Limiting the impact of mobility on ad hoc clustering

Abstract

This paper explores the impact of node mobility on DMAC, a typical clustering protocol for mobile ad hoc networks. Several protocols for clustering have been proposed, which are quite similar in operations and performance. We selected one and evaluate the cost of maintaining the clustering structures when the nodes move according to three different mobility models, namely, the random way point model, the Brownian motion and the Manhattan mobility model. Via ns2-based simulations we have observed that the mobility models have different impact on protocol performance. The general trend, however, appears to be the same for networks of increasing size. The second contribution of this paper concerns mitigating the impact of mobility over the clustering structure and hence on the overall network performance. We consider a generalization of DMAC (GDMAC) where rules are established to decrease the number of cluster updates. Via simulation we have observed that GDMAC is effective in reducing the clustering overhead imposed by mobility, and hence its maintenance cost.

Efficient Data Transfer by Mobility Adjustment Algorithm for Clustered Mobile Ad-Hoc Networks

“…In the Generalized Distributed Mobility Adaptive Clustering (GDMAC) algorithm [18] some neighbours heads are equal to 'K'. The role of the neighbour cluster heads changes only when the weight difference between them exceeds a particular threshold value.…”

A new approach to geographic routing for location aided cluster based MANETs

“…Most of the algorithms such as Weighted Clustering Algorithm (WCA) [7][8][9], Generalized Distributed Mobility Adaptive Clustering (GDMAC) [10] are derived from DMAC. WCA considers degree of connectivity, mobility, battery power and transmission power.…”

Topology Control by Transmission Range Adjustment Protocol for Clustered Mobile Ad Hoc Networks

“…This nonneighborhood restriction of cluster heads and the constraint of affiliating a node to a higher weighted head (if it is found within its transmission range) reduces the clustering efficiency. This problem was overcome by the authors of [13] in the generalized distributed mobility adaptive clustering algorithm (GDMAC) where K numbers of cluster heads are allowed to remain as neighbors. Further, reaffiliation by a node occurs only when the difference in weight values of two neighbor cluster heads exceed a threshold value H.…”