http://www.eecs.ucf.edu/~dcm/Teaching/COT4810-Spring2011/Literature/SensorNetworksSurvey.pdf

Wireless sensor networks: a survey

In this paper, we address the issues of maintaining sensing coverage and connectivity by keeping a minimum number of sensor nodes in the active mode in wireless sensor networks. We investigate the relationship between coverage and connectivity by solving the following two sub-problems. First, we prove that if the radio range is at least twice the sensing range, complete coverage of a convex area implies connectivity among the working set of nodes. Second, we derive, under the ideal case in which node density is sufficiently high, a set of optimality conditions under which a subset of working sensor nodes can be chosen for complete coverage. Based on the optimality conditions, we then devise a decentralized density control algorithm, Optimal Geographical Density Control (OGDC), for density control in large scale sensor networks. The OGDC algorithm is fully localized and can maintain coverage as well as connectivity, regardless of the relationship between the radio range and the sensing range. Ns-2 simulations show that OGDC outperforms existing density control algorithms [25, 26, 29] with respect to the number of working nodes needed and network lifetime (with up to 50% improvement), and achieves almost the same coverage as the algorithm with the best result.

/pdf/maintaining-sensing-coverage-and-connectivity-in-large-51bozdz8j8.pdf

Maintaining Sensing Coverage and Connectivity in Large Sensor Networks.

One fundamental issue in sensor networks is the coverage problem, which reflects how well a sensor network is monitored or tracked by sensors. In this paper, we formulate this problem as a decision problem, whose goal is to determine whether every point in the service area of the sensor network is covered by at least k sensors, where k is a predefined value. The sensing ranges of sensors can be unit disks or non-unit disks. We present polynomial-time algorithms, in terms of the number of sensors, that can be easily translated to distributed protocols. The result is a generalization of some earlier results where only k=1 is assumed. Applications of the result include: (i) positioning applications, (ii) situations which require stronger environmental monitoring capability, and (iii) scenarios which impose more stringent fault-tolerant capability.

/pdf/the-coverage-problem-in-a-wireless-sensor-network-4ssl5sybyb.pdf

The coverage problem in a wireless sensor network

A critical aspect of applications with wireless sensor networks is network lifetime. Power-constrained wireless sensor networks are usable as long as they can communicate sensed data to a processing node. Sensing and communications consume energy, therefore judicious power management and sensor scheduling can effectively extend network lifetime. To cover a set of targets with known locations when ground access in the remote area is prohibited, one solution is to deploy the sensors remotely, from an aircraft. The lack of precise sensor placement is compensated by a large sensor population deployed in the drop zone, that would improve the probability of target coverage. The data collected from the sensors is sent to a central node (e.g. cluster head) for processing. In this paper we propose un efficient method to extend the sensor network life time by organizing the sensors into a maximal number of set covers that are activated successively. Only the sensors from the current active set are responsible for monitoring all targets and for transmitting the collected data, while all other nodes are in a low-energy sleep mode. By allowing sensors to participate in multiple sets, our problem formulation increases the network lifetime compared with related work [M. Cardei et al], that has the additional requirements of sensor sets being disjoint and operating equal time intervals. In this paper we model the solution as the maximum set covers problem and design two heuristics that efficiently compute the sets, using linear programming and a greedy approach. Simulation results are presented to verify our approaches.

/pdf/energy-efficient-target-coverage-in-wireless-sensor-networks-2snkcx2hjq.pdf

Energy-efficient target coverage in wireless sensor networks

Wireless Sensor Networks (WSNs) are used in many applications in military, ecological, and health-related areas These applications often include the monitoring of sensitive information such as enemy movement on the battlefield or the location of personnel in a building Security is therefore important in WSNs However, WSNs suffer from many constraints, including low computation capability, small memory, limited energy resources, susceptibility to physical capture, and the use of insecure wireless communication channels These constraints make security in WSNs a challenge In this article we present a survey of security issues in WSNs First we outline the constraints, security requirements, and attacks with their corresponding countermeasures in WSNs We then present a holistic view of security issues These issues are classified into five categories: cryptography, key management, secure routing, secure data aggregation, and intrusion detection Along the way we highlight the advantages and disadvantages of various WSN security protocols and further compare and evaluate these protocols based on each of these five categories We also point out the open research issues in each subarea and conclude with possible future research directions on security in WSNs

