Results 1  10
of
33
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 ..."
Abstract

Cited by 84 (6 self)
 Add to MetaCart
(Show Context)
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.
Network Lifetime and Power Assignment in AdHoc Wireless Networks
 IN ESA
, 2003
"... Used for topology control in adhoc wireless networks, Power Assignment is a family of problems, each defined by a certain connectivity constraint (such as strong connectivity) The input consists of a directed complete weighted graph G = (V; c). The power of a vertex u in a directed spanning subgra ..."
Abstract

Cited by 53 (4 self)
 Add to MetaCart
Used for topology control in adhoc wireless networks, Power Assignment is a family of problems, each defined by a certain connectivity constraint (such as strong connectivity) The input consists of a directed complete weighted graph G = (V; c). The power of a vertex u in a directed spanning subgraph H is given by pH(u) = maxuv2E(H) c(uv). The power of H is given by p(H) = P u2V pH(u), Power Assignment seeks to minimize p(H) while H satisfies the given connectivity constraint. We
The power range assignment problem in radio networks on the plane
 Proc. 17th Annual Symposium on Theoretical Aspects of Computer Science (STACS
, 2000
"... Abstract. Given a finite set S of points (i.e. the stations of a radio network) on the plane and a positive integer 1 ≤ h ≤ S  −1, the 2d Min h R. Assign. problem consists of assigning transmission ranges to the stations so as to minimize the total power consumption provided that the transmission ..."
Abstract

Cited by 42 (7 self)
 Add to MetaCart
Abstract. Given a finite set S of points (i.e. the stations of a radio network) on the plane and a positive integer 1 ≤ h ≤ S  −1, the 2d Min h R. Assign. problem consists of assigning transmission ranges to the stations so as to minimize the total power consumption provided that the transmission ranges of the stations ensure the communication between any pair of stations in at most h hops. We provide a lower bound on the total power consumption opt h (S) yielded by an optimal range assignment for any instance (S, h) of2d Min h R. Assign., for any positive constant h>0. The lower bound is a function of S, h and the minimum distance over all the pairs of stations in S. Then, we derive a constructive upper bound for the same problem as a function of S, h and the maximum distance over all the pairs of stations in S (i.e. the diameter of S). Finally, by combining the above bounds, we obtain a polynomialtime approximation algorithm for 2d Min h R. Assign. restricted to wellspread instances, for any positive constant h. Previous results for this problem were known only in special 1dimensional configurations (i.e. when points are arranged on a line).
An Optimal Bound for the MST Algorithm to Compute Energy Efficient Broadcast Trees in Wireless Networks
 IN ICALP
, 2005
"... Computing energy efficient broadcast trees is one of the most prominent operations in wireless networks. For stations embedded in the Euclidean plane, the best analytic result known to date is a 6.33approximation algorithm based on computing an Euclidean minimum spanning tree. We improve the analy ..."
Abstract

Cited by 42 (0 self)
 Add to MetaCart
Computing energy efficient broadcast trees is one of the most prominent operations in wireless networks. For stations embedded in the Euclidean plane, the best analytic result known to date is a 6.33approximation algorithm based on computing an Euclidean minimum spanning tree. We improve the analysis of this algorithm and show that its approximation ratio is 6, which matches a previously known lower bound for this algorithm.
Power efficient range assignment in adhoc wireless networks
 IN PROC. IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC
, 2003
"... We study the problem of assigning transmission ranges to the nodes of ad hoc wireless networks so that to minimize power consumption while ensuring network connectivity. We give (1) an exact branch and cut algorithm based on a new integer linear program formulation solving instances with up to 354 ..."
Abstract

Cited by 26 (2 self)
 Add to MetaCart
(Show Context)
We study the problem of assigning transmission ranges to the nodes of ad hoc wireless networks so that to minimize power consumption while ensuring network connectivity. We give (1) an exact branch and cut algorithm based on a new integer linear program formulation solving instances with up to 3540 nodes in 1 hour; (2) a proof that MINPOWER SYMMETRIC CONNECTIVITY WITH ASYMMETRIC POWER REQUIREMENTS is inapproximable within £¥¤§¦©¨������� � �� � factor for ¨��� � any unless; (3) an improved analysis for two approximation algorithms recently proposed by Călinescu et al. (TCS’02), decreasing the best known approximation factor to �������� ¨ ; (4) a comprehensive experimental study comparing new and previously proposed heuristics with the above exact and approximation algorithms.
Power optimization for connectivity problems
 MATHEMATICAL PROGRAMMING
"... Given a graph with costs on the edges, the power of a node is the maximum cost of an edge leaving it, and the power of the graph is the sum of the powers of the nodes of this graph. Motivated by applications in wireless multihop networks, we consider four fundamental problems under the power minimi ..."
Abstract

