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This paper presents a new approach for distributed target detection in wireless sensor networks (WSNs). Contrary to the conventional practice where every sensor uses an identical threshold for decision-making, an unequal and dynamic local sensor threshold selection scheme is proposed. This threshold selection scheme is based on a recently proposed statistical metric for multiple testing problems called the False Discovery Rate (FDR). Assuming a signal attenuation model, where the received signal power decays as the distance from the target increases, various performance indices like the system level probability of detection and the probability of false alarm are studied. Simulation results are provided to demonstrate the effectiveness of this approach. [ABSTRACT FROM AUTHOR]

The paper proposes a routing scheme for IPv6-based all-IP wireless sensor networks. The paper creates the IPv6 address structure and the IPv6 address configuration algorithm for all-IP wireless sensor networks. Based on the IPv6 address structure, the paper proposes the routing algorithm in the link layer for all-IP wireless sensor networks. In the routing scheme, a sensor node stores the next channel-sampling time of its neighbor nodes. In this way, only during the next channel-sampling time, a sensor node keeps active. and during any other time it returns to sleep. Therefore, the routing performance is improved. and the power consumption is reduced. Finally, the paper discusses the reduced IPv6 protocol stack performing the routing scheme. The routing scheme's performance parameters are evaluated, including routing power consumption and delay, and the data results show the correctness and efficiency of the scheme. [ABSTRACT FROM AUTHOR]

In a wireless sensor and actuator network (WSAN), a group of sensor nodes, actuators, and actuation devices is geographically distributed and linked by wireless networks. Sensor nodes gather information for an event occurring in the physical world and send the sensed values to actuator nodes. Actuator nodes perform appropriate actions on actuation devices on receipt of sensed values from sensor nodes. Sensor nodes are a low cost, low-powered device with limited energy, computation, and wireless communication capabilities. Sensor nodes may suffer from arbitrary faults. Furthermore, wireless communications are unreliable due to collision and noise of a wireless channel and shortage of power of sensor nodes. Reliable efficient communication among sensor nodes, actuator nodes, and actuation devices is required in the presence of node and network faults. In order to realize the reliability and efficiency, we newly propose a multi-actuator/multi-sensor (MAMS) model where each sensor node sends sensed values to multiple actuator nodes and each actuator node receives sensed values from multiple sensor nodes for each event occurring in an event area. Even if some number of sensor nodes and actuator nodes are faulty and messages sent by sensor nodes and actuator nodes are lost, a required action can be performed on actuation devices. Actuator nodes are required to receive some messages from some number of sensor nodes to make a decision on what actions to be performed on actuation devices. Here, multiple actuator nodes may perform actions on receipt of sensed values. Multiple redundant executions of an action on each device have to be prevented and conflicting actions on each actuation device from multiple actuators have to be serialized. In this paper, we discuss a method to reliably and non-redundantly perform actions. On the other hand, there is one primary actuator node and multiple backup actuator nodes in the passive model. Only the primary actuator node performs actions. In this paper, we present a semi-passive coordination (SPC) model where not only primary but also backup actuator nodes receive messages from sensor nodes. Only one actuator node performs an action on an actuation device and a backup actuator node takes over the primary one if the primary gets faulty. In addition, multiple actuator nodes issue actions to each actuation device. We discuss how to resolve redundant execution of an action on an actuation device and serialize conflicting actions from multiple actuator nodes. [ABSTRACT FROM AUTHOR]

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]

In wireless sensor networks (WSNs), sensors use different types of information, such as temperatures, humidity, magnetic fields, and sound; their communication distances and battery sizes and capacities may be different. Differences in communication distances and battery capacities when the same communication method is used affect the life of the entire sensor network topology. Tests for the maximum life of the sensor network topology require many sensor nodes and huge proportional costs. In addition, experiments to verify new ideas for WSNs as alternatives to existing methods also require large expenditures. Since experiments with the arrangement of actual sensors are expensive, such experiments are conducted using simulators so that solutions for protocol design and verification can be compared through software. Existing simulators are tailored to certain sensor characteristics, so that only quite limited results can be obtained through the implementation of simulated operations, simulations of sensor arrangements, and the comparison of limited information transmission routing functions provided by simulators. This paper proposes diverse sensor definable simulators (DSDs) for the performance of experiments on diverse sensors with different communication distances in WSN environments where Geography Markup Language (GML) based coordinates are utilized. [ABSTRACT FROM AUTHOR]

Opportunistic activity recognition as research discipline is characterized by the fact that human activities (and more generally the context) shall be recognized with sensors that are initially unknown to the system. In contrast to "traditional" applications—where sensors, their modalities, locations, and working characteristics have to be defined at design time—opportunistic systems do not rely on an initially defined and fixed sensing infrastructure. Sensors have to be utilized upon their spontaneous availability and activity recognition capabilities and dynamic sensor ensembles have to be configured at runtime with respect to maximized recognition accuracy and minimized energy consumption. This requirement contains two research challenges that this paper tackles: (i) estimating the accuracy of an ensemble without being able to compare the output in the form of recognized activity classes to a (labeled) ground truth and (ii) optimizing the accuracy/energy trade-off by applying exact and heuristic methods adapted for cooperative sensor ensembles. [ABSTRACT FROM AUTHOR]

