Showing papers on "Topology control published in 2009"

Hybrid Control for Connectivity Preserving Flocking

Abstract: In this technical note, we address the combined problem of motion and network topology control in a group of mobile agents with common objective the flocking behavior of the group. Instead of assuming network connectivity, we enforce it by means of distributed topology control that decides on both deletion and creation of communication links between agents, adapting the network to the group's spatial distribution. With this protocol ensuring network connectivity, a decentralized motion controller aligns agent velocity vectors and regulates inter-agent distances to maintain existing network links. The stability of the flocking controller is established in continuous time by means of an observability argument on a quadratic form of the graph Laplacian that exploits the time delay between link deletion and creation caused by the topology control protocol, which induces a dwell time between network switches.

RACNet: a high-fidelity data center sensing network

Abstract: RACNet is a sensor network for monitoring a data center's environmental conditions. The high spatial and temporal fidelity measurements that RACNet provides can be used to improve the data center's safety and energy efficiency. RACNet overcomes the network's large scale and density and the data center's harsh RF environment to achieve data yields of 99% or higher over a wide range of network sizes and sampling frequencies. It does so through a novel Wireless Reliable Acquisition Protocol (WRAP). WRAP decouples topology control from data collection and implements a token passing mechanism to provide network-wide arbitration. This congestion avoidance philosophy is conceptually different from existing congestion control algorithms that retroactively respond to congestion. Furthermore, WRAP adaptively distributes nodes among multiple frequency channels to balance load and lower data latency. Results from two testbeds and an ongoing production data center deployment indicate that RACNet outperforms previous data collection systems, especially as network load increases.

Variable radii connected sensor cover in sensor networks

Abstract: One of the useful approaches to exploit redundancy in a sensor network is to keep active only a small subset of sensors that are sufficient to cover the region required to be monitored The set of active sensors should also form a connected communication graph, so that they can autonomously respond to application queries and/or tasks Such a set of active sensors is known as a connected sensor cover, and the problem of selecting a minimum connected sensor cover has been well studied when the transmission radius and sensing radius of each sensor is fixed In this article, we address the problem of selecting a minimum energy-cost connected sensor cover, when each sensor node can vary its sensing and transmission radius; larger sensing or transmission radius entails higher energy costFor the aforesaid problem, we design various centralized and distributed algorithms, and compare their performance through extensive experiments One of the designed centralized algorithms (called CGA) is shown to perform within an O(log n) factor of the optimal solution, where n is the size of the network We have also designed a localized algorithm based on Voronoi diagrams which is empirically shown to perform very close to CGA and, due to its communication-efficiency, results in significantly prolonging the network lifetime We also extend the aforementioned algorithms to incorporate fault tolerance In particular, we show how to extend the algorithms to address the minimum energy-cost connected sensor k-cover problem, in which every point in the query region needs to be covered by at least k distinct active sensors The CGA preserves the approximation bound in this case We also propose a localized topology control scheme to preserve k-connectivity, and use it to extend the Voronoi-based approach to computing a minimum energy-cost k1-connected k2-cover We study the performance of our proposed algorithms through extensive simulations

Fault-Tolerant Algorithms/Protocols in Wireless Sensor Networks

Abstract: Wireless sensor networks (WSNs) have wide variety of applications and provide limitless future potentials. Nodes in WSNs are prone to be failure due to energy depletion, hardware failure, communication link errors, malicious attack, and so on. Therefore, fault tolerance is one of the critical issues in WSNs. The chapter investigates current research work on fault tolerance in WSNs. We study how fault tolerance is addressed in different applications of WSNs. Five categories of applications are discussed: node placement, topology control, target and event detection, data gathering and aggregation, and sensor surveillance. In each category, we focus on the representative research works that presented algorithms and approaches in application layer to achieve fault tolerance.

Topology Control in Wireless Sensor Networks: with a companion simulation tool for teaching and research

Abstract: Topology Control in Wireless Sensor Networks addresses the need for a text that combines the background material needed to understand wireless sensor networks with in-depth material about topology control, which is a very important topic related to this technology; and a companion simulation tool of great value for instructors and researchers.

