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Topology Control in Wireless Ad Hoc and Sensor Networks
 ACM Computing Surveys
, 2005
"... Topology Control (TC) is one of the most important techniques used in wireless ad hoc and sensor networks to reduce energy consumption (which is essential to extend the network operational time) and radio interference (with a positive effect on the network traffic carrying capacity). The goal of thi ..."
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Cited by 304 (4 self)
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Topology Control (TC) is one of the most important techniques used in wireless ad hoc and sensor networks to reduce energy consumption (which is essential to extend the network operational time) and radio interference (with a positive effect on the network traffic carrying capacity). The goal of this technique is to control the topology of the graph representing the communication links between network nodes with the purpose of maintaining some global graph property (e.g., connectivity), while reducing energy consumption and/or interference that are strictly related to the nodes ’ transmitting range. In this article, we state several problems related to topology control in wireless ad hoc and sensor networks, and we survey stateoftheart solutions which have been proposed to tackle them. We also outline several directions for further research which we hope will motivate researchers to undertake additional studies in this field.
Topology control meets sinr: the scheduling complexity of arbitrary topologies
 in Proceedings of ACM MobiHoc
, 2006
"... To date, topology control in wireless ad hoc and sensor networks—the study of how to compute from the given communication network a subgraph with certain beneficial properties—has been considered as a static problem only; the time required to actually schedule the links of a computed topology with ..."
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Cited by 103 (9 self)
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To date, topology control in wireless ad hoc and sensor networks—the study of how to compute from the given communication network a subgraph with certain beneficial properties—has been considered as a static problem only; the time required to actually schedule the links of a computed topology without message collision was generally ignored. In this paper we analyze topology control in the context of the physical SignaltoInterferenceplusNoiseRatio (SINR) model, focusing on the question of how and how fast the links of a resulting topology can actually be realized over time. For this purpose, we define and study a generalized version of the SINR model and obtain theoretical upper bounds on the scheduling complexity of arbitrary topologies in wireless networks. Specifically, we prove that even in worstcase networks, if the signals are transmitted with correctly assigned transmission power levels, the number of time slots required to successfully schedule all links of an arbitrary topology is proportional to the squared logarithm of the number of network nodes times a previously defined static interference measure. Interestingly, although originally considered without explicit accounting for signal collision in the SINR model, this static interference measure plays an important role in the analysis of link scheduling with physical link interference. Our result thus bridges the gap between static graphbased interference models and the physical SINR model. Based on these results, we also show that when it comes to scheduling, requiring the communication links to be symmetric may imply significantly higher costs as opposed to topologies allowing unidirectional links.
Distributed Connectivity Control of Mobile Networks
, 2007
"... Control of mobile networks raises fundamental and novel problems in controlling the structure of the resulting dynamic graphs. In particular, in applications involving mobile sensor networks and multiagent systems, a great new challenge is the development of distributed motion algorithms that guara ..."
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Cited by 75 (10 self)
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Control of mobile networks raises fundamental and novel problems in controlling the structure of the resulting dynamic graphs. In particular, in applications involving mobile sensor networks and multiagent systems, a great new challenge is the development of distributed motion algorithms that guarantee connectivity of the overall network. In this paper, we address this challenge using a novel control decomposition. First, motion control is performed in the continuous state space, where nearest neighbor potential fields are used to maintain existing links in the network. Second, distributed coordination protocols in the discrete graph space ensure connectivity of the switching network topology. Coordination is based on locally updated estimates of the abstract network topology by every agent as well as distributed auctions that enable tie breaking whenever simultaneous link deletions may violate connectivity. Integration of the overall system results in a distributed, multiagent, hybrid system for which we show that, under certain secondary objectives on the agents and the assumption that the initial network is connected, the resulting motion always satisfies connectivity of the network. Our approach can also account for communication time delays in the network as well as collision avoidance, while its efficiency is illustrated in nontrivial computer simulations.
A ConeBased Distributed TopologyControl Algorithm for Wireless MultiHop Networks
 IEEE/ACM TRANSACTIONS ON NETWORKING
, 2002
"... The topology of a wireless multihop network can be controlled by varying the transmission power at each node. In this paper, we give a detailed analysis of a conebased distributed topology control algorithm. This algorithm does not assume that nodes have GPS information available; rather it dep ..."
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Cited by 62 (1 self)
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The topology of a wireless multihop network can be controlled by varying the transmission power at each node. In this paper, we give a detailed analysis of a conebased distributed topology control algorithm. This algorithm does not assume that nodes have GPS information available; rather it depends only on directional information. Roughly speaking, the basic idea of the algorithm is that a node u transmits with the minimum power p u,# required to ensure that in every cone of degree # around u, there is some node that u can reach with power p u,# . We show that taking # = 5#/6 is a necessary and sufficient condition to guarantee that network connectivity is preserved. More precisely, if there is a path from s to t when every node communicates at maximum power then, if # 5#/6, there is still a path in the smallest symmetric graph G # containing all edges (u, v) such that u can communicate with v using power p u,# . On the other hand, if # > 5#/6,
A Robust Interference Model for Wireless Ad Hoc Networks
 5th International Workshop on Algorithms for Wireless, Mobile, Ad Hoc and Sensor Networks (WMAN
, 2005
"... Among the foremost goals of topology control in wireless adhoc networks is interference reduction. This paper presents a receivercentric interference model featuring two main advantages over previous work. First, it reflects the fact that interference occurs at the intended receiver of a message. ..."