Sensor network systems are being expanded with the development of technology for the design of a low-power chips and for operating sensor networks. However, it is difficult to modify or change an application for a stationary sensor node after installation in the field. Furthermore, there is a limit to installation after developing and testing a new sensor node if it needs to reconfigure the software and hardware of the existing sensor node. Therefore, not only is software reconfiguration needed but also dynamic hardware reconfiguration for various changes in requirements, such as sensor type, communication bandwidth, quality of service, or reduced power consumption depending on the changing environment and requirements of users. This paper proposes a specially designed stationary node called a SMART (system management architecture for reconfigurable technology) node, which is capable of dynamic reconfiguration of the various sensing functions or communication protocols. The SMART node can provide suitable service and change the communication protocol according to various surroundings and user requirements. [ABSTRACT FROM AUTHOR]

The mixed wireless sensor networks that are composed of a mixture of mobile and static sensors are the tradeoff between cost and coverage. To provide the required high coverage, the mobile sensors have to move from dense areas to sparse areas. However, where to move and how to move are important issues for mobile sensors. This paper presents a centralized algorithm to assist the movement of mobile sensors. In this algorithm, the management node of the WSN collected the geographical information of all of the static and mobile sensors. Then, the management node executed the algorithm to get the best matches between mobile sensors and coverage holes. Simulation results show the effectiveness of our algorithm, in terms of saving energy and the load balance. [ABSTRACT FROM AUTHOR]

Rotating machinery is widely used in modern industry. It is one of the most critical components in a variety of machinery and equipment. Along with the continuous development of science and technology, the structures of rotating machinery become of larger scale, of higher speed, and more complicated, which results in higher probability of concurrent failure in practice. It is important to enable reliable, safe, and efficient operation of large-scale and critical rotating machinery, which requires us to achieve accurate diagnosis of concurrent fault, for example, rolling bearing diagnosis, gearbox diagnosis, and compressor diagnosis. In this paper, to achieve concurrent fault diagnosis for rotating machinery, which cannot be accurately diagnosed by existing methods, we develop an integrated method using artificial immune algorithm and evidential theory. [ABSTRACT FROM AUTHOR]

Energy hole problem is considered one of the most severe threats in wireless sensor networks. In this paper the idea of exploiting sink mobility for the purpose of culling the energy hole problem in hierarchical large-scale wireless sensor networks based on bees algorithm is presented. In the proposed scheme, a mobile sink equipped with a powerful transceiver and battery, traverses the entire field, and periodically gathers data from network cluster heads. The mobile sink follows an adaptive gathering strategy resilient to both connected and disconnected networks. The proposed gathering strategy geared to eliminate multihop relays required by all cluster heads to reach the mobile sink, balancing the traffic load across all network heads, meanwhile, reducing the loss that data may incur due to buffer overflow. Furthermore, enabling the mobile sink to navigate safely within cluttered and uncluttered fields augments the proposed gathering strategy. Extensive simulations are conducted in order to validate the effectiveness of the proposed strategy. The achieved results show an improvement in overall system performance compared to other mobility strategies. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) have attracted intense interest due to their extensible capability. In this paper, we attempt to answer a fundamental but practical question: "how should we deploy these nodes?" In most current designs, sensor nodes are randomly or uniformly distributed because of their simplicity. However, the node deployment has a great impact on the performance of WSNs. Instead of maintaining the coverage for some snapshots of a WSN, it is essential that we can provide a continuous coverage in the whole lifecycle of the WSN. We will exhibit the weakness of the uniform distribution by disclosing the fatal sink routing-hole problem. To address this problem, we propose a non-uniform, power-aware distribution scheme. Our analysis and simulation results show that the power-aware deployment scheme can significantly improve the long-term network connectivity and service quality. [ABSTRACT FROM AUTHOR]

Characteristics of wireless sensor networks, specifically dense deployment, limited processing power, and limited power supply, provide unique design challenges at the transport layer. Message transmission between sensor nodes over a wireless medium is especially expensive. Care must be taken to design an efficient transport layer protocol that combines reliable message delivery and congestion control with minimal overhead and retransmission. Sensor networks are created using low cost, low power nodes. Wireless sensors are assumed to have a finite lifetime; care must be taken to design and implement transport layer algorithms that allow maximum network lifetime. In this paper we present current and future challenges in the design of transport layers for sensor networks. Current transport layer protocols are compared based on how they implement reliable message delivery, congestion control, and energy efficiency. [ABSTRACT FROM AUTHOR]

Energy conservation is an important design consideration for battery powered wireless sensor networks (WSNET). Energy constraint in WSNETs limits the total amount of sensed data (data capacity) received by sinks. In the commonly used static model of sensor networks with uniformly distributed homogenous sensors with a stationary sink, sensors close to the sink drain their energy much faster than sensors far away from the sink due to the unevenly distributed forwarding workloads among sensors. A major issue, which has not been adequately addressed so far, is the question of how sensor deployment governs the data capacity, and how to improve data capacity of WSNETs. In our previous work, we provided a simple analytical model to address this issue for one specific type of WSNETs. In this paper, we extend our previous work to address this issue for general WSNETs. In the extended static models, for large networks, we find that after the lifetime of a sensor network is over, there is a great amount of energy left unused, which can be up to 90% of the total initial energy. Thus, the static models with uniformly distributed homogenous sensors cannot effectively utilize their energy. This energy waste implies that the potential data capacity is much larger than the capacity achieved in these static models. To increase the total data capacity, we propose a non-uniform sensor distribution strategy. Simulation results show that, for large, dense WSNETs, the non-uniform sensor distribution strategy can increase the total data capacity by an order of magnitude. [ABSTRACT FROM AUTHOR]