/pdf/a-survey-of-security-issues-in-wireless-sensor-networks-4dxn3686s1.pdf

A survey of security issues in wireless sensor networks

Wireless sensor networks have emerged recently as an effective way of monitoring remote or inhospitable physical environments. One of the major challenges in devising such networks lies in the constrained energy and computational resources available to sensor nodes. These constraints must be taken into account at all levels of the system hierarchy. The deployment of sensor nodes is the first step in establishing a sensor network. Since sensor networks contain a large number of sensor nodes, the nodes must be deployed in clusters, where the location of each particular node cannot be fully guaranteed a priori. Therefore, the number of nodes that must be deployed in order to completely cover the whole monitored area is often higher than if a deterministic procedure were used. In networks with stochastically placed nodes, activating only the necessary number of sensor nodes at any particular moment can save energy. We introduce a heuristic that selects mutually exclusive sets of sensor nodes, where the members of each of those sets together completely cover the monitored area. The intervals of activity are the same for all sets, and only one of the sets is active at any time. The experimental results demonstrate that by using only a subset of sensor nodes at each moment, we achieve a significant energy savings while fully preserving coverage.

/pdf/power-efficient-organization-of-wireless-sensor-networks-48bb9g1in3.pdf

Power efficient organization of wireless sensor networks

Networks of wireless microsensors for monitoring physical environments have emerged as an important new application area for wireless technology. Key attributes of these new types of networked systems are the severely constrained computational and energy resources, and an ad hoc operational environment. This paper is a study of the communication security aspects of these networks. Resource limitations and specific architecture of sensor networks call for customized security mechanisms. Our approach is to classify the types of data existing in sensor networks, and identify possible communication security threats according to that classification. We propose a communication security scheme where for each type of data we define a corresponding security mechanism. By employing this multitiered security architecture where each mechanism has different resource requirements, we allow for efficient resource management, which is essential for wireless sensor networks.

/pdf/on-communication-security-in-wireless-ad-hoc-sensor-networks-1n0o90aeup.pdf

On communication security in wireless ad-hoc sensor networks

Wireless sensor networks monitor the physical world by taking measurements of physical phenomena. Those measurements, and consequently the results computed from the measurements, may be significantly inaccurate. Therefore, in order to properly design and use wireless sensor networks, one must develop methods that take error sources, error propagation through optimization software, and ultimately their impact on applications, into consideration. In this paper, we focus on location discovery induced errors. We have selected location discovery as the object of our case study since essentially all sensor network computation and communication tasks are dependent on geographical node location data. First, we model the error in input parameters of the location discovery process. Then, we study the impact of errors on three selected applications: exposure, best- and worst-case coverage, and shortest path routing. Furthermore, we examine how the choice of a specific objective function optimized during the location discovery process impacts the errors in results of different applications.

https://www.cs.ucla.edu/~miodrag/papers/Slijepcevic_MCC_02.pdf

Location errors in wireless embedded sensor networks: sources, models, and effects on applications

One task in which inaccurate measurements are often used is location discovery, a process where the nodes in a network determine their locations. We have focused on location discovery as the primary target of our study since many sensor network tasks are dependent on location information. We demonstrate the benefits of location error analysis for system software and applications in wireless sensor networks. The technical highlight of our work is a statistically validated parameterized model of location errors that can be used to evaluate the impact of a location discovery algorithm on subsequent tasks. We prove that the distribution of location error can be approximated with a family of Weibull distributions. Then, we show that while performing the location discovery task, the nodes in a network can estimate the parameters of the distribution. Finally, we describe how applications can use the estimated statistical parameters to: (i) estimate the confidence intervals for their results, (ii) organize resource consumption to achieve optimal results in presence of estimated magnitude of error.

Characterization of location error in wireless sensor networks: analysis and applications

In a computational tour-de-force, this volume wipes away a host of problems related to location discovery in wireless ad-hoc sensor networks. WASNs have recognized potential in many applications that are location-dependent, yet are heavily constrained by factors such as cost and energy consumption. Their ad-hoc nature, with direct rather than mediated connections between a network of wireless devices, adds another layer of difficulty. Basing this work entirely on data-driven, coordinated algorithms, the authors aim is to present location discovery techniques that are highly accurateand which fit user criteria. The research deploys nonparametric statistical methods and relies on the concept of joint probability to construct error (including location error) models and environmental field models. It also addresses system issues such as the broadcast and scheduling of the beacon. Reporting an impressive accuracy gain of almost 17 percent, and organized in a clear, sequential manner, this book represents a stride forward in wireless localization.

Sasha Slijepcevic

Papers

Power efficient organization of wireless sensor networks

On communication security in wireless ad-hoc sensor networks

Location errors in wireless embedded sensor networks: sources, models, and effects on applications

Characterization of location error in wireless sensor networks: analysis and applications

Localization in Wireless Networks: Foundations and Applications