Surveillance Wireless Sensor Networks Research Articles

Energy-efficient Data Aggregation in Low-power Wireless Networks with Sensors of Discrete Transmission Ranges: A Mathematical Framework for Network Design

The advancements in sensor technology and the evolution of new generation technologies such as the Internet of Things have led to extensive deployment of low-power wireless sensor networks for various surveillance and monitoring applications. The volume and velocity of the data generated by a large number of sensors and monitors used in such applications are huge. The harnessing of such big data is critical to the real-time control of underlying real-world processes. Future generation networks favor the deployment of sensors with different discrete transmission ranges. Such multiple transmission ranges introduce different connectivity constraints in the network. Advanced strategies are under investigation for designing energy-efficient data aggregation schemes in such connectivity-constrained networks. To aid such works, we introduce a mathematical framework that captures the salient features of low-power networks with sensors of multiple transmission ranges. The proposed framework can serve as a baseline platform to investigate different networking problems in such systems. Further, we consider a cluster-based multihop network with fixed intra-cluster and inter-cluster transmission ranges and address the problem of designing an optimal network configuration for minimizing the data transmission in the network. We model the problem as an integer linear program, which can be applied only to networks of small sizes because of the hardness of the problem. To address the problem in large-scale networks, we design a polynomial-time approximation method using the proposed mathematical framework. The performance of the proposed methods is evaluated under compression schemes based on compressive sensing.

Residual energy-based clustering in UAV-aided wireless sensor networks for surveillance and monitoring applications

Aim: Unmanned aerial vehicle (UAV)-aided wireless sensor networks (WSNs) are effectively used for surveillance, monitoring, and rescue applications in military and commercial domains. In UAV-aided WSNs (UWSNs), efficient data gathered from sensor nodes are desired to enhance network performance. However, communication between UAV and sensor nodes is challenging due to the high mobility of the UAV and a large number of sensor nodes. Clustering in UWSNs limits the number of sensor nodes communicating with the UAV, i.e., only the cluster head in a cluster can transmit the sensed data to the UAV, which reduces collision probability. Methods: In this paper, we propose a residual energy-based clustering algorithm for sensor-to-UAV communication in UWSNs. The cluster size and the number of sensor nodes in a cluster are determined on the basis of the residual energy of the sensor nodes. The performance of the proposed algorithm is evaluated by using the MATLAB simulator and then compared with that of the conventional clustering algorithm. Results: According to our extensive simulation results, the proposed clustering scheme significantly outperforms the conventional one in terms of network lifetime and data delivery ratio. Conclusion: Hence, through our studies and simulations, it can be assured that the network lifetime of UWSNs can be prolonged and the throughput of the network can also be elevated by controlling the early death of sensor nodes due to the uneven energy consumptions. We will come up with further analysis and validation of our work in the future.

Broker-Based Nodes Recharging Scheme for Surveillance Wireless Rechargeable Sensor Networks

In Surveillance Wireless Sensor Networks (SWSN), the nodes are distributed at the borders to detect unauthorized intrusions. In such applications, as the nodes are usually equipped with limited batteries and the network area is harsh to be accessible for humans, energy efficiency is considered as one of the main issues in designing the sensor networks. In the last years, Wireless Rechargeable Sensor Networks (WRSN) provides valuable insights into solving the energy constraint problem in WSNs. In a WRSN, Wireless Mobile Chargers (WMC) are responsible to recharge the batteries of the sensor nodes in order to enhance the operation time of the network. In most of the previous WRSN based schemes, the WMCs recharge the nodes singly and directly, which results in increasing the travel time of WMC and waiting time of sensor nodes. In addition, despite of using WMC, the permanent network lifetime has not been addressed in most of the previous schemes. Therefore, to overcome the limitations of existing literature, this research work focuses on the design and development of Broker-based Nodes Recharging Scheme (BNRS) which significantly contributes to improved lifetime and performance of SWSN. In the proposed scheme, power banks are employed as brokers between sensor nodes and WMC. The main duty of a power bank is to receive energy from WMC and transfer to the sensor nodes. Based on the simulation experiments the proposed BNRS achieves the permanent network operation which results in increasing security in the border of countries.