Reliable dissemination of bulk data is one of the important problems in sensor networks. For example, programming or upgrading the software in sensors at run-time requires reliable dissemination of a new program across the network. In this paper, we present Infuse, a time division multiple access (TDMA) based reliable data dissemination protocol. Infuse takes two input parameters: i. the choice of the recovery algorithm (from one of two presented in this paper) to deal with unexpected channel errors (e.g., message corruption, varying signal strength), and ii. whether a sensor should listen only to a subset of its neighbors to reduce the amount of active radio time. Based on these parameters, we obtain four possible versions of Infuse. We compare the performance of these versions to assist a designer in selecting the appropriate version based on the network characteristics. Furthermore, we demonstrate Infuse in the context of network programming. [ABSTRACT FROM AUTHOR]

Key pre-distribution is an important area of research in Distributed Sensor Networks (DSN). Two sensor nodes are considered connected for secure communication if they share one or more common secret key(s). It is important to analyse the largest subset of nodes in a DSN where each node is connected to every other node in that subset (i.e., the largest clique). This parameter (largest clique size) is important in terms of resiliency and capability towards efficient distributed computing in a DSN. In this paper, we concentrate on the schemes where the key pre-distribution strategies are based on transversal design and study the largest clique sizes. We show that merging of blocks to construct a node provides larger clique sizes than considering a block itself as a node in a transversal design. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) can be used to monitor long linear structures such as pipelines, rivers, railroads, international borders, and high power transmission cables. In this case a special type of WSN called linear wireless sensor network (LSN) is used. One of the main challenges of using LSN is the reliability of the connections among the nodes. Faults in a few contiguous nodes may cause the creation of holes which will result in dividing the network into multiple disconnected segments. As a result, sensor nodes that are located between holes may not be able to deliver their sensed information which negatively affects the network's sensing coverage. Sensing robots can be used to overcome these faults and enhance the coverage. Sensing robots provide additional sensing coverage and restore the connectivity among disconnected segments. This paper develops a cost-effective design for robot-assisted fault-tolerant LSN. In this design the numbers of fixed sensor nodes and mobile sensing robots are determined such that the required reliability and sensing coverage levels are maintained while the total cost is minimized. The paper covers both uniformly and randomly deployed sensors LSNs. [ABSTRACT FROM AUTHOR]

Cognitive radio (CR) is a regulated technique for opportunistic access of idle resources. In CR, spectrum sensing is one of the key functionalities. It is used to sense the unused spectrum in an opportunistic manner. In this paper, we have proposed two-stage detectors for spectrum sensing in cognitive radio networks (CRN). The first stage consists of multiple energy detectors (MED), where each energy detector (ED) is having single antenna with fixed threshold (MED_FT) for making a local binary decision, and if required, the second stage comprised of ED with adaptive double threshold (ED_ADT) is invoked. The detection performance of the proposed scheme is compared with cyclostationary-based sensing method and adaptive spectrum sensing scheme. Numerical results show that the proposed scheme improves detection performance and outperforms the cyclostationary-based sensing method and adaptive spectrum sensing by 12.3% and 14.4% at signal to noise ratio (SNR) setting of as low as −8 dB, respectively. Performance was also measured in terms of sensing time. It is shown that the proposed scheme yields smaller sensing time than cyclostationary detection and adaptive spectrum sensing scheme in the order of 4.3 ms and 0.1 ms at −20 dB SNR, respectively. [ABSTRACT FROM AUTHOR]

For the Ubiquitous Sensor Network (USN) environment, which generally uses spatial as well as aspatial sensor data, a sensor database system to manage these data is essential. For this reason, sensor database systems such as TinyDB and Cougar are being developed by researchers. However, as most of these systems do not support spatial data types and spatial operators for managing spatial sensor data, they are not suitable for the USN environment. Therefore, in this paper, we design and implement Spatial TinyDB which is a spatial sensor database system that extends TinyDB to support spatial data types and spatial operators for the efficient management of spatial sensor data. In particular, Spatial TinyDB provides memory management and filtering functions to reduce system overload caused by sensor data streams. Finally, we prove that Spatial TinyDB is superior by comparing its actual performance, in terms of execution time, accuracy, and memory usage, with that of TinyDB. [ABSTRACT FROM AUTHOR]

Wireless sensor networks are susceptible to node replication attacks due to their unattended nature. Existing replicas detection schemes can be further improved in regard of detection probabilities, detection overheads, and the balance of detection overheads among sensor nodes. In this paper, we make the following contributions: first, we point out the unrealistic assumption that the replica node would behave honestly as the benign sensor nodes; thus the existing detection schemes would fail if the replica nodes cheat or collude with the compromised node. Then, we propose a location-binding symmetric key scheme forcing the replica nodes to be inserted only in the vicinity of the compromised node. Later, a detecting scheme is presented to inspect the location claims within the neighborhood. Finally, analysis shows that our scheme helps to detect and defend against replication attacks effectively and efficiently. Extensive simulations are conducted and the results show that the detection overheads are low and evenly distributed among all the sensor nodes. [ABSTRACT FROM AUTHOR]