LTRT: An efficient and reliable topology control algorithm for ad-hoc networks

Abstract: Broadcasting, in the context of ad-hoc networks, is a costly operation, and thus topology control has been proposed to achieve efficient broadcasting with low interference and low energy consumption. By topology control, each node optimizes its transmission power by maintaining network connectivity in a localized manner. Local Minimum Spanning Tree (LMST) is the state-of-the-art topology control algorithm, which has been proven to provide satisfactory performance. However, LMST almost always results in a 1-connected network, without redundancy to tolerate external factors. In this paper, we propose Local Tree-based Reliable Topology (LTRT), which is mathematically proven to guarantee k-edge connectivity while preserving the features of LMST. LTRT can be easily constructed with a low computational complexity of O(k(m + n log n)), where k is the connectivity of the resulting topology, n is the number of neighboring nodes, and m is the number of edges. Simulation results have demonstrated the efficiency of LTRT and its superiority over other localized algorithms.

Game-Theoretic Modeling of Joint Topology Control and Power Scheduling for Wireless Heterogeneous Sensor Networks

Abstract: Wireless Heterogeneous Sensor Network (WHSN) facilitates ubiquitous information acquisition for Ambient Intelligence (AmI) systems. It is of great importance of power management and topology control for WHSN to achieve desirable network performances, such as clustering properties, connectivity and power efficiency. This paper proposes a game theoretic model of topology control to analyze the decentralized interactions among heterogeneous sensors. We study the utility function for nodes to achieve desirable frame success rate and node degree, while minimizing the power consumption. Specifically, we propose a static complete-information game formulation for power scheduling and then prove the existence of the Nash equilibrium with simultaneous move. Because the heterogeneous sensors typically react to neighboring environment based on local information and the states of sensors are evolving over time, the power-scheduling problem in WHSN is further formulated into a more realistic incomplete-information dynamic game model with sequential move. We then analyze the separating equilibrium, one of the perfect Bayesian equilibriums resulted from the dynamic game, with the sensors revealing their operational states from their actions. The sufficient and necessary conditions for the existence of separating equilibrium are derived for the dynamic Bayesian game, which provide theoretical basis to the proposed power scheduling algorithms, NEPow and BEPow. The primary contributions of this paper include applying game theory to analyze the distributed decision-making process of individual sensor nodes and to analyze the desirable utilities of heterogeneous sensor nodes. Simulations are presented to validate the proposed algorithms and the results show their ability of maintaining reliable connectivity, reducing power consumption, while achieving desirable network performances.

Algorithmic models of interference in wireless ad hoc and sensor networks

Abstract: Among the most critical issues of wireless ad hoc and sensor networks are energy consumption in general and interfer-ence in particular. The reduction of interference is consequently considered one of the foremost goals of topology control. Almost all of the related work however considers this issue implicitly: Low interference is often claimed to be a consequence of sparseness or low degree of the constructed topologies. This paper, in contrast, studies explicit definitions of interference. Various models of in-terference--both from a sender-centric and a receiver-centric per-spective--are proposed, compared, and analyzed with respect to their algorithmic properties and complexities.

Using Local Geometry for Tunable Topology Control in Sensor Networks

Abstract: Neighbor-Every-Theta (NET) graphs are such that each node has at least one neighbor in every theta angle sector of its communication range. We show that for thetas < pi, NET graphs are guaranteed to have an edge-connectivity of at least floor (2pi)/thetas, even with an irregular communication range. Our main contribution is to show how this family of graphs can achieve tunable topology control based on a single parameter thetas. Since the required condition is purely local and geometric, it allows for distributed topology control. For a static network scenario, a power control algorithm based on the NET condition is developed for obtaining k-connected topologies and shown to be significantly efficient compared to existing schemes. In controlled deployment of a mobile network, control over positions of nodes can be leveraged for constructing NET graphs with desired levels of network connectivity and sensing coverage. To establish this, we develop a potential fields based distributed controller and present simulation results for a large network of robots. Lastly, we extend NET graphs to 3D and provide an efficient algorithm to check for the NET condition at each node. This algorithm can be used for implementing generic topology control algorithms in 3D.