Energy-aware scheduling for information fusion in wireless sensor network surveillance

Effective energy control while maintaining reliable monitoring performance becomes a key issue in wireless sensor networks (WSNs) based surveillance applications. While importance difference of surveillance zone, limited energy and dynamic network topology pose great challenges to surveillance performance. It is necessary to adjust sensor nodes' awakening frequency dynamically for information fusion. Thus an energy-aware scheduling with quality guarantee method named ESQG is proposed in this paper which considers sensor nodes' residual energy, different importance degrees of the surveillance zone and network topology comprehensively. It first uses a Voronoi diagram to determine the effective scope of each sensor node and then calculates node importance according to its residual energy and the importance degree of the effective scope. Then ESQG utilizes the importance of individual sensing scope and current forwarding costs to further compute node importance and awakening frequency for information fusion. In this way, ESQG can dynamically adapts each nodes awakening frequency to its dynamic network topology and importance degree of each individual sensing scope. The nodes are then turned on stochasticlly via the node awakening probability and node importance based information fusion is conducted for target detection. Besides, an adaptive process of perception factor C is proposed to match actual situation, and automatically change according to the detected data. Experiments results demonstrate that the proposed method ESQG can reduce the number of awakening nodes to a large extent while maintaining high reliability via information fusion.

Border Surveillance With WSN Systems in a Distributed Manner

Border surveillance is an application of wireless sensor networks (WSNs) and it is mainly used for security purpose. The present issue of implementing this application is a barrier coverage in WSNs. Due to energy constraints, minimizing energy consumption of sensors is a critical challenge. This paper presents a new distributed approach to the border surveillance in WSNs in order to maximize the number of barriers and minimize energy consumption. We use a learning automata scheme in our approach to solve this problem. We present distributed border surveillance (DBS) algorithm that aims to find the minimum possible number of nodes in each barrier to monitor the network borders. In DBS approach, learning automaton assists to find the best nodes to assure barrier coverage at any moment. The algorithm was implemented through computer simulations and compared to the existing competing algorithms. The simulation results show that the DBS scheme outperformed some state-of-art barrier-coverage algorithms.

Exploiting Correlation for Confident Sensing in Fusion-Based Wireless Sensor Networks

Wireless sensor networks for obstacle detection, environment monitoring, and military surveillance have stringent accuracy requirements for target monitoring and demand long system lifetime. We define meeting such user requirements as confident sensing. In order to achieve confident sensing and energy balance among sensors, it is necessary to cluster sensors properly. But in most traditional approaches, such as sensor-target distance based methods, users’ accuracy requirements on sensor correlation can hardly be fulfilled. Accordingly, we first make quantitative study on relationship between sensor-target distance and sensing accuracy as well as sensor correlation among the heterogeneous or homogeneous sensors. Their impacts on sensor collaboration provide guideline for confident sensing. Then, in order to meet user sensing accuracy requirements and obtain energy balance among sensors, we propose a collaborative sensor selection method named CSdT. Based on sensor-target distance and sensor correlation, CSdT scheme clusters right sensors in a distributed way. Besides, from perspective of mutual information, we explain the role of such correlation and sensor-target distance on confident sensing. Finally, we conduct extensive experiments on real data to validate and evaluate CSdT. Experimental results demonstrate the superior performance of our method over existing solutions in terms of meeting users’ requirements and obtaining energy balance.

A Lightweight Routing Protocol for aWireless Video Surveillance Platform: Implementation, Experiments and Perspectives

Recently, a new application of wireless sensor networks has emerged and it consists on Multimedia Surveillance Wireless Sensor Networks (MSWSNs). This application involves interconnected wireless video sensors capable of processing, sending, and receiving data. The first step in this work is to setu

Optimization of Deployment Quality for Intrusion Detection in Surveillance Wireless Sensor Network

The volatile nature of wireless sensor network promise a lot of scopes in diverse disciplines. It is highly applicable in hostile environment, where nodes can be only deployed randomly, without having any predetermined statistical distribution. The fundamental challenges arise to provide maximum coverage and connectivity in hostile vicinity. A detailed analysis of node density, is required to achieve appropriate coverage. The problem of coverage is solved by optimum distribution scenario and sensing range of sensor nodes. Our goal is to achieve promising deployment quality and detection probability, by mapping the problem of intruder detection with geometric intersection domain, a tool from integral geometry and geometric probability. The proposed deployment quality analysis computes number of sensor nodes, required to attain optimum detection performance.