The need for remote monitoring of almost every place in the world is still growing, while many new technical solutions are extensively developed by research community. The knowledge of the environment and the weather conditions of human environment is, in certain cases of polluted places in heavy industrial areas, necessary to allow real-time warnings about deteriorating conditions to living community in these desired places. While huge money investments were used for real-time monitoring of every possible quantity of human body, people's living environment became increasingly poorer. In this paper we present a modern and relatively cheap solution for powering some types of intelligent sensors in which traditional battery power source is insufficient and other powering options are not applicable. Obtaining the energy to supply sensors is possible even from immediate sensors' environment. Sources (which are utilizing thermal gradient) are supplying energy from the surrounding environment and without the need for high-intensity incident light (solar energy based). In order to achieve the full working mode, only a small thermal gradient is needed in order of degrees. The developed test application is using sophisticated electronic circuit provided by Linear Technology Company, which is able to use even small energy bursts for discontinuous intelligent sensors operations. The heat energy is converted into electric energy which is stored in very high-capacity capacitor (about 1 F). This power supply type is suitable for any environment, where some permanent thermal gradient is presented. [ABSTRACT FROM AUTHOR]

The security of the embedded Linux core system is more important than before because this system is becoming more useful to solve the security problem of the computer system than the Windows operating system. It is firstly necessary to identify the normal state of the embedded Linux core system with a model. In this paper, the normal model of this normal system is represented with the space-time property set of all the components in this system. For example, the space property of a file in this system is the absolute pathname of this file, and the time property of this file is its last revision time. This immune embedded Linux core system uses multiple sensors to detect some important information, such as the disaster features. This antidisaster system will be tested on the ARM11 chips. [ABSTRACT FROM AUTHOR]

Biological sensors are a very promising technology that will take healthcare to the next level. However, there are obstacles that must be overcome before the full potential of this technology can be realized. One such obstacle is that the heat generated by biological sensors implanted into a human body might damage the tissues around them. Dynamic sensor scheduling is one way to manage and evenly distribute the generated heat. In this paper, the dynamic sensor scheduling problem is formulated as a Markov decision process (MDP). Unlike previous works, the temperature increase in the tissues caused by the generated heat is incorporated into the model. The solution of the model gives an optimal policy that when executed will result in the maximum possible network lifetime under a constraint on the maximum temperature level tolerable by the patient's body. In order to obtain the optimal policy in a lesser amount of time, two specific types of states are aggregated to produce a considerably smaller MDP model equivalent to the original one. Numerical and simulation results are presented to show the validity of the model and superiority of the optimal policy produced by it when compared with two policies one of which is specifically designed for biological wireless sensor networks. [ABSTRACT FROM AUTHOR]

This paper proposes an optimal mobile sensor-scheduling algorithm for recovering the failure sensors in hybrid wireless sensor networks (WSNs). To maintain a guaranteed coverage over the area of interest, spare mobile sensors in WSNs will be activated to replace the failure sensors. The optimal scheduling problem is formulated into two optimization problems, one of which precisely determines the minimum value of the largest distance required to travel for mobile sensors, while the other one gives the optimal dispatch for mobile sensors to minimize the total travel distance. Furthermore, a distributed suboptimal scheduling, which only requires the local matching information of mobile sensors, is developed as well. Both regular and random network topologies are provided to illustrate the proposed algorithms in the simulation. [ABSTRACT FROM AUTHOR]

Target tracking has become an elementary task in wireless visual sensor networks (WVSNs). In this paper, we propose a camera sensor activation scheme for target tracking in WVSN. Our objective is to balance the tradeoff between the accuracy of target tracking and the resources of networks. By studying the sensing model and deployments of cameras, an observation correlation coefficient is derived to describe the correlation characteristics of visual information observed by cameras with overlapped field of views. According to the observation correlation coefficient, a correlation-based camera activation scheme is designed. Experimental results show that the proposed observation correlation coefficient can model the correlation characteristics of visual information in WVSN. Further simulations show that the correlation-based camera activation scheme has satisfied performance in target tracking compared with other sensor selection methods. [ABSTRACT FROM AUTHOR]

The use of a spatially distributed set of sensors has become a cost-effective approach to achieve surveillance coverage against moving targets. As more sensors are utilized in a collaborative manner, the optimal placement of sensors becomes critical to achieve the most efficient coverage. In this paper, we develop a numerical optimization approach to place distributed sets of sensors to perform surveillance against moving targets over extended areas. In particular, we develop a genetic algorithm solution to find spatial sensor density functions that maximize effectiveness against moving targets, where the surveillance performance of individual sensors is dependent on their absolute position in the region as well as their relative position to both the expected target(s) and any asset that is being protected. The density function representation of optimal sensor locations is shown to provide a computationally efficient method for determining sensor asset location planning. We illustrate the effective performance of this method on numerical examples based on problems of general area surveillance and risk-based surveillance in protection of an asset. [ABSTRACT FROM AUTHOR]

