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69
Opportunitybased topology control in wireless sensor networks
 in ICDCS
, 2008
"... Topology control is an effective method to improve the energy efficiency of wireless sensor networks (WSNs). Traditional approaches are based on the assumption that a pair of nodes is either “connected ” or “disconnected”. These approaches are called connectivitybased topology control. In real envi ..."
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Cited by 139 (21 self)
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Topology control is an effective method to improve the energy efficiency of wireless sensor networks (WSNs). Traditional approaches are based on the assumption that a pair of nodes is either “connected ” or “disconnected”. These approaches are called connectivitybased topology control. In real environments however, there are many intermittently connected wireless links called lossy links. Taking a succeeded lossy link as an advantage, we are able to construct more energyefficient topologies. Towards this end, we propose a novel opportunitybased topology control. We show that opportunitybased topology control is a problem of NPhard. To address this problem in a practical way, we design a fully distributed algorithm called CONREAP based on reliability theory. We prove that CONREAP has a guaranteed performance. The worst running time is O(E) where E is the link set of the original topology, and the space requirement for individual nodes is O(d) where d is the node degree. To evaluate the performance of CONREAP, we design and implement a prototype system consisting of 50 Berkeley Mica2 motes. We also conducted comprehensive simulations. Experimental results show that compared with the connectivitybased topology control algorithms, CONREAP can improve the energy efficiency of a network up to 6 times. 1
Power Optimization in FaultTolerant Topology Control Algorithms for Wireless Multihop Networks
 in Proceedings of the 9th Annual International Conference on Mobile Computing and Networking. 2003
, 2003
"... In ad hoc wireless networks, it is crucial to minimize power consumption while maintaining key network properties. This work studies power assignments of wireless devices that minimize power while maintaining kfault tolerance. Specifically, we require all links established by this power setting be ..."
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Cited by 84 (6 self)
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In ad hoc wireless networks, it is crucial to minimize power consumption while maintaining key network properties. This work studies power assignments of wireless devices that minimize power while maintaining kfault tolerance. Specifically, we require all links established by this power setting be symmetric and form a kvertex connected subgraph of the network graph. This problem is known to be NPhard. We show current heuristic approaches can use arbitrarily more power than the optimal solution. Hence, we seek approximation algorithms for this problem. We present three approximation algorithms. The first algorithm gives an O(kα)approximation where α is the best approximation factor for the related problem in wired networks (the best α so far is O(log k).) With a more careful analysis, we show our second (slightly more complicated) algorithm is an O(k)approximation. Our third algorithm assumes that the edge lengths of the network graph form a metric. In this case, we present simple and practical distributed algorithms for the cases of 2 and 3connectivity with constant approximation factors. We generalize this algorithm to obtain an O(k 2c+2)approximation for general kconnectivity (2 ≤ c ≤ 4 is the power attenuation exponent). Finally, we show that these approximation algorithms compare favorably with existing heuristics. We note that all algorithms presented in this paper can be used to minimize power while maintaining kedge connectivity with guaranteed approximation factors.
Deploying Sensor Networks with Guaranteed Fault Tolerance
, 2005
"... We consider the problem of deploying or repairing a sensor network to guarantee a specified level of multipath connectivity (kconnectivity) between all nodes. Such a guarantee simultaneously provides fault tolerance against node failures and high overall network capacity (by the maxflow mincut t ..."
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Cited by 76 (4 self)
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We consider the problem of deploying or repairing a sensor network to guarantee a specified level of multipath connectivity (kconnectivity) between all nodes. Such a guarantee simultaneously provides fault tolerance against node failures and high overall network capacity (by the maxflow mincut theorem). We design and analyze the first algorithms that place an almostminimum number of additional sensors to augment an existing network into a kconnected network, for any desired parameter k. Our algorithms have provable guarantees on the quality of the solution. Specifically, we prove that the number of additional sensors is within a constant factor of the absolute minimum, for any fixed k. We have implemented greedy and distributed versions of this algorithm, and demonstrate in simulation that they produce highquality placements for the additional sensors.
Approximating minimum cost connectivity problems
 58 in Approximation algorithms and Metaheuristics, Editor
, 2007
"... ..."
Hardness of Approximation for VertexConnectivity NetworkDesign Problems
, 2002
"... In the survivable network design problem (SNDP), the goal is to find a minimumcost spanning subgraph satisfying certain connectivity requirements. We study the vertexconnectivity variant of SNDP in which the input specifies, for each pair of vertices, a required number of vertexdisjoint paths con ..."
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Cited by 50 (4 self)
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In the survivable network design problem (SNDP), the goal is to find a minimumcost spanning subgraph satisfying certain connectivity requirements. We study the vertexconnectivity variant of SNDP in which the input specifies, for each pair of vertices, a required number of vertexdisjoint paths connecting them.