Fusion-based surveillance WSN deployment using Dempster–Shafer theory

In mission-critical Wireless Sensor Networks surveillance applications, a high detection rate coupled with a low false alarm rate is essential. Additionally, fusion methods can be employed with the hope that aggregation of uncertain information from multiple sensors enhances the quality of surveillance provided by the network. This paper investigates the following fundamental problem: what is the best way to deploy a finite number of unreliable sensors characterized by uncertain readings in order to satisfy the user detection requirements. Unlike prior efforts that rely on simple fusion schemes, we use the Dempster–Shafer theory to define a generic evidence fusion scheme that captures several characteristics of real-world applications. The fusion-based uncertainty-aware sensor networks deployment problem is formulated as a binary non-linear and non-convex optimization problem that is NP-hard, and an efficient heuristic using genetic algorithms is investigated. The effectiveness and efficiency of the proposed approach are evaluated using both simulations and experiments. The obtained results demonstrate the appropriateness of the evidence fusion model that considers in a meaningful way the information on the quality of sensors decisions as well as the reliability of these sensors along with their uncertain and imprecise decisions. Also, the proposed approach outperforms state-of-the-art deployment strategies.

Automated Negotiation for Resource Assignment in Wireless Surveillance Sensor Networks.

Due to the low cost of CMOS IP-based cameras, wireless surveillance sensor networks have emerged as a new application of sensor networks able to monitor public or private areas or even country borders. Since these networks are bandwidth intensive and the radioelectric spectrum is limited, especially in unlicensed bands, it is mandatory to assign frequency channels in a smart manner. In this work, we propose the application of automated negotiation techniques for frequency assignment. Results show that these techniques are very suitable for the problem, being able to obtain the best solutions among the techniques with which we have compared them.

A New Method for Prolonging Network Lifetime and Maintaining the Connectivity in Wireless Sensor Network Through Controlling the Transmission Power

Energy preservation constitutes a very critical challenge in wireless sensor network surveillance applications. On one hand, transmitting data by using additional transmission power is among the biggest sources of energy consumption. On the other hand, using a small transmission power degrades the connectivity between nodes. In this paper, a Distributed transmission Power Control Method (DPCM) to minimize the consumed energy is proposed. Moreover, it aims to keep a good connectivity between nodes. These purposes are accomplished by adjusting, dynamically, the transmission power taking into account the connectivity information of the neighbors at one and two-hop. Simulation experiences are carried out to measure the performance improvements of the presented method in both static and mobile networks by using Castalia simulator. According to the obtained results, the authors' method minimizes the consumed energy without penalizing the connectivity between nodes compared to DPCS and farthest neighbor methods. In addition, DPCM achieves good performances in spite of node mobility.

Probabilistic Methods based on Energy's Threshold in Switching Mode of Mobile Wireless Sensor for Surveillance Application

The continuity running of the sensor network on limited energy resources constitutes a real challenge for researchers. In fact, many schemes have been proposed to economize the wasted energy of this latter. However, most of them are proposed for static network. In this article we propose threshold formula and we present two probabilistic methods to reduce the energy consumption and at the same time improve the latency in mobile wireless sensor network surveillance applications, based ZebraNet. The first is PMFT for Probabilistic method with fixed threshold. The second is PMVT for probabilistic method with varying threshold. PMFT defines a fixed threshold for all nodes, which is calculated using Poisson distribution. Whereas, PMVT uses a variant threshold for each node with taking into account the mobility pattern and the residual energy of each sensor. The experimental evaluation shows that our methods outperform conventional methods, in terms of consumed energy and end to end delay in spite of the sensors mobility.