Atarraya: a simulation tool to teach and research topology control algorithms for wireless sensor networks

Abstract: Topology Control is a well-known technique for saving energy in wireless sensor networks. Despite the fact that topology control algorithms and protocols have been extensively studied, they are currently unavailable in most, if not all, simulation tools. In this work we introduce Atarraya, a discrete-event simulation tool specifically designed for testing and implementing topology control protocols for wireless sensor networks. The simulation tool includes structures for designing both topology construction and topology maintenance protocols. In addition, Atarraya includes several key algorithms and applications that along with its graphical user interface can be used to support teaching activities. The correctness of the tool is validated using well-known results available in the literature.

An Adaptive Partitioning Scheme for Sleep Scheduling and Topology Control in Wireless Sensor Networks

Abstract: This paper presents an adaptive partitioning scheme of sensor networks for node scheduling and topology control with the aim of reducing energy consumption. Our scheme partitions sensors into groups such that a connected backbone network can be maintained by keeping only one arbitrary node from each group in active status while putting others to sleep. Unlike previous approaches that partition nodes geographically, our scheme is based on the measured connectivity between pairwise nodes and does not depend on nodes' locations. In this paper, we formulate node scheduling with topology control as a constrained optimal graph partition problem, which is NP-hard, and propose a Connectivity-based Partition Approach (CPA), which is a distributed heuristic algorithm, to approximate a good solution. We also propose a probability-based CPA algorithm to further save energy. CPA can ensure K-vertex connectivity of the backbone network, which achieves the trade-off between saving energy and preserving network quality. Moreover, simulation results show that CPA outperforms other approaches in complex environments where the ideal radio propagation model does not hold.

Autonomous reconfiguration and control in directional mobile ad hoc networks

Abstract: Requirements for increasingly complex, scalable, and dynamic wireless networks, which provide assured end-to-end broadband connectivity in a wide range of scenarios, have been emerging. In this context, we have been investigating wireless technologies that provide extremely high data rates through the use of narrow-beam free space optical (FSO) and/or radio-frequency (RF) point-to-point links. The use of directional wireless communications to form flexible backbone networks, which provide broadband connectivity to capacity- limited wireless networks or hosts using omnidirectional transmission, promises to circumvent the scalability limitations of traditional flat wireless networks. We have been investigating backbones of base stations, in which topologies and mobility can be controlled for purposes of assured communications. We refer to these as Directional Mobile Ad Hoc Networks (DMANET). Our work considers the use of topology control to assure robust end-to-end broadband connectivity in heterogeneous and dynamic environments. Topology control is defined as the autonomous network capability to dynamically reconfigure its physical topology. In the case of directional wireless backbone (DWB) networks, the physical topology can be reconfigured through: Autonomous 1) Topology Reconfiguration (ATR): dynamic redirection of point-to-point links using heuristic algorithms for creating new topologies and pointing, acquisition and tracking of links. Topology reconfiguration algorithms, which compute minimum energy configurations by determining optimal link assignments between backbone nodes, are presented. The pointing, acquisition and tracking (PAT) process needed to physically redirect point-to-point links is also addressed. 2) Mobility Control (MC): dynamic reposition and "morphing" of backbone nodes. In this model, communication links define physical interactions between network nodes. Control mechanisms are designed to mimic physical systems' natural reaction to external excitations, which drive the network topology to minimum energy configurations Using both ATR and MC, networks are completely selforganizing. They can autonomously adapt their physical topology to maximize coverage to terminals or hosts while maintaining robust backbone connectivity. In this paper, we present the design, implementation and evaluation of our novel approaches to autonomous reconfiguration and control.

