2010 | OriginalPaper | Chapter
Modeling and Performance Analysis of Efficient and Dynamic Probabilistic Broadcasting Algorithm in MANETs Routing Protocols
Authors : Deepak Dembla, Yogesh Chaba
Published in: Recent Trends in Network Security and Applications
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
A MANET (Mobile Adhoc network) is an autonomous system consisting of a set of mobile hosts that are free to move without the need for a wired backbone or a fixed base station. Conventional on-demand route discovery for Adhoc routing protocols extensively use simple flooding, which could potentially lead to high channel contention, causing redundant retransmissions and thus excessive packet collisions in the network. Broadcasting is an essential building block of any MANET, so it is imperative to utilize the most efficient broadcast methods possible, to ensure a reliable network. This paper proposes a new AODV-Efficient and dynamic probabilistic broadcasting approach which is quite efficient and dynamic in nature and solves the broadcast storm problem in AODV. The simulation is done on Global Mobile Simulator (GloMoSim). Routing overhead and end-to-end delays are considered as main performance evaluation metrics. The results show that at a very heavy traffic load , the normalized routing load is reduced to around 35% and 25% compared with AODV-blind flooding and AODV-fixed probability model, when used with AODV-EDPB. The data packets in proposed algorithm experience lower latency than in AODV-blind flooding and AODV-FP model. Also the results show that at higher pause times there is proportionally more decrease in normalized routing load when compared with AODV-FP and AODV-BF approaches and achieve lower overhead and improved delivery latency as compared to conventional AODV, especially in dense networks.