Fault-Tolerant Power Assignment and Backbone in Wireless Networks

Carmi, Paz; Segal, Michael; Katz, Matthew J.; Shpungin, Hanan

doi:10.1109/percomw.2006.55

Cited by 11 publications

(9 citation statements)

References 22 publications

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“…For k > 2 we analyze a power assignment developed in [1], and derive some interesting bounds on the stretch factor for both models as well. We also describe how to compute the power assignments distributively without a central coordinating unit.…”

Section: Discussionmentioning

confidence: 99%

“…Finally we can present a theorem which summarizes the properties ofp k . It is a combination of the results obtained in [1] and [56].…”

Section: B General K-strong Connectivitymentioning

confidence: 92%

“…• For any other k, k > 2, we analyze the energy and distance stretch factors of the power assignmentp k , which can be computed in O(n log n) time, based on a power assignment presented in [1], so that c(…”

Section: Our Contributionmentioning

confidence: 99%

“…induces a 2-strongly connected graph. Then we present a power assignment p k , developed in [1] for k-strong connectivity, for any k > 1. In later sections we show that these power assignments also induce good spanners under both, energy and distance, models.…”

Section: Theorem 23 ([56])mentioning

confidence: 99%

“…Developing fault resistant 2 topology control algorithms can play a crucial factor in keeping the network in an operable state. Naturally, the fault resistant version of the MINSC problem is also NP-hard, so the goal was again to develop fault resistant topology control approximation algorithms with a bound on the total cost ( [1], [10], [11], [12]). Low total energy consumption and fault resistance are fundamental for successful network deployment.…”

Section: Introductionmentioning

confidence: 99%

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Near-Optimal Multicriteria Spanner Constructions in Wireless Ad Hoc Networks

Shpungin

Segal

2010

IEEE/ACM Trans. Networking

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Abstract-In this paper we study asymmetric power assignments which induce a low energy k-strongly connected communication graph with spanner properties. We address two spanner models: energy and distance. The former serves as an indicator for the energy consumed in a message propagation between two nodes, while the latter reflects the geographic properties of routing in the induced communication graph. We consider a random wireless ad-hoc network with |V | = n nodes distributed uniformly and independently in a unit square.For k ∈ {1, 2} we propose several power assignments which obtain a good bicriteria approximation on the total cost and stretch factor under the two models. For k > 2 we analyze a power assignment developed in [1], and derive some interesting bounds on the stretch factor for both models as well. We also describe how to compute all the power assignments distributively, and provide simulation results. To the best of our knowledge, these are the first provable theoretical bounds for low cost spanners in wireless ad-hoc networks.

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Section: Discussionmentioning

confidence: 99%

“…Finally we can present a theorem which summarizes the properties ofp k . It is a combination of the results obtained in [1] and [56].…”

Section: B General K-strong Connectivitymentioning

confidence: 92%

Section: Our Contributionmentioning

confidence: 99%

Section: Theorem 23 ([56])mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Near-Optimal Multicriteria Spanner Constructions in Wireless Ad Hoc Networks

Shpungin

Segal

2010

IEEE/ACM Trans. Networking

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Optimal placement and routing strategies for resilient two‐tiered sensor networks

Bari

Jaekel

Bandyopadhyay

2008

Wireless Communications

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In hierarchical sensor networks using relay nodes, sensor nodes are arranged in clusters and higher powered relay nodes can be used as cluster heads. The lifetime of such a network is determined primarily by the lifetime of the relay nodes. In this paper, we propose two new integer linear programs (ILPs) formulations for optimal data gathering, which maximize the lifetime of the upper tier relay node network. Unlike most previous approaches considered in the literature, our formulations can generate optimal solutions under the non-flow-splitting model. Experimental results demonstrate that our approach can significantly extend network lifetime, compared to traditional routing schemes, for the non-flow-splitting model. The lifetime can be further enhanced by periodic updates of the routing strategy based on the residual energy at each relay node. The proposed rescheduling scheme can be used to handle single or multiple relay node failures. We have also presented a very simple and straightforward algorithm for the placement of relay nodes. The placement algorithm guarantees that all the sensor nodes can communicate with at least one relay node and that the relay node network is at least 2-connected. This means that failure of a single relay node will not disconnect the network, and data may be routed around the failed node. The worst case performance of the placement algorithm is bounded by a constant with respect to any optimum placement algorithm.typically not feasible so that the lifetime of a sensor network is usually over as soon as the battery (batteries) in critical node(s) [3,4] is(are) depleted.In sensor networks, all data flow from the sensor nodes toward the base station (BS), whose location is usually fixed. The transmission power dissipated by a sender node to transmit each bit of data to a receiver node greatly increases with the increase of the distance between the sender and the receiver [1,3,[5][6][7]. Therefore, nodes located further away from the BS use some intermediate node(s) to forward the data to the BS. In such a data-gathering model, it is possible that some nodes are required to relay more data and/or over higher distances, compared to other nodes, and hence dissipate energy at higher rates. This uneven energy dissipation among the nodes leads to the faster 'death' of some nodes in the network, assuming that initial energy provisioning for all nodes are equal. This may cause the network to lose its usefulness, even though many other nodes in the network still retain power and a careful load distribution could have prolonged the useful lifetime of the network. Determining an optimal routing scheme that balances the load on different nodes and maximizes the network lifetime is a non-trivial task.Recently, some special nodes, called relay nodes, have been proposed in sensor networks to achieve various objectives, for example, balanced data gathering, reduction of transmission range, connectivity, and fault tolerance [4,[8][9][10]. These relay nodes may serve as cluster heads in a hierarchica...

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