On demand knowledge‐based memory‐aided rebroadcast algorithm for multimedia voice data transmission in MANET

Abstract

Summary MANET refers to wireless networks in which mobile nodes can be easily adapted to change the location dynamically due to their mobility and offers flexibility in the network configuration. An efficient mechanism for reliable exchanging of the multimedia voice messages through MANET nodes is achieved by route discovery of broadcasting operation. A major problem in such systems is the broadcast overhead and retransmission associated with high dense network and less reachability in sparse network. In systems of vastly dynamic nature, to reduce this broadcast overhead in nodes and to increase the reachability in static or semi static nodes in an environment, an enhanced mechanism shore up called On Demand Knowledge‐Based Memory‐Aided Rebroadcast Algorithm for Multimedia voice Data Transmission in MANET (OMRA) is herewith proposed, which operates on both dense and sparse network. In this scheme, hello multimedia voice messages are broadcast to collect one‐hop neighbor information such as mobility factor, node velocity, node density ratio and uncovered neighbors. Additionally, it determines and preserves inquiry data of mobile nodes when the mobility factor is low ensue in sparse network. By considering these varying nature the rebroadcast delay and rebroadcast probability are adjusted adaptively to decide whether to rebroadcast the inward multimedia voice messages. This paper concentrates only on broadcasting the multimedia voice message through MANET nodes in a reliable manner. The performance study of this work is analyzed by various existing algorithms in the literature such as flooding, Gossip1, DBA, and NCPR. The experimental results proves that the proposed OMRA has got an edge over the existing broadcast schemes in terms of broadcast overhead and retransmission of multimedia voice messages, especially to increase reachability in sparse networks.

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