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This paper assumes a set of identical wireless hosts, each one aware of its location. The network is described by a unit distance graph whose vertices are points on the plane two of which are connected if their distance is at most one. The goal of this paper is to design local distributed solutions that require a constant number of communication rounds, independently of the network size or diameter. This is achieved through a combination of distributed computing and computational complexity tools. Starting with a unit distance graph, the paper shows: 1. How to extract a triangulated planar spanner; 2. Several algorithms are proposed to construct spanning trees of the triangulation. Also, it is described how to construct three spanning trees of the Delaunay triangulation having pairwise empty intersection, with high probability. These algorithms are interesting in their own right, since trees are a popular structure used by many network algorithms; 3. A load balanced distributed storage strategy on top of the trees is presented, that spreads replicas of data stored in the hosts in a way that the difference between the number of replicas stored by any two hosts is small. Each of the algorithms presented is local, and hence so is the final distributed storage solution, obtained by composing all of them. This implies that the solution adapts very quickly, in constant time, to network topology changes. We present a thorough experimental evaluation of each of the algorithms supporting our claims. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) are a family of wireless networks that usually operate with irreplaceable batteries. The energy sources limitation raises the need for designing specific protocols to prolong the operational lifetime of such networks. These protocols are responsible for messages exchanging through the wireless communications medium from the sensors to the base station (sink node). Therefore, the determination of the optimal location of the sink node becomes crucial to assure both the prolongation of the network’s operation and the quality of the provided services. This paper proposes a novel algorithm based on a Particle Swarm Optimization (PSO) approach for designing an energy-aware topology control protocol. The deliverable of the algorithm is the optimal sink node location within a deployment area. The proposed objective function is based on a number of topology control protocol’s characteristics such as numbers of neighbors per node, the nodes’ residual energy, and how they are far from the center of the deployment area. The simulation results show that the proposed algorithm reveals significant effectiveness to both topology construction and maintenance phases of a topology control protocol in terms of the number of active nodes, the topology construction time, the number of topology reconstructions, and the operational network’s lifetime. [ABSTRACT FROM AUTHOR]

As an important application domain of wireless sensor networks (WSN), wireless home sensor network (WHSN) can be built as a traditional WSN. However, when we consider its own character that plug-in sensors are fixed with AC power supply while mobile sensors are battery powered, traditional WSN techniques do not match well. In this paper, we propose a smart wireless home sensor network architecture with improved routing protocols. It is a hierarchical architecture in which AC-powered sensors act as backbone nodes for data retransmission, while battery-powered sensors act as leaves that only transmit data relevant to themselves. Each sensor is assigned with a prime number as its location identifier. For our routing algorithm, the LID is used as routing address and is decomposed to a sequence of prime numbers that indicates the route towards its destination. In addition, we improve existing routing algorithms such as SPIN, LEACH, and DD to incorporate traditional WSN routing algorithms into our smart WHSN architecture, and comparable efficiencies are made between them. Moreover, we propose a network path recovery algorithm for failures that are caused by node mobility or backbone node failures. All our algorithms have been provided with faithful simulations to verify the feasibility and efficiency. [ABSTRACT FROM AUTHOR]

Node position information is one of the important issues in many wireless sensor networks' usages. In this paper, based on path planning, a location predicting method (PPLP) for indoor mobile target localization is proposed. We first establish the path planning model to constrain the movement trajectory of the mobile target in indoor environment according to indoor architectural pattern. Then, one certain localization result can be obtained using MLE algorithm. After that, based on the path-planning model and some previous localization results, the most likely position of the target in the next time interval can be predicted with the proposed predicting approach. Finally, the MLE result and prediction result are weighted to obtain the final position. The simulation results demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Random mobility and energy constraint are two main factors affecting system performance in mobile sensor networks, which cause many difficulties to system design. It is necessary to develop high-efficiency algorithms and protocols for mobile sensor networks to adapt to dynamic network environment and energy limitation. In this paper, a new clustering algorithm based on residual energy difference ratio is presented to improve system performance. Firstly, it is an energy-efficient algorithm. The residual energy of sensor nodes and average residual energy of system are considered in the residual energy difference ratio, which effectively avoid the nodes with low residual energy being selected as cluster heads. An energy-optimal scheme is used in cluster formation phase to minimize energy consumption. Secondly, it is a dynamic algorithm. The system dynamically clusters the sensor nodes according to the data transmission delays. It makes the whole system adapt to the random mobility of sensor nodes. The NS2 software is used to simulate the new clustering algorithm. The simulation experiments can verify the validity of the proposed theory. [ABSTRACT FROM AUTHOR]