This paper presents a theoretical study for verifying the impact of using smart nodes in motor monitoring systems in industrial environments employing Wireless Sensor Networks (WSNs). Structured cabling and sensor deployment are usually more expensive than the cost of the sensors themselves. Besides the high cost, the wired approach offers little flexibility, making the network deployment and maintenance a complex process. In this context, wireless networks present a number of advantages compared to wired networks as, for example, the ease and speed of deployment and maintenance and the associated low cost. However, WSNs have several limitations, such as the low bandwidth and unreliability, especially in harsh environments (e.g., industrial plants). This paper presents a theoretical study on the performance of WSNs for motor monitoring applications in industrial environments, taking into account WSNs' characteristics (i.e., unreliability and communication and processing latency). The results obtained through mathematical models were analyzed together with experimental results, and it was demonstrated that employing intelligent nodes with local processing capabilities is essential for the applications under consideration, because it reduces the amount of data transmitted over the network allowing monitoring even in scenarios with high interference rate, paying off the extra latency resulting from local processing. [ABSTRACT FROM AUTHOR]

Node deployment is one of the fundamental tasks for underwater acoustic sensor networks (UASNs) where the deployment strategy supports many fundamental network services, such as network topology control, routing, and boundary detection. Due to the complex deployment environment in three-dimensional (3D) space and unique characteristics of underwater acoustic channel, many factors need to be considered specifically during the deployment of UASNs. Thus, deployment issues in UASNs are significantly different from those of wireless sensor networks (WSNs). Node deployment for UASNs is an attractive research topic upon which a large number of algorithms have been proposed recently. This paper seeks to provide an overview of the most recent advances of deployment algorithms in UASNs while pointing out the open issues. In this paper, the deployment algorithms are classified into three categories based on the mobility of sensor nodes, namely, (I) static deployment, (II) self-adjustment deployment, and (III) movement-assisted deployment. The differences of the representative algorithms in aspects of sensor node types, computation complexity, energy consumption, deployment objectives, and so forth, are discussed and investigated in detail. [ABSTRACT FROM AUTHOR]

Wireless sensor network has been applied to many areas for a longtime. A new kind of wireless sensors equipped with a camera and a microphone has been emerging recently. This kind of sensor is called wireless multimedia sensor (WMS) because it can capture and process multimedia data such as image, sound, and video. The visual monitoring network is a typical scenario of WMS application. Massive data would be produced in a short time because of the intensive WMS deployment. Many data aggregation and compression technologies have been proposed for addressing how to transfer data efficiently However, data aggregation technologies need highly efficient router algorithm, and compression algorithms might consume more computation time and memory because of the high complexity. This paper applies data deduplication technology to this scenario. It can eliminate the redundant data from raw data to exploit the network bandwidth efficiently. Moreover, a chunking algorithm with low computation complexity is presented in this paper, and its efficiency has been proved through the experiments. [ABSTRACT FROM AUTHOR]

Wireless sensor networks are increasingly adopted both in aircraft and civil structural health monitoring. However, due to the limited resources on a wireless sensor node, structural evaluation ability of the wireless sensor network is also limited, especially for large-scale structures. This paper presents a multi-agent cooperation system based on mobile agent technology for wireless sensor network-based structural health monitoring which deals with the evaluation of large-scale structure. Mobile agent with the signal processing or evaluation algorithm is designed to migrate among different sensor nodes and perform network self-organization, data processing, information fusion, and damage estimation. This method can reduce the request to the sensor nodes and achieve a better monitoring and evaluation performance through multiagent cooperation. The proposed mobile multiagent system is evaluated by a large dimension aerospace aluminum structure monitoring experiment in which strain distribution and joint failure are monitored by different sensors. Experimental results show that the system can significantly improve the monitoring performance for large-scale structures. [ABSTRACT FROM AUTHOR]

To gain benefit from netted sensors, it is essential to correctly integrate each sensor into a global frame of reference. The process is termed sensor registration. It involves minimizing the effects of the errors from the imprecisely known relative positions or orientations of the various sensors, the biased sensor measurements, the offset sensor clocks, and so on. In the paper, a model of a typical sensor registration problem in a 2-sensor scenario is presented for illustration. Four kinds of registration errors, i.e., calibration errors (offsets), attitude (orientation) errors, position errors, and timing errors are mainly discussed in literatures, and literatures are categorized in the paper by its purpose that which one of the four kinds of errors, or which combination of the decoupled errors among them is aimed to solve. The registration errors can be viewed as constant and they can also vary or drift slowly. To address them, different kinds of algorithms have been developed. The algorithms for sensor registration can be divided into three types referred to as Type 1, Type 2, and Type 3 respectively. Algorithms of Type 1, mainly including batch processing methods and meta-heuristic optimization ones, are applied to cases that the registration errors are constant over time. Algorithms of Type 2 provide online estimation of sensor biases, but it is decoupled from the target estimation. The assumption for constant errors is relaxed, and the approaches are extended to cope with both constant and varying errors. The algorithms of Type 3 attempt to simultaneously solve for target variables and sensor systematic biases, and most of them achieve this via augmented state Kalman filter with the augmented state vector combining the target states and sensor uncertainty. References are accordingly organized by type, discussed, and annotated. Related issues of sensor registration are concerned including the non-unique detection probability, the asynchronous sensor measurements, the observability of registration problem, the relative registration and absolute registration, and the performance bounds of the estimator of the registration errors. The developed techniques for solving the problems are summarized respectively. The paper is concluded with a brief summary and some thoughts on the future trends and research directions. [ABSTRACT FROM AUTHOR]

