Showing papers by "Samir R. Das published in 2004"

Connected K-coverage problem in sensor networks

Abstract: In overdeployed sensor networks, one approach to conserve energy is to keep only a small subset of sensors active at any instant. In this article, we consider the problem of selecting a minimum size connected K-cover, which is defined as a set of sensors M such that each point in the sensor network is "covered" by at least K different sensors in M, and the communication graph induced by M is connected. For the above optimization problem, we design a centralized approximation algorithm that delivers a near-optimal (within a factor of O(lg n)) solution, and present a distributed version of the algorithm. We also present a communication-efficient localized distributed algorithm which is empirically shown to perform well

Variable radii connected sensor cover in sensor networks

Abstract: One of the useful approaches to exploit redundancy in a sensor network is to actively keep only a small subset of sensors that are sufficient to cover the region required to be monitored. The set of active sensors should also form a connected communication graph, so that they can autonomously respond to application queries and/or tasks. Such a set of active sensors is known as a connected sensor cover, and the problem of selecting a minimum connected sensor cover has been well studied when the transmission radius and sensing radius of each sensor is fixed. In this article, we address the problem of selecting a minimum energy-cost connected sensor cover, when each sensor node can vary its sensing and transmission radius; larger sensing or transmission radius entails higher energy cost. For the above problem, we design various centralized and distributed algorithms, and compare their performance through extensive experiments. One of the designed centralized algorithms (called CGA) is shown to perform within an O(log n) factor of the optimal solution, where n is the size of the network. We have also designed a localized algorithm based on Voronoi diagrams which is empirically shown to perform very close to CGA, and due to its communication-efficiency, results in significantly prolonging the network lifetime.

Serial data fusion using space-filling curves in wireless sensor networks

Abstract: This paper considers serial fusion as a mechanism for collaborative signal detection. The advantage of this technique is that it can use only the sensor observations that are really necessary for signal detection and thus can be very communication efficient. We develop the signal processing mechanisms for serial fusion based on simple models. We also develop a space-filling curve-based routing mechanism for message routing to implement serial fusion. We demonstrate via simulations that serial fusion with curve-based routing performs better, both in terms of detection errors and message cost, relative to commonly used mechanisms such as parallel fusion with a tree-based aggregation scheme.

Performance of dead reckoning‐based location service for mobile ad hoc networks

Abstract: A predictive model-based mobility tracking method, called dead reckoning, is developed for mobile ad hoc networks It disseminates both location and movement models of mobile nodes in the network so that every node is able to predict or track the movement of every other node with a very low overhead The basic technique is optimized to use ‘distance effect’, where distant nodes maintain less accurate tracking information to save overheads The dead reckoning-based location service mechanism is evaluated against three known location dissemination service protocols: simple, distance routing effect algorithm for mobility (DREAM) and geographic region summary service (GRSS) The evaluation is done with geographic routing as an application It is observed that dead reckoning significantly outperforms the other protocols in terms of packet delivery fraction It also maintains low-control overhead Its packet delivery performance is only marginally impacted by increasing speed or noise in the mobility model, that affects its predictive ability Copyright © 2004 John Wiley & Sons, Ltd

Ad hoc network routing for hotspot mitigation and load balancing in wireless LANs

Abstract: A method for balancing network load among mobile hosts includes determining and monitoring a performance of a first access point connected to a mobile host by an infrastructure network, determining that the performance of the first access point is undesirable, and virtualizing a network interface of the mobile host connected to the first access point, wherein an ad hoc network are established in addition to the infrastructure network. The method further including determining a route to a second access point through at least one cooperating mobile host, and switching a connection of the mobile host to the second access point via the route to the second access point, wherein the connection is established via the ad hoc network.

Performance of dead reckoning-based location service for mobile ad hoc networks: Research Articles

Abstract: A predictive model-based mobility tracking method, called dead reckoning, is developed for mobile ad hoc networks. It disseminates both location and movement models of mobile nodes in the network so that every node is able to predict or track the movement of every other node with a very low overhead. The basic technique is optimized to use ‘distance effect’, where distant nodes maintain less accurate tracking information to save overheads. The dead reckoning-based location service mechanism is evaluated against three known location dissemination service protocols: simple, distance routing effect algorithm for mobility (DREAM) and geographic region summary service (GRSS). The evaluation is done with geographic routing as an application. It is observed that dead reckoning significantly outperforms the other protocols in terms of packet delivery fraction. It also maintains low-control overhead. Its packet delivery performance is only marginally impacted by increasing speed or noise in the mobility model, that affects its predictive ability. Copyright © 2004 John Wiley & Sons, Ltd.