Cited by 24 (13 self)
 Add to MetaCart
(Show Context)
Given a graph with costs on the edges, the power of a node is the maximum cost of an edge leaving it, and the power of the graph is the sum of the powers of the nodes of this graph. Motivated by applications in wireless multihop networks, we consider four fundamental problems under the power minimization criteria: the MinPower bEdgeCover problem (MPbEC) where the goal is to find a minpower subgraph so that the degree of every node v is at least some given integer b(v), the MinPower knode Connected Spanning Subgraph problem (MPkCSS), MinPower kedge Connected Spanning Subgraph problem (MPkECSS), and finally the MinPower kEdgeDisjoint Paths problem in directed graphs (MPkEDP). We give an O(log 4 n)approximation algorithm for MPbEC. This gives an O(log 4 n)approximation algorithm for MPkCSS for most values of k, improving the best previously known O(k)approximation guarantee. In contrast, we obtain an O ( √ n) approximation algorithm for MPkECSS, and for its variant in directed graphs (i.e., MPkEDP), we establish the following inapproximability threshold: MPkEDP cannot be approximated within O(2 log1−ε n) for any fixed ε> 0, unless NPhard problems can be solved in quasipolynomial time.
On the Approximation Ratio of the MSTbased Heuristic for the EnergyEfficient Broadcast Problem in Static AdHoc Radio Networks
 Problem in Static AdHoc Radio Networks. Int. Parallel and Distributed Processing Sympos. (IPDPS
, 2003
"... We present a new analysis of the approximation ratio of the MSTbased heuristic [1] for the Minimum Energy Broadcast Problem in AdHoc Radio Networks. ..."
Abstract

Cited by 16 (4 self)
 Add to MetaCart
(Show Context)
We present a new analysis of the approximation ratio of the MSTbased heuristic [1] for the Minimum Energy Broadcast Problem in AdHoc Radio Networks.
TimeEfficient Broadcast in Radio Networks
, 2010
"... Broadcasting is a basic network communication task, where a message initially held by a source node has to be disseminated to all other nodes in the network. Fast algorithms for broadcasting in radio networks have been studied in a wide variety of different models and under different requirements. S ..."
Abstract

Cited by 16 (0 self)
 Add to MetaCart
(Show Context)
Broadcasting is a basic network communication task, where a message initially held by a source node has to be disseminated to all other nodes in the network. Fast algorithms for broadcasting in radio networks have been studied in a wide variety of different models and under different requirements. Some of the main parameters giving rise to the different variants of the problem are the accessibility of knowledge about the network topology, the availability of collision detection mechanisms, the wakeup mode, the topology classes considered, and the use of randomness. This chapter introduces the problem, reviews the literature on timeefficient broadcasting algorithms for radio networks under a variety of models and assumptions, and illustrates some of the basic techniques.
Sharing the Cost of Multicast Transmissions in Wireless Networks
, 2007
"... We investigate the problem of sharing the cost of a multicast transmission in a wireless network in which each node (i.e., radio station) of the network corresponds to a (set of) user(s) potentially interested in receiving the transmission. As in the model considered by Feigenbaum et al. [2001], use ..."
Abstract

Cited by 14 (2 self)
 Add to MetaCart
(Show Context)
We investigate the problem of sharing the cost of a multicast transmission in a wireless network in which each node (i.e., radio station) of the network corresponds to a (set of) user(s) potentially interested in receiving the transmission. As in the model considered by Feigenbaum et al. [2001], users may act selfishly and report a false “level of interest” in receiving the transmission trying to be charged less by the system. We consider the issue of designing so called truthful mechanisms for the problem of maximizing the net worth (i.e., the overall “satisfaction” of the users minus the cost of the transmission) for the case of wireless networks. Intuitively, truthful mechanisms guarantee that no user has an incentive in reporting a false valuation of the transmission. Unlike the “wired” network case, here the cost of a set of connections implementing a multicast tree is not the sum of the single edge costs, thus introducing a complicating factor in the problem. We provide both positive and negative results on the existence of optimal algorithms for the problem and their use to obtain VCG truthful mechanisms achieving the same performances.
Experimental Analysis of Practically Efficient Algorithms for BoundedHop Accumulation
 in AdHoc Wireless Networks, In Proc. of the IEEE IPDPSWMAN
"... The paper studies the problem of computing a minimal energycost range assignment in an adhoc wireless network which allows a set S of stations located in the 2dimensional Euclidean space to perform accumulation (alltoone) operations towards some root station b in at most h hops (2Dim Min hAcc ..."
Abstract

Cited by 12 (5 self)
 Add to MetaCart
The paper studies the problem of computing a minimal energycost range assignment in an adhoc wireless network which allows a set S of stations located in the 2dimensional Euclidean space to perform accumulation (alltoone) operations towards some root station b in at most h hops (2Dim Min hAccumulation Range Assignment problem). We experimentally investigate the behavior of fast and easytoimplement heuristics for the 2Dim Min hAccumulation Range Assignment problem on instances obtained by choosing at random n points in a square of side length L. We compare the performance of an easytoimplement, very fast heuristic with those of three simple heuristics based on classical greedy algorithms (Prim’s and Kruskal’s ones) defined for the Minimum Spanning Tree problem. The comparison is carried out over thousands of random instances in several different situations depending on: the distribution of the stations in the plane, their density, the energy cost function. 1