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88
Efficient broadcasting in ad hoc wireless networks using directional antennas
 IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
, 2006
"... Using directional antennas to conserve bandwidth and energy consumption in ad hoc wireless networks (or simply ad hoc networks) is becoming popular in recent years. However, applications of directional antennas for broadcasting have been limited. We propose a novel broadcast protocol called directio ..."
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Cited by 19 (6 self)
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Using directional antennas to conserve bandwidth and energy consumption in ad hoc wireless networks (or simply ad hoc networks) is becoming popular in recent years. However, applications of directional antennas for broadcasting have been limited. We propose a novel broadcast protocol called directional selfpruning (DSP) for ad hoc wireless networks using directional antennas. DSP is a nontrivial generalization of an existing localized deterministic broadcast protocol using omnidirectional antennas. Compared with its omnidirectional predecessor, DSP uses about the same number of forward nodes to relay the broadcast packet, while the number of forward directions that each forward node uses in transmission is significantly reduced. With the lower broadcast redundancy, DSP is more bandwidth and energyefficient. DSP is based on 2hop neighborhood information and does not rely on location or angleofarrival (AoA) information. Two special cases of DSP are discussed: the first one preserves shortest paths in reactive routing discoveries; the second one uses the directional reception mode to minimize broadcast redundancy. DSP is a localized protocol. Its expected number of forward nodes is Oð1Þ times the optimal value. An extensive simulation study using both custom and ns2 simulators shows that DSP significantly outperforms both omnidirectional broadcast protocols and existing directional broadcast protocols.
Distributed algorithms for coloring and domination in wireless ad hoc networks
 In Proc. of FSTTCS
, 2004
"... Abstract. We present fast distributed algorithms for coloring and (connected) dominating set construction in wireless ad hoc networks. We present our algorithms in the context of Unit Disk Graphs which are known to realistically model wireless networks. Our distributed algorithms take into account t ..."
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Cited by 18 (0 self)
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Abstract. We present fast distributed algorithms for coloring and (connected) dominating set construction in wireless ad hoc networks. We present our algorithms in the context of Unit Disk Graphs which are known to realistically model wireless networks. Our distributed algorithms take into account the loss of messages due to contention from simultaneous interfering transmissions in the wireless medium. We present randomized distributed algorithms for (conflictfree) Distance2 coloring, dominating set construction, and connected dominating set construction in Unit Disk Graphs. The coloring algorithm has a time complexity of O( ∆ log 2 n) and is guaranteed to use at most O(1) times the number of colors required by the optimal algorithm. We present two distributed algorithms for constructing the (connected) dominating set; the former runs in time O( ∆ log 2 n) and the latter runs in time O(log 2 n). The two algorithms differ in the amount of local topology information available to the network nodes. Our algorithms are geared at constructing Well Connected Dominating Sets (WCDS) which have certain powerful and useful structural properties such as low size, low stretch and low degree. In this work, we also explore the rich connections between WCDS and routing in ad hoc networks. Specifically, we combine the properties of WCDS with other ideas to obtain the following interesting applications: – An online distributed algorithm for collisionfree, low latency, low redundancy and high throughput broadcasting. – Distributed capacity preserving backbones for unicast routing and scheduling. 1
Fast Distributed Well Connected Dominating Sets for Ad Hoc Networks
, 2004
"... We present the first distributed algorithms for computing connected dominating sets (CDS) for ad hoc networks that break the lineartime barrier. We present two algorithms which require O(\Delta log^2 n)andO(log^2 n) running time respectively, where \Delta is the maximum node degree and n is the siz ..."
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Cited by 16 (0 self)
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We present the first distributed algorithms for computing connected dominating sets (CDS) for ad hoc networks that break the lineartime barrier. We present two algorithms which require O(\Delta log^2 n)andO(log^2 n) running time respectively, where \Delta is the maximum node degree and n is the size of the network. This is a substantial improvement over existing implementations, all of which require \Omega(n) running time.
Constructing Minimum Connected Dominating Sets with Bounded Diameters in Wireless Networks
, 2009
"... Connected Dominating Sets (CDSs) can serve as virtual backbones for wireless networks. A smaller virtual backbone incurs less maintenance overhead. Unfortunately, computing a minimum size CDS is NPhard, and thus most researchers in this area concentrate on how to construct smaller CDSs. However, pe ..."
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Cited by 13 (8 self)
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Connected Dominating Sets (CDSs) can serve as virtual backbones for wireless networks. A smaller virtual backbone incurs less maintenance overhead. Unfortunately, computing a minimum size CDS is NPhard, and thus most researchers in this area concentrate on how to construct smaller CDSs. However, people neglected other important metrics of network, such as diameter and average hop distances between two communication parties. In this paper, we investigate the problem of constructing quality CDS in terms of size, diameter, and Average Backbone Path Length (ABPL). We present two centralized algorithms having constant performance ratios for its size and diameter of the constructed CDS. Especially, the size of CDS computed by the second algorithm is no more than 6.906 times of its optimal solution. Furthermore, we give its distributed version, which not only can be implemented in real situation easily but also considers energy to extend network lifetime. In our simulation, we show that in average the distributed algorithm not only generates a CDS with smaller diameter and ABPL than related work but also suppresses its size well. We also show that it is more energy efficient than others in prolonging network lifetime.
