EZ-AG: Structure-free data aggregation in MANETs using push-assisted self-repelling random walks

This paper describes EZ-AG, a structure-free protocol for duplicate insensitive data aggregation in MANETs. The key idea in EZ-AG is to introduce a token that performs a self-repelling random walk in the network and aggregates information from nodes when they are visited for the first time. A self-repelling random walk of a token on a graph is one in which at each step, the token moves to a neighbor that has been visited least often. While self-repelling random walks visit all nodes in the network much faster than plain random walks, they tend to slow down when most of the nodes are already visited. In this paper, we show that a single step push phase at each node can significantly speed up the aggregation and eliminate this slow down. By doing so, EZ-AG achieves aggregation in only O(N) time and messages. In terms of overhead, EZ-AG outperforms existing structure-free data aggregation by a factor of at least log(N) and achieves the lower bound for aggregation message overhead. We demonstrate the scalability and robustness of EZ-AG using ns-3 simulations in networks ranging from 100 to 4000 nodes under different mobility models and node speeds. We also describe a hierarchical extension for EZ-AG that can produce multi-resolution aggregates at each node using only O(NlogN) messages, which is a poly-logarithmic factor improvement over existing techniques

Analysis of multi-resolution data aggregation using push-assisted random walks in mobile ad-hoc network (MANET)

ABSTRACT Analysis of Multi-Resolution Data Aggregation using Push-assisted Random Walks in Mobile Ad-hoc Networks (MANETs) Sowmya Srinivasapura Devaraja Data Aggregation in Mobile Ad-hoc Network (MANET) has proven challenging because of changing topology. Structure-based models like tree-based, cluster-based and chain-based have high maintenance cost. In earlier works, different forms of biased random walks have been verified to be effective without need for structure maintenance. The key idea in the protocol was to use one or more tokens that are circulated using biased random walks to effectively compute the data aggregation. One such protocol is EZ-AG that uses Push-assisted Self-Repelling Random Walks . A self-repelling random walk of a token on a graph is one in which at each step, the token moves to a neighbor that has been visited least often. While self-repelling random walks visit all nodes in the network much faster than plain random walks, they tend to slow down when most of the nodes are already visited. It\u27s verified that a single step push phase at each node can significantly speed up the aggregation and eliminate the slow down. Results have been verified that EZ-AG achieves aggregation in only O (N) time and messages. When the network is quite large, obtaining only one aggregate may not be sufficient. It will be more useful to provide distance-sensitive multi-resolution aggregates of data. The contribution in this project is, we have analyzed the Hierarchical EZ-AG proposed to provide multi-resolution results. We show that aggregates for nearby regions are obtained at faster rate in comparison to the farther region. The idea is to introduce the tokens in the network at distinct levels, execute EZ-AG protocol and obtain localized data aggregation output at distinct levels. Existing techniques for hierarchical aggregations require O (N log5.4 (N)) messages. Hierarchical EZ-AG outperforms these techniques by aggregating with only O (N log (N)) messages. We evaluate the performance of hierarchical EZ-AG considering message overhead, token messages, number of aggregations at distinct levels, node speed and mobility. Our results are validated using simulations in network simulator, ns-3 for network ranging from 100 to 4000 nodes under different node speeds and mobility models

Exploiting random walks for robust, scalable, structure-free data aggregation and routing in mobile ad-hoc networks (MANETs)

The focus of this thesis is on the design of scalable data aggregation protocols for Mobile Ad-hoc Networks (MANETs). Data aggregation Protocols that rely on network structures such as trees or backbones are not well suited for MANETs because the underlying topology of MANETs is constantly changing. On the other hand, unstructured techniques such as flooding and gossiping have a high messaging overhead and take a long time to finish. Therefore, in this thesis, we explore the use of random walks as a structure-free alternative for data aggregation in MANETs.;The basic idea is to introduce one or more tokens that successively visit each node in a MANET by executing a random walk and compute the aggregate state. While random walks are simple, robust and overhead-free, plain random walks tend to be slow in visiting all nodes because the token can get stuck in regions of already visited nodes. Therefore, we first introduce self-repelling random walks (SRRW) in which at each step, the token chooses a neighbor that has been visited the least number of times. While SRRW significantly speeds up random walks in the initial stages, towards the end a slowdown is observed when a significant fraction of nodes are already visited. To address this shortcoming, we then develop two complementary strategies that speed up data aggregation.;First, we introduce gradient biased random walks (a pull-based strategy) where short temporary multi-hop gradients are used to pull the tokens toward unvisited node. We prove that gradient biased random walks achieve a cover time of O(N) and message overhead of O(NlogN) where N is the number of nodes in the network. Next, we introduce a push-based strategy in which self-repelling random walks are complemented by a single step push phase before the random walk phase, in which each node broadcasts its information to its neighbors. We show that this small push goes a long way in speeding up data aggregation. Push based random walks finish data aggregation in O(N) message and time. Finally, we describe hierarchical extension of the push-based protocol which can produce multi-resolution aggregates at each node using only O(NlogN) messages.;All our results are validated using simulations in ns-3 in networks ranging from 100 to 4000 nodes under different network densities, node speed and mobility models

Improving the Performance of Wireless LANs

This book quantifies the key factors of WLAN performance and describes methods for improvement. It provides theoretical background and empirical results for the optimum planning and deployment of indoor WLAN systems, explaining the fundamentals while supplying guidelines for design, modeling, and performance evaluation. It discusses environmental effects on WLAN systems, protocol redesign for routing and MAC, and traffic distribution; examines emerging and future network technologies; and includes radio propagation and site measurements, simulations for various network design scenarios, numerous illustrations, practical examples, and learning aids

Hybrid Routing in Delay Tolerant Networks

This work addresses the integration of today\u27s infrastructure-based networks with infrastructure-less networks. The resulting Hybrid Routing System allows for communication over both network types and can help to overcome cost, communication, and overload problems. Mobility aspect resulting from infrastructure-less networks are analyzed and analytical models developed. For development and deployment of the Hybrid Routing System an overlay-based framework is presented