A cross-layer approach for QoS topology control in wireless ad hoc networks

Abstract: Wireless ad hoc networks using omni-directional antennas do not scale well due to interference between nearby nodes. Maintaining the QoS of the communications in this type of network is a difficult task. Using multiple narrow beam directional antennas alleviates this problem at the expense of connectivity. Multi-beam Smart Antennas allow the network topology to be adjusted dynamically by adjusting the beamwidth and beam directions to minimize interference and to maximize the number of possible concurrent network communications. This in turn helps to maintain the QoS of the communications. QoS routing has long been used to meet the user requirements by finding appropriate paths to the destinations. We extend this concept to create an Adaptive QoS Topology Control (AQTC) System using Smart Antennas. We use a cross-layer approach to control the topology dynamically where the topology control layer sits between the MAC and the routing protocol. The performance of our protocol has been evaluated using extensive simulations. Simulation results show that different topologies for a set of communications perform differently. AQTC always forms a topology to facilitate the current communications and improves the network throughput and end-to-end delay.

Optimal solutions for fault-tolerant topology control in wireless ad hoc networks

Abstract: Topology control is one of the most important techniques used in wireless ad hoc and sensor networks to reduce energy consumption. Algorithms for topology control attempt to reduce the number of links and the power consumption in a network subject to connectivity constraints. We show that the related optimization problems may be classified into four main variants, regarding the topology of the input graph (symmetric or asymmetric) and of the solution (unidirectional or bidirectional). We present three mixed integer programming formulations for the k-connected minimum power consumption problem, which consists in finding a power assignment to the nodes of a wireless network so as that the resulting network topology be k-vertex connected (i.e., k-fault tolerant) and the total power consumption be minimum. These formulations are sufficiently general to encompass all four problem variants. We report computational experiments comparing the formulations. Optimal solutions for moderately sized networks are obtained using a commercial solver.

A framework for decentralised feedback connectivity control with application to sensor networks

Abstract: In this article, we propose a decentralised algorithm for connectivity maintenance in a distributed sensor network. Our algorithm uses the dynamics of a consensus algorithm to estimate the connectivity of a network topology in a decentralised manner. These estimates are then used to inform a decentralised control algorithm that regulates the network connectivity to some desired level. Under certain realistic assumptions we show that the closed-loop dynamics can be described as a consensus algorithm with an input, and eventually reduces to a scalar system. Bounds are given to ensure the stability of the algorithm and examples are given to illustrate the efficacy of the proposed algorithm.

Topology maintenance: Extending the lifetime of wireless sensor networks

Abstract: Topology control is a well-known strategy to save energy and extend the lifetime of wireless sensor networks. In the literature, it is usually referred as the process that, given a set of nodes, builds a reduced topology that still guarantees connectivity and coverage. Here, we extend this definition. We consider topology control as two processes: topology construction and topology maintenance. Topology construction encompasses those algorithms that build the reduced topology. Topology maintenance is the process that changes the reduced topology from time to time when the current one is no longer optimal. In this paper we define topology maintenance and present different strategies and triggering criteria that can be used to switch the network topology. We also implement static and dynamic global topology maintenance strategies using two well-known topology construction algorithms and time- and energy-based triggering criteria, and compare their performance via simulations on sparse and dense networks. Our results demonstrate that the appropriate use of topology maintenance techniques extends the network lifetime versus the option of not doing topology maintenance at all. In sparse networks, while dynamic global techniques improve the network lifetime, static techniques may improve or degrade the performance. However, all results are fairly similar. On the other hand, topology maintenance is very well justified in dense networks where important performance improvements can be achieved. In this case, the superiority of dynamic global techniques is evident, and even more as the density of the network increases.

Topology Design and Control: A Game-Theoretic Perspective

Abstract: We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the "relaying extent" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central ("social") agent with the ability to impose the initial configuration on the system.

Bio-inspired topology control for knowledge sharing mobile agents

Abstract: We present different approaches for knowledge sharing bio-inspired mobile agents to obtain a uniform distribution of the nodes over a geographical terrain. In this application, the knowledge sharing agents in a mobile ad hoc network adjust their speed and directions based on genetic algorithms (GAs). With an analytical model, we show that the best fitness value is obtained when the number of neighbors for a mobile agent is equal to the mean node degree. The genetic information that each mobile agent exchanges with other neighboring agents within its communication range includes the node's location, speed, and movement direction. We have implemented a simulation software to study the effectiveness of different GA-based algorithms for network performance metrics including node densities, speed, and number of generations that a GA runs. Compared to random-walk and Hill Climbing approaches, all GA-based cases show encouraging results by converging towards a uniform node distribution.