In recent years, sensors are often deployed to sense the target environment. Besides the sensed environmental information, sensor's position information itself is very important in most cases. With the increasing number of sensors, automatic sensor localization becomes necessary. For accurately localizing sensors, line of sight between nodes and beacons is often required. However, in many cases, it is very difficult to ensure that every beacon has the line of sight to a target sensor node. In this paper, a non-line-of-sight beacon identification approach is proposed. With which, the beacons that have no line of sight to a target sensor can be found out and then ruled out, thus the final localization result can be rectified and the accuracy can be improved. Simulations are conducted, and results show that non-line-of-sight beacons can be identified effectively. The proposed approach will be helpful in the real sensor localization in sensor networks, especially for the systems that beacons are sparsely deployed. [ABSTRACT FROM AUTHOR]

In order to reduce the location estimation error in wireless sensor network (WSN), a localization algorithm is proposed combining sliding-mode and spring-relaxation-like techniques for wireless sensor networks in this paper. Our proposed method takes advantage of the spring-relaxation technique. The overall accuracy of the location estimations is improved by sliding-mode technique. The convergence of the proposed algorithm is proved using the convergence conditions of discrete sliding-mode. Moreover, it requires only a few beacons with known locations to compute the location estimations of all sensors. Simulation examples demonstrate the overall accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

If data have the same value frequently in a data-centric storage sensor network, then the load is concentrated on a specific sensor node and the node consumes energy rapidly. In addition, if the sensor network is expanded, the routing distance to the target sensor node becomes longer in data storing and query processing, and this increases the communication cost of the sensor network. This paper proposes a nonuniform network split(NUNS) method that distributes the load among sensor nodes in data-centric storage sensor networks and efficiently reduces the communication cost of expanding sensor networks. NUNS splits a sensor network into partitions of nonuniform sizes in a way of minimizing the difference in the number of sensor nodes and in the size of partitions, and it stores data occurring in each partition in the sensor nodes of the partition. In addition, NUNS splits each partition into zones of nonuniform sizes as many as the number of sensor nodes in the partition in a way of minimizing the difference in the size of the split zones and assigns each zone to the processing area of each sensor node. Finally, we performed various performance evaluations and proved the superiority of NUNS to existing methods. [ABSTRACT FROM AUTHOR]

Target tracking is an important application of wireless sensor networks where energy conservation plays an important role. In this paper, we propose an energy-efficient sensor activation protocol based on predicted region technique, called predicted region sensor activation algorithm (PRSA). The proposed algorithm predicts the moving region of target in the next time interval instead of predicting the accurate position, by analyzing current location and velocity of the target. We take these nodes within the predicted region as waiting-activation nodes and establish activation strategy. The fewest essential number of sensor nodes within the predicted region will be activated to monitor the target. Thus, the number of nodes that was involved in tracking the target will be decreased to save energy and prolong the network's operational lifetime. The simulation results demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Previous research demonstrated that inferential sensors-based control technology can significantly improve the energy efficiency of space heating systems. However, the performance strongly relies on the accuracy and robustness of the dynamic model upon which the inferential model is built. Traditional methods, such as simplified physical model, adaptive neurofuzzy inferential sensor- (ANFIS-) based model, were developed and tested in this research. In attempt to improve both the accuracy and robustness of inferential model, this study aims to investigate how to improve the performance of inferential sensors using physical-rules-based ANFIS in prediction of the hydraulic system temperature in order to adapt the good power needed in the dwellings. This paper presents the structure of this innovative method. The performance is tested using experimental data and is compared with that of previous methods using three performance measures: RMSE, RMS, and R 2 . The results show that the physical-rule-based ANFIS inferential model is more accurate and robust. The impact of this improvement on the overall control performance is also discussed. [ABSTRACT FROM AUTHOR]

This paper proposes a scheme to enhance localization in terms of accuracy and transmission overhead in wireless sensor networks. This scheme starts from a basic anchor-node-based distributed localization (ADL) using grid scan with the information of anchor nodes within two-hop distance. Even though the localization accuracy of ADL is higher than that of previous schemes (e.g., DRLS), estimation error can be propagated when the ratio of anchor nodes is low. Thus, after each normal node estimates the initial position with ADL, it checks whether the position needs to be corrected because of the insufficient anchors within two-hop distance, that is, the node is in sparse anchor area. If correction needs, the initial position is repositioned using hop progress by the information of anchor nodes located several hops away so that error propagation is reduced (REP); the hop progress is an estimated hop distance using probability based on the density of sensor nodes. Results via in-depth simulation show that ADL has about 12% higher localization accuracy and about 10% lower message transmission cost than DRLS. In addition, the localization accuracy of ADL with REP is about 30% higher than that of DRLS, even though message transmission cost is increased. [ABSTRACT FROM AUTHOR]