Detection quality of border surveillance wireless sensor networks in the existence of trespassers’ favorite paths

The performance of a surveillance wireless sensor network is generally measured with its detection capability within a monitored zone. This capability is affected by various parameters such as the sensor count, the sensor range, the area width and the target mobility model. In real life examples it is observed that intruders prefer some favorite regions because of their geographical advantages within a monitored border area. These regions, which bounds the randomly chosen trespassing paths, are generally in close vicinity. In this paper, we introduce the notion of trespassers’ favorite paths (TFP) and provide a tool that can be used to forecast the detection probability of a surveillance network in such a network with TFPs. The detection probability is reduced to the geometric line intersection problem using bijection and the boundary conditions of intruder trajectories for the border area and the favorite region are determined. The line intersection problem is solved using tools from the integral geometry and geometric probability. The effect of the favorable region on the detection quality under different conditions is calculated using probabilistic models. The accuracy of the proposed quality metric is validated by both analytical methods and simulation results. Furthermore, the importance of the intrusion model on the network performance is presented using realistic scenarios. It is shown that the existence of favorite paths has significant impact on the detection quality of the network. The proposed detection quality metric provides analytical tools suitable for both real life and simulation scenarios to the network designers to forecast and optimize the expected detection performance, and is computationally inexpensive compared to both simulation based and distributed quality measurements.

Towards an optimal lifetime in heterogeneous surveillance wireless sensor networks

In this article, we study the coverage problem for heterogeneous wireless sensor networks where different targets need to be covered (sensed) by different types of wireless sensors running at possibly different sampling rates as well as different initial energy reserve. The objective is to maximize network lifetime while fulfilling diversified coverage constraints, i.e., different targets may require different sensing quality in terms of the number of transducers, sampling rate, sensing data rate, etc. The problem is particularly challenging since we need to consider both connectivity and routing requirements. To conquer this combinational complexity, we formulate a lifetime maximization problem, which is general and allows unprecedented diversity in coverage requirements, sampling rates, transmission energy consumption models, communication ranges, and target sensing ranges. Furthermore, to efficiently solve the optimization problem, we propose a column generation based approach, where a column corresponding to a feasible solution; our idea is to find a column with steepest ascent in lifetime, based on which we iteratively search for the solution of the maximum lifetime problem. To speed up the convergence rate, we generate an initial solution through a novel random selection algorithm. Through extensive simulations, we systematically study the effect of sampling rates, transmission energy consumption models, communication ranges, and sensing ranges on the lifetime. Several interesting insights have been revealed.

A Taxonomy of Agent Technologies for Ubiquitous Computing Environments

The design, development and deployment of Mobile Agent (MA) systems for high-level inference and surveillance in wireless sensor networks and RFID systems have drawn increasing attention in the past decade. To answer how the state-of-the-art of MA in a wide range of ubiquitous and sensor environments is, this paper investigates the current progress of MA. It proposes a taxonomy, by which MA systems in ubiquitous computing environments are decomposed and discussed. Then, this paper provides insights into the strengths and weaknesses of existing efforts. Finally, it presents a series of solutions from the viewpoint of various roles of MA in ubiquitous environments and situations.

Transmitting-Mode Time Reversal Imaging Using MUSIC Algorithm for Surveillance in Wireless Sensor Network

The electromagnetic time reversal (TR) detection and imaging using multiple signal classification (MUSIC) is extended to the Maxwell equations problems with the transmitting-mode configurations, where the transmitter and receiver arrays are bistatic and the arrays elements are arbitrarily distributed. Based on this type of setup, the multistatic response matrix is derived in detail for target-scattering by relatively small anisotropic spheres located in the imaging domain. Then the electromagnetic transmitting-mode MUSIC algorithm is proposed by defining the pseudo-spectrum deduced from the Maxwell equations. By such extension, following advantages are achieved: a) leading to more accurate location and higher imaging resolution because the noncoincident arrays actually increase the effective aperture of the array; b) making the algorithm more flexible and practical; c) enlarging the coverage area of the detection system due to the reciprocal mapping between the transmitter and receiver spaces; and d) overcoming one special problem that the echo-mode encounters when one target is atop another one in the upright direction of the transceiver antenna array even they are far-separated. Based on these advantages, we have numerically discussed typical applications of the proposed method for surveillance in wireless sensor network. Through examples, the validity, the improvement, and the extended potential of the electromagnetic transmitting-mode time reversal MUSIC method are verified.

