Trajectory control of mobile gateways for range extension in ad hoc networks

Mohamed, Ben Ahmed; Krishnamurthy, Srikanth V.; Dao, Son

doi:10.1016/s1389-1286(02)00249-9

Cited by 18 publications

(12 citation statements)

References 5 publications

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“…The goal is to populate a building with the least number of access point (gateways) so that a user can directly reach at least one of them regardless where he is in the building. Meanwhile, the model considered in [2] and [4] is to use a gateway node as a direct router for a group of mobile nodes that would be otherwise unreachable due to topological reasons such as blockages. However the scope is limited to a single gateway system.…”

Section: Related Workmentioning

confidence: 99%

Optimized asset planning for minimizing latency in wireless sensor networks

Youssef

Younis

2008

Wireless Netw

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Wireless Sensor Networks (WSNs) has been attracting lots of interest in recent years. In such networks sensors data are collected over multi-hop routes at one or multiple base-stations (gateway nodes) for processing. In many WSN applications such as disaster management and combat field surveillance, rapid response to detected events is necessary and thus data latency should be minimal. Given the sensor's energy and radio range constraints, direct communication with the gateway is inefficient and often infeasible for most deployed sensors. An intuitive approach to limit data latency is to increase the population of gateways and place them in the vicinity of sensors. However, gateway nodes are typically costly and thus it is desired to limit their count. Therefore, there is a need to balance between such conflicting requirements. In this paper, we pursue an integrated approach to asset planning in WSNs so that the data latency is minimized. The goal is to determine the least number of gateways and identify where to place them in the network in order to achieve a certain delay bound on data delivery. We formulate an optimization model for the asset planning problem and present effective algorithms for solving it. The proposed solution scheme employs contemporary search heuristics such as k-means and genetic algorithms. Validation results confirm the effectiveness of our approach in achieving the desired design goals.

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Section: Related Workmentioning

confidence: 99%

Optimized asset planning for minimizing latency in wireless sensor networks

Youssef

Younis

2008

Wireless Netw

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“…The gateways, also called base stations, in these systems are stationary in nature and are placed in order to achieve coverage of an area or a building using the minimal number of gateway units. Another related work to gateway optimal positioning is reported in [25] [26]. The considered model is to use the gateway node as a direct router for a group of mobile nodes that would be otherwise unreachable due to topological reasons such as blockages.…”

Section: Related Workmentioning

confidence: 99%

Sink repositioning for enhanced performance in wireless sensor networks

2005

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Abstract. Most of the energy aware routing approaches for unattended wireless sensor networks pursue multi-hop paths in order to minimize the total transmission power. Since almost in all sensor networks data are routed towards a single sink (gateway), hops close to that sink become heavily involved in packet forwarding and thus their batteries get depleted rather quickly. In addition, the interest in optimizing the transmission energy tends to increase the levels of packet relaying and thus makes queuing delay an issue, especially for real-time traffic. In this paper we investigate the potential of gateway repositioning for enhanced network performance in terms of energy, de lay and throughput. We address issues related to when should the gateway be relocated, where it would be moved to and how to handle its motion without negative effect on data traffic . We present two approaches that factor in the traffic pattern for determining a new location of the gateway for optimized communication energy and timeliness respectively. The gateway movement is carefully managed in order to avoid packet losses. The proposed approaches are validated in a simulated environment.

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“…We propose a distributed protocol to control the trajectories of the Rnodes such that a reliable routing framework could be provided. In [17], a trajectory control algorithm was proposed for mobile gateways in ad hoc networks. The objective of the trajectory control algorithm is to determine where the gateways are to be placed, relative to the ad hoc group of nodes that the gateway serves such that certain network performance metrics such as throughput was maximized.…”

Section: Related Workmentioning

confidence: 99%

“…The objective of the trajectory control algorithm is to determine where the gateways are to be placed, relative to the ad hoc group of nodes that the gateway serves such that certain network performance metrics such as throughput was maximized. Unlike in [17] wherein one would most likely place the gateways in dense regions within the network, our objective would be to place the R-nodes in sparser regions of the network and control their trajectories so as to increase the probability of establishing a reliable path (defined earlier) between two arbitrary nodes. In order to facilitate the computation of multiple node-disjoint paths from a source to the destination, we choose AODV as a candidate protocol and make modifications to it to enable the discovery of such paths.…”

Section: Related Workmentioning

confidence: 99%

A framework for reliable routing in mobile ad hoc networks

Krishnamurthy

Tripathi

IEEE INFOCOM 2003. Twenty-Second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37

378

287

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Abstract-Mobile ad hoc networks consist of nodes that are often vulnerable to failure. As such, it is important to provide redundancy in terms of providing multiple node-disjoint paths from a source to a destination. We first propose a modified version of the popular AODV protocol that allows us to discover multiple node-disjoint paths from a source to a destination. We find that very few of such paths can be found. Furthermore, as distances between sources and destinations increase, bottlenecks inevitably occur and thus, the possibility of finding multiple paths is considerably reduced. We conclude that it is necessary to place what we call reliable nodes (in terms of both being robust to failure and being secure) in the network for efficient operations. We propose a deployment strategy that determines the positions and the trajectories of these reliable nodes such that we can achieve a framework for reliably routing information. We define a notion of a reliable path which is made up of multiple segments, each of which either entirely consists of reliable nodes, or contains a preset number of multiple paths between the end points of the segment. We show that the probability of establishing a reliable path between a random source and destination pair increases considerably even with a low percentage of reliable nodes when we control their positions and trajectories in accordance with our algorithm.

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Trajectory control of mobile gateways for range extension in ad hoc networks

Cited by 18 publications

References 5 publications

Optimized asset planning for minimizing latency in wireless sensor networks

Optimized asset planning for minimizing latency in wireless sensor networks

Sink repositioning for enhanced performance in wireless sensor networks

A framework for reliable routing in mobile ad hoc networks

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