Cyber-Physical System (CPS) is an integration of distributed sensor networks with computational devices. CPS claims many promising applications, such as traffic observation, battlefield surveillance, and sensor-network-based monitoring. One important topic in CPS research is about the atypical event analysis, that is, retrieving the events from massive sensor data and analyzing them with spatial, temporal, and other multidimensional information. Many traditional methods are not feasible for such analysis since they cannot describe the complex atypical events. In this paper, we propose a novel model of atypical cluster to effectively represent such events and efficiently retrieve them from massive data. The basic cluster is designed to summarize an individual event, and the macrocluster is used to integrate the information from multiple events. To facilitate scalable, flexible, and online analysis, the atypical cube is constructed, and a guided clustering algorithm is proposed to retrieve significant clusters in an efficient manner. We conduct experiments on real sensor datasets with the size of more than 50 GB; the results show that the proposed method can provide more accurate information with only 15% to 20% time cost of the baselines. [ABSTRACT FROM AUTHOR]

We examine the problem of designing the encoding and control policies of a linear stochastic control system, where the communication channel between the plant state observer (sensor) and the controller is a lossy wireless channel that is constrained in terms of transmit power and bandwidth. For a first-order ARMA modeled plant with Gaussian statistics, when there are two sensors observing the plant, nonlinear encoding is shown to result in smaller cost at time instant T = 1 compared to the linear schemes, if transmissions are carried out over parallel Gaussian independent channels. In this paper, optimal linear coding schemes for the case of multiple sensors are examined. They are shown to minimize the control cost at the infinite time horizon, when the wireless channel is accessed using time division multiplexing. Our analysis is carried out for when separation between the state estimation and control is possible, and the optimal steady state control law is certainty equivalent. The distortion lower bound for estimating the plant state is derived, along with the necessary conditions on the transmit power that minimize the steady state control cost. We also propose a linear scheme that reaches the distortion bound asymptotically under relaxed conditions. [ABSTRACT FROM AUTHOR]

Volunteer forwarding, as an emerging routing idea for large scale, location-aware wireless sensor networks, has recently received significant attention. However, several critical research issues raised by volunteer forwarding, including communication collisions, communication voids, and time-critical routing, have not been well addressed by the existing work. In this paper, we propose a priority-based stateless geo-routing (PSGR) protocol that addresses these issues. Based on PSGR, sensor nodes are able to locally determine their priority to serve as the next relay node using dynamically estimated network density. This effectively suppresses potential communication collisions without prolonging routing delays. PSGR also overcomes the communication void problem using two alternative stateless schemes, rebroadcast and bypass. Meanwhile, PSGR supports routing of time-critical packets with different deadline requirements at no extra communication cost. Additionally, we analyze the energy consumption and the delivery rate of PSGR as functions of the transmission range. Finally, an extensive performance evaluation has been conducted to compare PSGR with competing protocols, including GeRaf, IGF, GPSR, flooding, and MSPEED. Simulation results show that PSGR exhibits superior performance in terms of energy consumption, routing latency, and delivery rate, and soundly outperforms all of the compared protocols. [ABSTRACT FROM AUTHOR]

In radio frequency identification (RFID) systems, the detection range and read rates will suffer from interference among high power reading devices. This problem grows severely and degrades system performance in dense RFID networks. Consequently, medium access protocols (MAC) protocols are needed for such networks to assess and provide access to the channel so that tags can be read accurately. In this paper, we investigate a suite of feasible power control schemes to ensure overall coverage area of the system while maintaining a desired read rate. The power control scheme and MAC protocol dynamically adjusts the RFID reader power output in response to the interference level seen during tag reading and acceptable signal-to-noise ratio (SNR). We present novel distributed adaptive power control (DAPC) and probabilistic power control (PPC) as two possible solutions. A suitable back off scheme is also added with DAPC to improve coverage. Both the methodology and implementation of the schemes are presented, simulated, compared, and discussed for further work. [ABSTRACT FROM AUTHOR]

In general, wireless sensor networks have a certain degree of spatial redundancy, which means that a high number of nodes can sense the same event at the same time. This redundancy permits to simplify both MAC protocol and the transport of sensed data. In particular, in this paper, we review a widely accepted transport technique which makes use of the event-reliability concept. A system implementing this technique is essentially a control system, where the controlled variables are the reporting rates of sensor nodes and the control variable is a function of the perceived event reliability at the sink node. As control system, we are interested in stable operating points. If we respect the capacity limit of the network, such stable points exist. However, if we take into account also the irregularities of radio links, well documented in recent measurements on real sensors testbeds, possible unstable states may arise. Here, we study this problem by means of simulation of a wireless sensor network under the assumption of two simplified versions of the radio model. We found that indeed the routing protocols should be carefully engineered in order to support event reliability based techniques. [ABSTRACT FROM AUTHOR]

Recent wireless microsensor network protocols provide more flexible leverage to the applications with dynamically changing topology, but they should be designed to overcome energy constraints, the bandwidth limit, and system latency. Thus, microsensor network protocols should be effective both in energy and in latency. In addition, they should be evaluated through designated tools at each level of networking characteristics. This paper proposes a new Timeout-based Information Forwarding (TIF) protocol for wireless sensor networks. It uses a relatively simple logic to forward the data packet with multi-hop fashion to reduce the overall network energy consumption. The TIF protocol has been implemented into a network evaluation tool, called TIE/MEMS, and provides a design strategy for distributed wireless sensor network systems needed for various emerging applications. The simulated results show that the TIF protocol has low energy consumption and provides design guidelines between energy consumption and latency according to the number of hops by adjusting weight values in the timeout function. [ABSTRACT FROM AUTHOR]