ECTC: Energy effiCient topology control algorithm for wireless sensor networks

Abstract: Sensor network which operates on battery are used to gather data in a variety of environments. The data collected by each node is communicated through the network to the sink, which uses all reported data to determine characteristics of the environment or detect an event. Prolonging sensor's operable lifetime is a main design challenge of these networks. A good energy saving technique in this direction is to schedule nodes sleep interval with the communication radio turned off. In this paper, we propose a distributed topology control algorithm, termed ECTC, which uses a clustering approach. It is built on the notion that when a region of a shared channel wireless sensor network has a sufficient density of nodes, significant energy saving is obtained by allowing redundant nodes to sleep. Using the two-hop neighborhood information, certain nodes sequentially select a subset of nodes to be active among all nodes in the neighborhood, to ensure connectivity. Moreover, to ensure fairness, the role of active nodes is rotated periodically to ensure energy-balanced operations. Results from stochastic geometry are used to derive solutions for the values of parameters of our algorithm that minimize the total energy spent in the network when all sensor nodes report data through the cluster heads to the sink.

A Generalized Probabilistic Topology Control for Wireless Sensor Networks

Abstract: Topology control is an effective method to improve energy-efficiency and increase the capacity in Wireless Sensor Networks (WSNs). To fully characterize WSNs with lossy links, we propose a novel probabilistic network model. Under this model, we meter the network quality using network reachability defined as the minimal of the upper limit of the end-to-end delivery ratio between any pair of nodes in the network.We attempt to find a minimal transmitting power for each node while the network reachability is above a given application- specified threshold, called probabilistic topology control (PTC). We prove that PTC is NP-hard and propose a fully distributed algorithm called BRASP. We prove that BRASP has the guar- anteed performance. Two rules that must be followed by any algorithm have been identified. We conduct both simulations and prototype implementations based an 18-TelosB-node test- bed. The experimental results show that the network energy- efficiency can be improved by up to 250%. The average node degree is reduced by 50% which will lead to a great benefit for the network capacity.

An Energy-Balanced Ant-Based Routing Protocol for Wireless Sensor Networks

Abstract: A variety of cluster based routing protocol have been proposed for wireless sensor networks. Routing problems in WSN can be summarized as: finding a path of data transmission from the source node to the sink node, which can take a smallest cost of energy consumption, at the same time can balance energy consumption of network. In this paper, we introduce the Energy-Balanced Ant-Based Routing Protocol (EBAB). EBAB describes a new adaptive dynamic routing algorithm based on simple biological "ants" that explore the network and find routes. EBAB produces clusters of unequal sizes to balance energy consumption. Clusters closer to the base station have smaller cluster sizes in order to maximize the life time of network. For sake of unequal size of cluster, we do research on optimum transmission range of sensor nodes. The operations of EBAB do not require any geographical location, angle-of-arrival and topology control.

Efficient distributed algorithms for topology control problem with shortest path constraints

Abstract: A Connected Dominating Set (CDS) can be used to construct a virtual backbone for wireless and mobile ad-hoc networks to make the system hierarchical and efficient. A virtual backbone can significantly improve network throughput, optimize broadband utilization, extend network lifetime, and reduce interference as well as packet retransmissions. Calculating a minimum backbone for a network is critical to reduce routing computation and energy consumption. This problem is a well-known NP-hard optimization problem, which has various applications in practice. In this paper, we propose a new problem based on customer fairness, which looks for a minimum CDS in a given communication model with shortest path constraints. It guarantees that any two clients can communicate with each other through this CDS with hop counts the same as the best path from the original graph, which means that routing on such a CDS will not bring additional traffic for every client. We name this problem as shortest path connected dominating set (SPCDS) and prove its NP-hardness by reduction from Hitting Set .T hen we propose a centralized greedy algorithm and an efficient distributed approximation algorithm with approximation ratio ∆ to solve SPCDS, where ∆ is the maximum vertex degree in the given topology. We also analyze the time complexity, message complexity, and evaluate the efficiency of our distributed heuristic by several numerical experiments and comparisons with previous literatures.