Iterative Rounding 2Approximation Algorithms for MinimumCost Vertex Connectivity Problems
 J. Comput. Syst. Sci
, 2002
"... The survivable network design problem (SNDP) is the following problem: given an undirected graph and values r ij for each pair of vertices i and j, find a minimumcost subgraph such that there are r ij disjoint paths between vertices i and j. In the edge connected version of this problem (ECSNDP) ..."
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Cited by 44 (0 self)
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The survivable network design problem (SNDP) is the following problem: given an undirected graph and values r ij for each pair of vertices i and j, find a minimumcost subgraph such that there are r ij disjoint paths between vertices i and j. In the edge connected version of this problem (ECSNDP) , these paths must be edgedisjoint. In the vertex connected version of the problem (VCSNDP), the paths must be vertex disjoint. The element connectivity problem (ELCSNDP, or ELC) is a problem of intermediate difficulty.
Faulttolerant relay node placement in heterogeneous wireless sensor networks
, 2007
"... Existing work on placing additional relay nodes in wireless sensor networks to improve network connectivity typically assumes homogeneous wireless sensor nodes with an identical transmission radius. In contrast, this paper addresses the problem of deploying relay nodes to provide faulttolerance w ..."
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Cited by 42 (0 self)
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Existing work on placing additional relay nodes in wireless sensor networks to improve network connectivity typically assumes homogeneous wireless sensor nodes with an identical transmission radius. In contrast, this paper addresses the problem of deploying relay nodes to provide faulttolerance with higher network connectivity in heterogeneous wireless sensor networks, where sensor nodes possess different transmission radii. Depending on the level of desired faulttolerance, such problems can be categorized as: (1) full faulttolerance relay node placement, which aims to deploy a minimum number of relay nodes to establish k (k ≥ 1) vertexdisjoint paths between every pair of sensor and/or relay nodes; (2) partial faulttolerance relay node placement, which aims to deploy a minimum number of relay nodes to establish k (k ≥ 1) vertexdisjoint paths only between every pair of sensor nodes. Due to the different transmission
Algorithms for SingleSource Vertex Connectivity
"... In the Survivable Network Design Problem (SNDP) the goal is to find a minimum cost subset of edges that satisfies a given set of pairwise connectivity requirements among the vertices. This general network design framework has been studied extensively and is tied to the development of major algorithm ..."
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Cited by 25 (2 self)
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In the Survivable Network Design Problem (SNDP) the goal is to find a minimum cost subset of edges that satisfies a given set of pairwise connectivity requirements among the vertices. This general network design framework has been studied extensively and is tied to the development of major algorithmic techniques. For the edgeconnectivity version of the problem, a 2approximation algorithm is known for arbitrary pairwise connectivity requirements. However, no nontrivial algorithms are known for its vertex connectivity counterpart. In fact, even highly restricted special cases of the vertex connectivity version remain poorly understood. We study the singlesource kvertex connectivity version of SNDP. We are given a graph G(V, E) with a subset T of terminals and a source vertex s, and the goal is to find a minimum cost subset of edges ensuring that every terminal is kvertex connected to s. Our main result is an O(k log n)approximation algorithm for this problem; this improves upon the recent 2 O(k2) log 4 napproximation. Our algorithm is based on an intuitive rerouting scheme. The analysis relies on a structural result that may be of independent interest: we show that any solution can be decomposed into a disjoint collection of multiplelegged spiders, which are then used to reroute flow from terminals to the source via other terminals. We also obtain the first nontrivial approximation algorithm for the vertexcost version of the same problem, achieving an O(k 7 log 2 n)approximation. 1.
Network Design for Vertex Connectivity
 In Proceedings of ACM Symposium on Theory of Computing (STOC), 2008. 6 C. Chekuri and
, 2008
"... We study the survivable network design problem (SNDP) for vertex connectivity. Given a graph G(V, E) with costs on edges, the goal of SNDP is to find a minimum cost subset of edges that ensures a given set of pairwise vertex connectivity requirements. When all connectivity requirements are between a ..."
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Cited by 25 (4 self)
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We study the survivable network design problem (SNDP) for vertex connectivity. Given a graph G(V, E) with costs on edges, the goal of SNDP is to find a minimum cost subset of edges that ensures a given set of pairwise vertex connectivity requirements. When all connectivity requirements are between a special vertex, called the source, and vertices in a subset T ⊆ V, called terminals, the problem is called the singlesource SNDP. Our main result is a randomized k O(k2) log 4 napproximation algorithm for singlesource SNDP where k denotes the largest connectivity requirement for any sourceterminal pair. In particular, we get a polylogarithmic approximation for any constant k. Prior to our work, no nontrivial approximation guarantees were known for this problem for any k ≥ 3. We also show that SNDP is k Ω(1)hard to approximate and provide an elementary construction that shows that the wellstudied setpair linear programming relaxation for this problem has an ˜ Ω(k 1/3) integrality gap.