The optimal distributed tracking control algorithms over nonlinear cooperative wireless sensor networks (WSNs) are presented in this paper. In order to solve transfer delay and packet loss problem, the architecture of wireless active sensor (WAS) is employed, where a state estimator is embedded, which can provide the needed state information. Furthermore, the optimal distributed tracking control algorithm is proposed. By solving the matrix equations and the adjoint difference equations, the optimal control law can be obtained easily, in which an increment integral regulator is designed to implement tracking target without steady-state error and a nonlinearity compensation term is designed to compensate for the effect produced by system nonlinearity Moreover, the observer-based dynamical algorithm is given considering the physically unrealizable disturbance states and the unavailable sensor states. Finally, computer simulations are carried out with application to two nonlinear pendulums, which prove that the algorithm is effective and easy to implement, and the system achieves the desired performance based on tradeoff between tracking error and control energy consumption. [ABSTRACT FROM AUTHOR]

Low data delivery efficiency and high energy consumption are the inherent problems in Underwater Wireless Sensor Networks (UWSNs) characterized by the acoustic channels. Existing energy-efficient routing algorithms have been shown to reduce energy consumption of UWSNs to some extent, but still neglect the correlation existing in the local data of sensor nodes. In this paper, we present a Multi-population Firefly Algorithm (MFA) for correlated data routing in UWSNs. We design three kinds of fireflies and their coordination rules in order to improve the adaptability of building, selecting, and optimization of routing path considering the data correlation and their sampling rate in various sensor nodes. Different groups of fireflies conduct their optimization in the evolution in order to improve the convergence speed and solution precision of the algorithm. Moreover, after the data packets are merged during the process of routing path finding, MFA can also eliminate redundant information before they are sent to the sink node, which in turn saves energy and bandwidth. Simulation results have shown that MFA achieves better performance than existing protocols in metrics of packet delivery ratio, energy consumption, and network throughput. [ABSTRACT FROM AUTHOR]

Recent communications in wireless sensor networks (WSNs) have much new energy-efficient protocols specifically designed, where energy awareness is an essential consideration. In WSNs, large numbers of tiny sensor nodes are used as an effective way of data gathering in various environments. Since the sensor nodes operate on battery of limited power, it is a great challenging aim to design an energy-efficient routing protocol, which can minimize the delay while offering high-energy efficiency and long span of network lifetime. Low energy adaptive clustering hierarchy (LEACH) is one of the clustering key routing techniques used to reduce energy consumption. In this paper, we propose an energy-efficient node scheduling reclustering algorithm in clusters and rotating cluster-head positions to evenly distribute the energy load among all of the nodes by the node scheduling concept of node active and sleep system in both homogeneous and heterogeneous methods to get energy-saving result. Our proposed model is enhanced from LEACH protocol by adapting node scheduling scheme (active and sleep) in homogeneous and heterogeneous node topologies of WSNs, which yield better performance in energy saving and increased network lifetime. This node scheduling scheme is properly implemented, and simulation results show that our proposed model is giving improved energy efficiency and prolongs the lifetime of WSNs. [ABSTRACT FROM AUTHOR]

Cognitive Wireless Sensor Network (CWSN) is a new paradigm which integrates cognitive features in traditional Wireless Sensor Networks (WSNs) to mitigate important problems such as spectrum occupancy. Security in Cognitive Wireless Sensor Networks is an important problem because these kinds of networks manage critical applications and data. Moreover, the specific constraints of WSN make the problem even more critical. However, effective solutions have not been implemented yet. Among the specific attacks derived from new cognitive features, the one most studied is the Primary User Emulation (PUE) attack. This paper discusses a new approach, based on anomaly behavior detection and collaboration, to detect the PUE attack in CWSN scenarios. A nonparametric CUSUM algorithm, suitable for low resource networks like CWSN, has been used in this work. The algorithm has been tested using a cognitive simulator that brings important results in this area. For example, the result shows that the number of collaborative nodes is the most important parameter in order to improve the PUE attack detection rates. If the 20% of the nodes collaborates, the PUE detection reaches the 98% with less than 1% of false positives. [ABSTRACT FROM AUTHOR]

Data broadcast is a fundamental operation in wireless sensor networks (WSNs). The existence of wireless interference makes it nontrivial to design a minimum-latency broadcast scheme, which is known to be NP-hard. Existing works all assume strict time synchronization and provide centralized TDMA scheduling algorithms. However, WSNs in practice are more likely to be distributed asynchronous systems. In this paper, we investigate the problem of data broadcast with minimum latency for distributed asynchronous WSNs. To this end, we propose a Distributed Asynchronous Broadcast (DAB) algorithm which crucially leverages an elaborately optimized carrier-sensing range together with collision-backoff schemes to coordinate the transmissions among the nodes on a predetermined broadcast backbone. Theoretical analysis shows that DAB is order-optimal and achieves constant factor approximation to the optimal delay. We then conduct extensive simulations to evaluate the practical capability of DAB in asynchronous WSNs and the results corroborate our theoretical analysis. [ABSTRACT FROM AUTHOR]