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Cited by 47 (5 self)
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Among the foremost goals of topology control in wireless adhoc networks is interference reduction. This paper presents a receivercentric interference model featuring two main advantages over previous work. First, it reflects the fact that interference occurs at the intended receiver of a message. Second, the presented interference measure is robust with respect to addition or removal of single network nodes. Regarding both of these aspects our model intuitively corresponds to the behavior of interference in reality. Based on this interference model, we show that currently known topology control algorithms poorly reduce interference. Motivated by the observation that already onedimensional network instances display the intricacy of the considered problem, we continue to focus on the socalled highway model. Setting out to analyze the special case of the exponential node chain, we eventually describe an algorithm guaranteeing to achieve a 4 √ ∆approximation of the optimal connectivitypreserving topology in the general highway model. 1.
Randomized 3D Geographic Routing
"... Abstract—We reconsider the problem of geographic routing in wireless ad hoc networks. We are interested in local, memoryless routing algorithms, i.e. each network node bases its routing decision solely on its local view of the network, nodes do not store any message state, and the message itself can ..."
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Cited by 47 (0 self)
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Abstract—We reconsider the problem of geographic routing in wireless ad hoc networks. We are interested in local, memoryless routing algorithms, i.e. each network node bases its routing decision solely on its local view of the network, nodes do not store any message state, and the message itself can only carry information about O(1) nodes. In geographic routing schemes, each network node is assumed to know the coordinates of itself and all adjacent nodes, and each message carries the coordinates of its target. Whereas many of the aspects of geographic routing have already been solved for 2D networks, little is known about higherdimensional networks. It has been shown only recently that there is in fact no local memoryless routing algorithm for 3D networks that delivers messages deterministically. In this paper, we show that a cubic routing stretch constitutes a lower bound for any local memoryless routing algorithm, and propose and analyze several randomized geographic routing algorithms which work well for 3D network topologies. For unit ball graphs, we present a technique to locally capture the surface of holes in the network, which leads to 3D routing algorithms similar to the greedyfacegreedy approach for 2D networks. I.
Localized topology control algorithms for heterogeneous wireless networks
 IEEE TRANS. ON NETWORKING
, 2005
"... Most existing topology control algorithms assume homogeneous wireless networks with uniform maximal transmission power, and cannot be directly applied to heterogeneous wireless networks where the maximal transmission power of each node may be different. We present two localized topology control alg ..."
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Cited by 30 (1 self)
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Most existing topology control algorithms assume homogeneous wireless networks with uniform maximal transmission power, and cannot be directly applied to heterogeneous wireless networks where the maximal transmission power of each node may be different. We present two localized topology control algorithms for heterogeneous networks: Directed Relative Neighborhood Graph (DRNG) and Directed Local Spanning Subgraph (DLSS). In both algorithms, each node independently builds its neighbor set by adjusting the transmission power, and defines the network topology by using only local information. We prove that: 1) both DRNG and DLSS can preserve network connectivity; 2) the outdegree of any node in the resulting topology generated by DRNG or DLSS is bounded by a constant; and 3) DRNG and DLSS can preserve network bidirectionality. Simulation results indicate that DRNG and DLSS significantly outperform existing topology control algorithms for heterogeneous networks in several aspects.
Reducing Interference in Ad hoc Networks through Topology Control
 IN: PROC OF THE 3 RD ACM JOINT WORKSHOP ON FOUNDATIONS OF MOBILE COMPUTING (DIALMPOMC). (2005
, 2005
"... Topology control aims to increase the lifetime of an ad hoc network by selecting only a subset of the available links to be used for routing. The tradeoff between keeping the spanner properties of the graph while sparsifying the graph has been well studied. However, it has often been assumed that a ..."
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Cited by 19 (1 self)
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Topology control aims to increase the lifetime of an ad hoc network by selecting only a subset of the available links to be used for routing. The tradeoff between keeping the spanner properties of the graph while sparsifying the graph has been well studied. However, it has often been assumed that a sparse graph implicitly has low interference, but recent research shows that that is not necessarily true. In this paper, we discuss different methods to measure interference, and present a new interference model that aims to describe the interference of the entire network, rather than just the worst part of it. We present API, a topology control algorithm that serves two purposes: it minimizes the interference in the network according to our metrics, and it keeps the spanner properties of the original graph. The paper is completed by simulations that compare different topologies with respect to different interference metrics.