In this paper, we utilize clustering to organize wireless sensors into an energy-efficient hierarchy. We propose a Medium-contention based Energy-efficient DIstributed Clustering (MEDIC) scheme, through which sensors self-organize themselves into energy-efficient clusters by bidding for cluster headship. This scheme is based on a new criterion that can be used by each sensor node to make a distributed decision on whether electing to be a cluster head or a non-head member, which is a fully distributed approach. Although MEDIC uses only local information, it achieves better performance in terms of effective lifetime and its Data/Energy Ratio is 25% higher than native LEACH (Low-Energy Adaptive Clustering Hierarchy), which relies on other routing algorithms to access global information. A complementary exponential data correlation model is also introduced to simulate different data aggregation effect. [ABSTRACT FROM AUTHOR]

The scale and functional complexity of future-generation wireless sensor networks will call for a non-homogeneous architecture, in which different sensors play different logical roles or functions, or have different physical capabilities in terms of energy, computing power, or network bandwidth. When sensors of the same group need to communicate with each other, their communications often have to pass through other sensors, thus forming an overlay on top of the wireless sensor network. The topology of the overlay is critical. It must have a low diameter to reduce the communication latency between those sensors. It also needs to avoid using other sensors for relaying the communications as much as possible, so as to preserve the energy of other sensors. In this paper, we propose a distributed overlay formation protocol taking account of the above factors. Through simulation, we compare our protocol with two overlay formation protocols, one that generates a fully connected topology and the other a minimum spanning tree. The results show that our protocol can achieve better performance both in message latency and energy consumption. [ABSTRACT FROM AUTHOR]

In the era in which activities performed by mobile users are tracked through various sensing mechanisms, the movement data collected through these sensors is submitted into a data mining algorithm in order to determine the movement pattern. The movement pattern refers to the pattern that mobile users generally take to move from one base location to another base location through multiple intermediate locations. This paper provides a proposal and case study on how the movement pattern can be extracted from mobile users through transforming the user movement database to the location movement database and subsequently transferred to an algorithm Apriori-like movement pattern (AMP) and movement tree (M-tree). The result is a list of sequences in which mobile users frequently go through that which satisfies min-support and min-confidence. The result of this movement pattern mining exercise opens up a new future for the prediction of the movement for the individual mobile user. [ABSTRACT FROM AUTHOR]

Wireless sensor nodes can be mobile within a chosen area and communicate with neighboring nodes in the bounds of protocol limits. Since communications among all network components in sensor networks are wireless, a peer-to-peer protocol is employed between two nodes. Among many concerns about design of sensor networks are growing bandwidth demands, speed of information retrieval, and transporting bytes over the wireless networks to provide a quality service for the diverse requirements of the users, such as signal processing or multimedia applications. Although traditional routing protocols ignore power management issues for sensor networks, design and implementation of an efficient energy based routing is in the core interest. In this paper, we discuss the current power management protocols, and propose an energy restrained information dissemination scheme. Experimental analysis and comparison with related work show that using the proposed scheme we can save substantial energy as compared to the prior methods. [ABSTRACT FROM AUTHOR]

In this paper, a distributed approach to radio scene analysis is considered. A Wireless Sensor Network, composed by Software Defined and Cognitive terminals, is used to classify air interfaces present in the radio scene. Two modes, namely Frequency Hopping Code Division Multiple Access and Direct Sequence Code Division Multiple Access, are identified, employing a signal processing technique. Time Frequency analysis, and a distributed decision theory. Advantages given by distributed detection are used to improve the performance of a Mode Identification module. Results in terms of error probability are obtained by modelling the probability density function of considered features as Asymmetric Generalized and Generalized Gaussian functions. [ABSTRACT FROM AUTHOR]

Recent advances in technology have made it possible to build surveillance systems using many low-cost sensor nodes with limited computation and communication capabilities. Due to a potentially large number of nodes deployed, node failures are inevitable and can render a surveillance system that has degraded detection performances. The exposure metric has been proposed earlier to assess the quality of a surveillance system based on the detection performances. In this paper, we characterize the vulnerability of a system in terms of its exposure with respect to the number of faulty nodes and their combinations. Specifically, we assess the exposure of a surveillance network subject to a given number of faulty nodes, and identify the worst-case fault combination for both an idling target and a traversing target. For an idling target, the worst-case fault combination and exposure is analytically identified. For a traversing target, a genetic algorithm based approach is proposed to derive a near worst-case fault combination, and extensive simulation results are presented to show the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

Sensor networks based on the de facto standard Berkeley TinyOS platform are changing the way environmental information is collected in the field. One such network has been designed, deployed, and tested in order to determine where ephemeral streams (small, temporary channels of runoff) form during precipitation events. This small, proof-of-concept test network was designed around a generic nondeterministic finite state machine component, which was built to be re-used in later environmental sensor network applications. A simplistic broadcast mechanism was devised to provide collective sampling interval changes to adapt to environmental conditions. In this paper, the design and testing of the ephemeral stream detection network are discussed, along with design features that can be re-used in later applications. Improvements for a later deployment of a larger, operational ephemeral stream detection network are also described. [ABSTRACT FROM AUTHOR]