dynamic wireless network without using any existing infrastructure known as Mobile Ad-Hoc Network (MANET). MANET performs peer to peer interactions among the wireless nodes participating in the network. Each node in the network must be able to function as a router as well to relay the packets generated by other nodes. Due to the mobility of nodes network topology changes frequently and the topology changes information must update every time to all the nodes in the network. Limited bandwidth and transmission characteristic impose administrative and control information to update the dynamic charge in the network topology, due to the mobility of the wireless nodes. Information update at some fixed time interval can cause unnecessary traffic in the wireless network so to make adaptive the time interval of these messages is a technique to improve the performance of the network. In this paper a soft computing technique Artificial Neural Network based reactive AODV routing protocol is proposed to determine the frequency of hello interval to improve the performance of the network.

GTS Allocation Strategy for IEEE 802.15.4 WSN

This paper details about the performance of the GTS allocation mechanism in IEEE 802.15.4. The analysis gives a full understanding of the behavior of the GTS mechanism with regards to Throughput and Wasted Bandwidth due to IFS. The impact of IEEE 802.15.4 parameters on the Wasted Bandwidth of a GTS allocation is analyzed which pave the way for an efficient dimensioning of an IEEE 802.15.4 cluster. The Proposed Scheme is focused to reduce the underutilization of Bandwidth and hence can be used to optimize the GTS Throughput.