Minimum energy broadcasting in multihop wireless networks using a single broadcast tree
 Mobile Networks and Applications
, 2006
"... In this paper we address the minimumenergy broadcast problem in multihop wireless networks, so that all broadcast requests initiated by different source nodes take place on the same broadcast tree. Our approach differs from the most commonly used one where the determination of the broadcast tree d ..."
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Cited by 10 (0 self)
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In this paper we address the minimumenergy broadcast problem in multihop wireless networks, so that all broadcast requests initiated by different source nodes take place on the same broadcast tree. Our approach differs from the most commonly used one where the determination of the broadcast tree depends on the source node, thus resulting in different tree construction processes for different source nodes. Using a single broadcast tree simplifies considerably the tree maintenance problem and allows scaling to larger networks. We first show that, using the same broadcast tree, the total power consumed for broadcasting from a given source node is at most twice the total power consumed for broadcasting from any other source node. We next develop a polynomialtime approximation algorithm for the construction of a single broadcast tree. The performance analysis of the algorithm indicates that the total power consumed for broadcasting from any source node is within 2H(n − 1) from the optimal, where n is the number of nodes in the network and H(n) is the harmonic function. This approximation ratio is close to the best achievable bound in polynomial time. We also provide a useful relation between the minimumenergy broadcast problem and the minimum spanning tree, which shows that a minimum spanning tree may be a good candidate in sparsely connected networks. The performance of our algorithm is also evaluated numerically with simulations.
Graph domination, coloring and cliques in telecommunications
 Handbook of Optimization in Telecommunications, pages 865–890. Spinger Science + Business
, 2006
"... This paper aims to provide a detailed survey of existing graph models and algorithms for important problems that arise in different areas of wireless telecommunication. In particular, applications of graph optimization problems such as minimum dominating set, minimum vertex coloring and maximum cliq ..."
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Cited by 9 (3 self)
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This paper aims to provide a detailed survey of existing graph models and algorithms for important problems that arise in different areas of wireless telecommunication. In particular, applications of graph optimization problems such as minimum dominating set, minimum vertex coloring and maximum clique in multihop wireless networks are discussed. Different forms of graph domination have been used extensively to model clustering in wireless ad hoc networks. Graph coloring problems and their variants have been used to model channel assignment and scheduling type problems in wireless networks. Cliques are used to derive bounds on chromatic number, and are used in models of traffic flow, resource allocation, interference, etc. In this paper we survey the solution methods proposed in the literature for these problems and some recent theoretical results that are relevant to this area of research in wireless networks.
The expected size of the rule k dominating set
 Algorithmica
, 2006
"... Dai, Li, and Wu proposed Rule k, a localized approximation algorithm that attempts to find a small connected dominating set in a graph. Here we consider the “average case”performance of Rule k for the model of random unit disk graphs constructed from n random points in an ℓn × ℓn square. If k ≥ 3 an ..."
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Cited by 7 (0 self)
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Dai, Li, and Wu proposed Rule k, a localized approximation algorithm that attempts to find a small connected dominating set in a graph. Here we consider the “average case”performance of Rule k for the model of random unit disk graphs constructed from n random points in an ℓn × ℓn square. If k ≥ 3 and ℓn = o ( √ n), then the expected size of the Rule k dominating set is Θ(ℓ 2 n) as n → ∞. If ℓn ≤ √ n, then expected size of the minimum CDS is also Θ(ℓ 2 n). 10 log n
A Power Aware Minimum Connected Dominating Set for Wireless Sensor Networks
 Journal of Networks
, 2009
"... Abstract Connected Dominating Set (CDS) problem in unit disk graph has a significant impact on an efficient design of routing protocols in wireless sensor networks. In this paper, an algorithm is proposed for finding Minimum Connected Dominating Set (MCDS) using Dominating Set. Dominating Sets are ..."
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Abstract Connected Dominating Set (CDS) problem in unit disk graph has a significant impact on an efficient design of routing protocols in wireless sensor networks. In this paper, an algorithm is proposed for finding Minimum Connected Dominating Set (MCDS) using Dominating Set. Dominating Sets are connected by using Steiner tree. The algorithm goes through three phases. In first phase Dominating Sets are found, in second phase connectors are identified, connected through Steiner tree. In third phase the CDS obtained in second phase is pruned to obtain a MCDS. MCDS so constructed needs to adapt to the continual topology changes due to deactivation of a node due to exhaustion of battery power. These topological changes due to power constraints are taken care by a local repair algorithm that reconstructs the MCDS i.e. Power Aware MCDS, using only neighbourhood information. Simulation results indicate both the heuristics are very efficient and result in near optimal MCDS. Index Terms Connected Dominating Set, topology, virtual backbone, wireless sensor networks. away from an element of the subset forms a dominating set S. A connected dominating set (CDS) C of G is a dominating set S in which all the elements are connected i.e. it induces a connected graph. The nodes in C are called dominators and the other nodes which are one hop away from C are dominatees. To minimize the number of hops, the minimum CDS is chosen as the backbone.. The backbone is the smallest CDS and every node is adjacent to this virtual backbone. Once data is received by a dominator, it is relayed through the MCDS towards the sink for minimum hop communication. Since the nodes have equal transmission range, the CDS has to be determined for Unit Disk Graph (UDG). The figures of CDS backbone and its UDG can be shown in Figure 1a and in figure 1b respectively. The problem is known to be NPhard and requires heuristics for the determination of the CDS [2].