VIGILANT + : mission objective interest groups for wireless sensor network surveillance applications

A system termed VIGILANT+ is outlined, which utilises situation awareness for the purposes of enabling distributed, autonomic, sensor management, so that savings on consumption of network resources can be achieved. VIGILANT+ is a novel proposition allowing deployed, unattended, wireless sensor nodes to self-organise into dynamic groups and self-manage their transmissions efficiently, according to a current common mission objective. First, a distributed situation assessment system named PORTENT model detects and characterises potential situations occurring within an uncertain environment, using the metric, quality of surveillance information. Secondly, a Bayesian belief network is utilised to understand and analyse the significance associated with the potential situation, primarily to enable deployed sensors to self-organise and assign themselves to mission objectives autonomously. Thirdly, a system is introduced for distributed autonomic transmission control, which enables the efficient management of sensor network resource consumption. Simulations have been undertaken to verify the integrated VIGILANT+ concepts and to demonstrate the effectiveness of the proposed approach in improving network efficiency, without compromising the presentation of mission surveillance utility.

Networking and application interface technology for wireless sensor network surveillance and monitoring

Distributed unattended ground sensor networks used in battlefield surveillance and monitoring missions, have proven to be valuable in providing a tactical information advantage required for command and control, intelligence, surveillance, and reconnaissance planning. Operational effectiveness for surveillance missions can be enhanced further through network centric capability, where distributed UGS networks have the ability to perform surveillance operations autonomously. NCC operation can be enhanced through UGSs having the ability to evaluate their awareness of the current joint surveillance environment, in order to provide the necessary adaptation to dynamic changes. NCC can also provide an advantage for UGS networks to self-manage their limited operational resources efficiently, according to mission objective priority. In this article, we present a crosslayer approach and highlight techniques that have potential to enable NCC operation within a mission-orientated UGS surveillance setting.

Sink placement on a 3D terrain for border surveillance in wireless sensor networks

With their distributed nature and redundant operation capability, wireless sensor networks are very suitable for border surveillance scenarios that track intruders trying to breach to a safe side. In such scenarios, keeping the operation going on for as long as possible is the most important aspect of the network. We propose that by placing sink at a carefully selected coordinate will results in a longer living network. We also place restrictions on the candidate locations so that the sensing quality of the network is above a useful predetermined value and the sink is placed in a relatively safe location to avoid destruction. In order to find the suitable coordinates we propose a modified lifetime metric which takes quality and safety measures into account. We also propose a genetic algorithm which uses a discrete event simulator-in-the-loop over a three dimensional terrain to find locations for the sink that fits the given quality and safety restrictions. Using a three dimensional underlying terrain makes the proposed approach more realistic. The results obtained for various sensor network scenarios indicate that the proposed algorithm can find locations that increase the lifetime by also considering the sensing quality and safety.

Secure Network Recovery from Base Station Failure of Surveillance WSN in Hostile Environment

Securing surveillance wireless sensor networks (WSNs) in hostile environments such as borders, perimeters and battlefields during Base Station (BS) failure is challenging. Surveillance WSNs are highly vulnerable to BS failure. The attackers can render the network useless by only destroying the BS as the needed efforts to destroy the BS is much less than that is needed to destroy the network. This attack scenario will give the attackers the best chance to compromise many legitimate nodes. Previous works have tackled BS failure by deploying a mobile BS or by using multiple BSs. Despite the best electronic countermeasures, intrusion tolerance and anti-traffic analysis strategies to protect the BSs, an adversary still can destroy them. This paper proposes a novel security architecture called Surveillance Security (SurvSec) for secure and reliable network recovery from single BS failure of surveillance WSN with single BS. SurvSec relies on a set of sensor nodes serve as Security Managers for management and storage of the security related data of all sensor nodes. SurvSec security architecture provides methodology for choosing and changing the security managers of the surveillance WSN. SurvSec has four components: (1) Sensor nodes serve as Security Managers, (2) Data Storage System, (3) Data Recovery System, (4) Security for the Data Storage System. Furthermore, both the frame format of the stored data is carefully built and the security threats are encoded to allow minimum overheads for SurvSec security architecture. In this paper, we provide detailed specifications of SurvSec security architecture along with its security system for secure and reliable network recovery from single BS failure. We evaluate our designed security architecture for reliable network recovery from BS failure. Our evaluation shows that the proposed new security architecture can meet all the desiredspecifications and our analysis shows that the provided Security Managers are capable of network recovery from BS failure.