Performance evaluation of adjusted probabilistic broadcasting in MANETs

Appropriate use of a probabilistic broadcasting method in MANETs can decrease the number of rebroadcasts, and as a result reduce the opportunity of contention and collision among neighbouring nodes. In this paper we evaluate the performance of adjusted probabilistic flooding by comparing it to "simple" flooding as used with the ad hoc on demand distance vector (AODV) routing protocol as well as a fixed probabilistic approach. The results reveal that the adjusted probabilistic flooding exhibits superior performance in terms of both reachability and saved rebroadcast

Improving route discovery in on-demand routing protocols using local topology information in MANETs

Most existing routing protocols proposed for MANETs use flooding as a broadcast technique for the propagation of network control packets; a particular example of this is the dissemination of route requests (RREQs), which facilitate route discovery. In flooding, each mobile node rebroadcasts received packets, which, in this manner, are propagated network-wide with considerable overhead. This paper improves on the performance of existing routing protocols by reducing the communication overhead incurred during the route discovery process by implementing a new broadcast algorithm called the adjusted probabilistic flooding on the Ad-Hoc on Demand Distance Vector (AODV) protocol. AODV [3] is a well-known and widely studied algorithm which has been shown over the past few years to maintain an overall lower routing overhead compared to traditional proactive schemes, even though it uses flooding to propagate RREQs. Our results, as presented in this paper, reveal that equipping AODV with fixed and adjusted probabilistic flooding, instead, helps reduce the overhead of the route discovery process whilst maintaining comparable performance levels in terms of saved rebroadcasts and reachability as achieved by conventional AODV\@. Moreover, the results indicate that the adjusted probabilistic technique results in better performance compared to the fixed one for both of these metrics

Distributed Community Detection in Dynamic Graphs

Inspired by the increasing interest in self-organizing social opportunistic networks, we investigate the problem of distributed detection of unknown communities in dynamic random graphs. As a formal framework, we consider the dynamic version of the well-studied \emph{Planted Bisection Model} \sdG(n,p,q) where the node set $[n]$ of the network is partitioned into two unknown communities and, at every time step, each possible edge $(u,v)$ is active with probability $p$ if both nodes belong to the same community, while it is active with probability $q$ (with $q<<p$) otherwise. We also consider a time-Markovian generalization of this model. We propose a distributed protocol based on the popular \emph{Label Propagation Algorithm} and prove that, when the ratio $p/q$ is larger than $n^{b}$ (for an arbitrarily small constant $b>0$), the protocol finds the right "planted" partition in $O(\log n)$ time even when the snapshots of the dynamic graph are sparse and disconnected (i.e. in the case $p=\Theta(1/n)$).Comment: Version I

Store and Haul: Improving Mobile Ad-Hoc Network Connectivity through Repeated Controlled Flooding

This work investigates the benefits and drawbacks of repeating controlled flooding at different intervals in mobile ad hoc networks (MANETs) to overcome episodic connectivity. Specifically, the thesis examines the efficiencies in repeating transmissions by quantifying the packet delivery ratio (PDR) and recording the resulting delays in different types of MANET scenarios. These scenarios mainly focus on partitions within the simulated networks by varying node density and mobility. The nodes store transmitted data and haul it across the MANET in the hope that it will come in range of a node that leads to the destination. A customized version of the Network Simulator 2 (ns-2) is used to create the simulations. A qualitative analysis follows and shows the cost and benefits of increased transmissions at varied time intervals