Transmission power adjustment of wireless sensor networks using fuzzy control algorithm

Abstract: Energy constraint is the most conspicuous characteristic in wireless sensor networks (WSN) Node deployment, dynamic topology control, and data transmission in WSN all consume a large amount of energy Therefore, proper adjustment of transmission power (TP) contributes much energy saving In this paper, a new TP adjustment method based on Fuzzy Control Theory, called FCTP, is proposed for the dynamic topology control The simulation results show that this method is more robust to tolerate accidental interfere, more rapidly convergent, and more energy efficient than other TP adjustment approaches, which lead to longer network lifetime Copyright © 2008 John Wiley & Sons, Ltd

Improving the topological resilience of mobile ad hoc networks

Abstract: In order to effectively deploy survivability techniques to improve the resilience of mobile ad hoc networks, one must be able to identify all the weak points of the network topology. The weak or critical points of the topology are those links and nodes whose failure results in partitioning of the network. Here we propose a new algorithm based on results from algebraic graph theory, that can find the critical points in the network for single and multiple failure cases. Utilizing this algorithm we present numerical results that examine how the number of critical points varies with nodal density. Secondly, we propose three localized topological control schemes to improve the network connectivity around critical points to lessen their importance and improve the network resilience. Numerical studies to evaluate the proposed schemes under node and link failure network conditions are presented.

Interference-aware topology control for low rate wireless personal area networks

Abstract: The topology control technique can prolong the network lifetime, but it can suffer the significant performance degradation due to the interferences of WLAN or Bluetooth devices. This paper proposes a novel topology control algorithm to reduce the interference effects. The basic idea of the proposed algorithm is to estimate the interference effects exactly and re-construct the robust network topology to the interference variations. From the experimental results, we can see that the proposed algorithm shows the good performance results in terms of the delivery ratio and the energy consumptions.

A game theoretical algorithm for joint power and topology control in distributed WSN

Abstract: In this paper, the issue of network topology control in wireless networks using a fully distributed algorithm is considered. Whereas the proposed distributed algorithm is designed applying game theory concepts to design a non-cooperative game, network connectivity is guaranteed based on asymptotic results of network connectivity. Simulations show that for a relatively low node density, the probability that the proposed algorithm leads to a connected network is close to one.

Measuring Indoor Mobile Wireless Link Quality

Abstract: This paper investigates methods for link quality measurement of an indoor, time-varying wireless link. Link quality estimates are used for a number of higher-layer functions, including rate adaptation, routing, and topology control. The objective is to rapidly and efficiently estimate the current reliability of an RF link in terms of its packet success probability in the presence of a time-varying channel. We compare various approaches to estimating the current packet success rate (PSR), including packet counting and several methods employing physical layer signal-to-noise ratio (SNR) measurements. Among the SNR-based estimators, we consider those using a simple moving average, an exponential moving average, and a Yule-Walker predictor of the current SNR. The analysis shows that the SNR-based estimators are more efficient than packet counting methods in terms of the number of measurements needed, are more accurate when link quality variability increases, and are more flexible in terms of predicting the PSR for various bit rates and packet sizes. An important requirement, however, of the SNR-based estimators is a priori knowledge of the SNR-PSR relationship, which is environment- and radio-dependent. An efficient methodology for obtaining this mapping is presented.

An Energy-Efficient Balanced Clustering Algorithm for Wireless Sensor Networks

Abstract: Clustering is a popular topology control method in wireless sensor networks, which can facilitate the network self-management and make it easy to devise the communication protocols. Also clustering can improve energy efficiency and the network scalability. Existing clustering algorithms concern much about the local energy consumption, but little about the overall energy consumption. A novel energy-efficient, balanced clustering algorithm EEBC is proposed in this paper. In EEBC the sensor nodes are clustered randomly at first, and then they conduct self-adaptive optimization to balance the size of clusters. The structure of the cluster is fixed after the optimization. The operation of EEBC is divided into rounds. At the end of each round the current cluster head selects a node from its cluster members as the next cluster head. The process of the cluster head rotation is transparent to other cluster members. The results of simulations show that EEBC outperforms existing algorithms in energy efficiency and clustering balance.