Message and time efficient multi-broadcast schemes

We consider message and time efficient broadcasting and multi-broadcasting in wireless ad-hoc networks, where a subset of nodes, each with a unique rumor, wish to broadcast their rumors to all destinations while minimizing the total number of transmissions and total time until all rumors arrive to their destination. Under centralized settings, we introduce a novel approximation algorithm that provides almost optimal results with respect to the number of transmissions and total time, separately. Later on, we show how to efficiently implement this algorithm under distributed settings, where the nodes have only local information about their surroundings. In addition, we show multiple approximation techniques based on the network collision detection capabilities and explain how to calibrate the algorithms' parameters to produce optimal results for time and messages.Comment: In Proceedings FOMC 2013, arXiv:1310.459

Scalable energy-efficient routing in mobile Ad hoc network

The quick deployment without any existing infrastructure makes mobile ad hoc networks (MANET) a striking choice for dynamic situations such as military and rescue operations, disaster recovery, and so on and so forth. However, routing remains one of the major issues in MANET due to the highly dynamic and distributed environment. Energy consumption is also a significant issue in ad hoc networks since the nodes are battery powered. This report discusses some major dominating set based approaches to perform energy efficient routing in mobile ad hoc networks. It also presents the performance results for each of these mentioned approaches in terms of throughput, average end to end delay and the life time in terms of the first node failure. Based on the simulation results, I identified the key issues in these protocols regarding network life time. In this report, I propose and discuss a new approach “Dynamic Dominating Set Generation Algorithm” (DDSG) to optimize the network life time. This algorithm dynamically selects dominating nodes during the process of routing and thus creates a smaller dominating set. DDSG algorithm thereby eliminates the energy consumption from the non-used dominating nodes. In order to further increase the network life time, the algorithm takes into consideration the threshold settings which helps to distribute the process of routing within the network. This helps to eliminate a single dominating node from getting drained out by continuous transmission and reception of packets. In this report, the detailed algorithmic design and performance results through simulation is discussed

Local Approximation Schemes for Ad Hoc and Sensor Networks

We present two local approaches that yield polynomial-time approximation schemes (PTAS) for the Maximum Independent Set and Minimum Dominating Set problem in unit disk graphs. The algorithms run locally in each node and compute a (1+ε)-approximation to the problems at hand for any given ε > 0. The time complexity of both algorithms is O(TMIS + log*! n/εO(1)), where TMIS is the time required to compute a maximal independent set in the graph, and n denotes the number of nodes. We then extend these results to a more general class of graphs in which the maximum number of pair-wise independent nodes in every r-neighborhood is at most polynomial in r. Such graphs of polynomially bounded growth are introduced as a more realistic model for wireless networks and they generalize existing models, such as unit disk graphs or coverage area graphs

Construction of Pipelined Strategic Connected Dominating Set for Mobile Ad Hoc Networks

Efficient routing between nodes is the most important challenge in a Mobile Ad Hoc Network (MANET). A Connected Dominating Set (CDS) acts as a virtual backbone for routing in a MANET. Hence, the construction of CDS based on the need and its application plays a vital role in the applications of MANET. The PipeLined Strategic CDS (PLS-CDS) is constructed based on strategy, dynamic diameter and transmission range. The strategy used for selecting the starting node is, any source node in the network, which has its entire destination within a virtual pipelined coverage, instead of the node with maximum connectivity. The other nodes are then selected based on density and velocity. The proposed CDS also utilizes the energy of the nodes in the network in an optimized manner. Simulation results showed that the proposed algorithm is better in terms of size of the CDS and average hop per path length