Localization is the key supporting technology for wireless sensor networks (WSNs). Security and accuracy are the premise of the localization application. Real-world applications of wireless sensor networks are often subject to a variety of adverse circumstances interference, and the localization performance is seriously affected. In this paper, we propose a BRS-based robust secure localization (BRSL) algorithm in order to reduce the impact of the malicious attackers in WSNs. The BRSL method includes two phases. In the first stage, the trust evaluation framework is established on the basis of beta reputation system. In the second phase, we employ the weighted Taylor-series least squares method to estimate the coordinates of sensor nodes. Simulation results demonstrate that the proposed algorithm is robust and effective. [ABSTRACT FROM AUTHOR]

Positioning of the location information of wireless sensor network nodes is one of the key issues in wireless sensor network applications. The traditional node positioning method based on least-square algorithm heavily depends on the ranging accuracy, and therefore cannot guarantee high precision. This paper presents a new method for wireless sensor network node positioning based on nonlinear weighting least-square algorithm. Regarding ranging equation error-weighted sum as a whole, this method starts with the initial iteration point of stepwise refinement to explore the optimal solution and further reduces the positioning computational complexity by the simplification of the Taylor equation. Experimental results demonstrate that promising results have been achieved by using this method. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) are one of the most promising technologies and have immense potential in both the military and civil field. WSNs offer a range of challenges for scientists and engineers of today. The biggest challenge among all is the energy constraint of these networks. In this context, various schemes have been presented in order to improve the life time of these networks and to overcome the energy constraint. One of the effective schemes is based on clustering of sensor nodes within a network in order to improve the network life time and decrease communication latency. Clustering algorithms are believed to be the best for wireless sensor networks because they work on the principle of divide and conquer. This paper includes a brief survey of various existing clustering algorithms and present a new clustering algorithm based on nondetermistic finite automata which further divides the communication between cluster heads into multihop by using a few nodes from each cluster. Performance studies indicate that the proposed algorithm is more efficient in terms of energy consumption and network connectivity. [ABSTRACT FROM AUTHOR]

Compared with the small overhead of data payload in sensor networks, the overhead of MAC address is significant from the point of view of energy-saving. A distributed algorithm (Virtual Grid Spatial Reusing-VGSR) for MAC address assignment is presented in this paper, which is a low energy cost algorithm and reduces the size of the fixed MAC address largely based on the mapping of the geographical position. Moreover, VGSR algorithm scales well with the network size and achieves the optimum performance by adjusting the communication range of sensor nodes. In typical scenarios, the MAC address size is 5 bits and the corresponding average size is only 3.86 bits, which outperforms other existing approaches. [ABSTRACT FROM AUTHOR]

Sensor network research is still in its infancy. There is a large volume of exploratory research. From lack of experimental data and sophisticated models derived from such data, many sensor network publications continue to use data generated from simple models in their algorithm evaluation. It is commonly agreed that data processing algorithms in sensor networks are sensitive to input data. However, no previous efforts have been devoted to quantitatively characterize the range of the algorithm performance when evaluated using different data input.In this paper, we made the first attempt to quantify the algorithm's sensitivity to data. Our evaluation results demonstrated that different data input could change the algorithm performance by as much as an order of magnitude or even change the relative performance order of two alternative algorithms. This pointed out the need to evaluate sensor network systems with data representing a wide range of real-world scenarios. For each algorithm in our case study, we identified a small set of data characteristics essential to the algorithm's performance. This defined a unique feature of our synthetic data generation framework and made both synthetic data generation and evaluation scalable. To support systematic algorithm evaluation and robust algorithm design and deployment, our synthetic data generation toolbox can generate 1. irregular topology data based on empirical models which will maintain important features of the experimental data; and 2. data corresponding to a wide range of parameter values. [ABSTRACT FROM AUTHOR]

This paper reviews some of the recent advances in the development of algorithms for wireless sensor networks. We focus on sensor deployment and coverage, routing, and sensor fusion. [ABSTRACT FROM AUTHOR]

This paper proposes a twice deployment node balance algorithm (TDNB) which guarantees successful detection of the moving target on road networks. Through dividing the deployment of the sensor nodes into two phases instead of deploying all the sensors at one time, TDNB has a better performance. In the former phase, some of the sensors are deployed on the road at random. In the latter phase, the rest of the sensors are deployed on demand to make the number on each path the same. Due to the equivalence of the node's number, the network will have a prolonged lifetime after inserting nodes into the segment according to this algorithm. TDNB extends the network's lifetime remarkably compared with the former algorithms. Furthermore, TDNB enables us to insert nodes to the segment required in the network instead of all the segments, which reduces the workload to a large extent. In short, without increasing the number of sensors in road network, TDNB has a better performance compared to VISA in terms of network lifetime, which meets the demand for persistent monitoring application. [ABSTRACT FROM AUTHOR]