CHOP: Maximum Coverage Optimization and Resolve Hole Healing Problem using Sleep and Wake-up Technique for WSN

The Sensor Nodes (SN) play an important role in various hazardous applications environments such as military surveillance, forests, battlefield, etc. The Wireless Sensor Network (WSN) comprised multiple numbers of sensor nodes which are used to perform sensing the physical conditions and subsequently transmitting data to the Base Station (BS). The nodes have limited batteries. The random distribution of nodes in the hazardous areas causes overlapping of nodes and coverage hole issues in the network. The Coverage Optimization and Resolve Hole Healing (CHOP) Protocol is proposed to optimize the network's overlapping and resolve the coverage hole problem. The working phases of the proposed protocol are network initialization, formation of the cluster, Selection of Cluster Head, and sleep and wake-up phase. The issues are optimized, and maximum coverage is achieved for a specific sensing range. Using statistics and probability theory, a link is established between the radius of the node and the coverage area. The protocol used the sleep and wake phase to select optimal nodes active to achieve maximum coverage. The proposed protocol outperformed and showed improvements in the network's performance and lifetime compared to LEACH, TEEN, SEP, and DEEC protocols

Ensuring Cyber-Security in Smart Railway Surveillance with SHIELD

Modern railways feature increasingly complex embedded computing systems for surveillance, that are moving towards fully wireless smart-sensors. Those systems are aimed at monitoring system status from a physical-security viewpoint, in order to detect intrusions and other environmental anomalies. However, the same systems used for physical-security surveillance are vulnerable to cyber-security threats, since they feature distributed hardware and software architectures often interconnected by ‘open networks’, like wireless channels and the Internet. In this paper, we show how the integrated approach to Security, Privacy and Dependability (SPD) in embedded systems provided by the SHIELD framework (developed within the EU funded pSHIELD and nSHIELD research projects) can be applied to railway surveillance systems in order to measure and improve their SPD level. SHIELD implements a layered architecture (node, network, middleware and overlay) and orchestrates SPD mechanisms based on ontology models, appropriate metrics and composability. The results of prototypical application to a real-world demonstrator show the effectiveness of SHIELD and justify its practical applicability in industrial settings

Coverage issues in wireless sensor networks.

A fundamental issue in the deployment of a large scale Wireless Sensor Network (WSN) is the ability of the network to cover the region of interest. While it is important to know if the region is covered by the deployed sensor nodes, it is of even greater importance to determine the minimum number of these deployed sensors that will still guarantee coverage of the region. This issue takes on added importance as the sensor nodes have limited battery power. Redundant sensors affect the communications between nodes and cause increased energy expenditure due to packet collisions. While scheduling the activity of the nodes and designing efficient communication protocols help alleviate this problem, the key to energy efficiency and longevity of the wireless sensor network is the design of efficient techniques to determine the minimum set of sensor nodes for coverage. Currently available techniques in the literature address the problem of determining coverage by modeling the region of interest as a planar surface. Algorithms are then developed for determining point coverage, area coverage, and barrier coverage. The analysis in this thesis shows that modeling the region as a two dimensional surface is inadequate as most applications in the real world are in a three dimensional space. The extension of existing results to three dimensional regions is not a trivial task and results in inefficient deployments of the sensor networks. Further, the type of coverage desired is specific to the application and the algorithms developed must be able to address the selection of sensor nodes not only for the coverage, but also for covering the border of a region, detecting intrusion, patrolling a given border, or tracking a phenomenon in a given three dimensional space. These are very important issues facing the research community and the solution to these problems is of paramount importance to the future of wireless sensor networks. In this thesis, the coverage problem in a three dimensional space is rigorously analyzed and the minimum number of sensor nodes and their placement for complete coverage is determined. Also, given a random distribution of sensor nodes, the problem of selecting a minimum subset of sensor nodes for complete coverage is addressed. A computationally efficient algorithm is developed and implemented in a distributed fashion. Numerical simulations show that the optimized sensor network has better energy efficiency compared to the standard random deployment of sensor nodes. It is demonstrated that the optimized WSN continues to offer better coverage of the region even when the sensor nodes start to fail over time. (Abstract shortened by UMI.

QoS-Aware Energy Management and Node Scheduling Schemes for Sensor Network-Based Surveillance Applications

Recent advances in wireless technologies have led to an increased deployment of Wireless Sensor Networks (WSNs) for a plethora of diverse surveillance applications such as health, military, and environmental. However, sensor nodes in WSNs usually suffer from short device lifetime due to severe energy constraints and therefore, cannot guarantee to meet the Quality of Service (QoS) needs of various applications. This is proving to be a major hindrance to the widespread adoption of WSNs for such applications. Therefore, to extend the lifetime of WSNs, it is critical to optimize the energy usage in sensor nodes that are often deployed in remote and hostile terrains. To this effect, several energy management schemes have been proposed recently. Node scheduling is one such strategy that can prolong the lifetime of WSNs and also helps to balance the workload among the sensor nodes. In this article, we discuss on the energy management techniques of WSN with a particular emphasis on node scheduling and propose an energy management life-cycle model and an energy conservation pyramid to extend the network lifetime of WSNs. We have provided a detailed classification and evaluation of various node scheduling schemes in terms of their ability to fulfill essential QoS requirements, namely coverage, connectivity, fault tolerance, and security. We considered essential design issues such as network type, deployment pattern, sensing model in the classification process. Furthermore, we have discussed the operational characteristics of schemes with their related merits and demerits. We have compared the efficacy of a few well known graph-based scheduling schemes with suitable performance analysis graph. Finally, we study challenges in designing and implementing node scheduling schemes from a QoS perspective and outline open research problems

Automatic triangulation positioning system for wide area coverage from a fixed sensors network

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonIn a wide area that many Transmitters (TRs) operate, systems of Fixed Sensors (FS) might be used in order to detect them and find TRs position. The detection and the accurate location of a new TR entering in the area frequently can be missed if the system fails to triangulate accurately the relative readings and analyze the changes in the received data. Additionally, there are cases that a Triangulation Station Network (TSN) can detect the heading as well as the transmitter’s position wrong. This thesis presents the design of a Sensors Network (FSN) system which is able to interact with a user, and exploit the relative data of the Sensors (SRs) in real time. The system performs localization with triangulation and the SRs are detect only TRs bearing data (range free). System design and algorithms are also explained. Efficient algorithms were elaborated and the outcomes of their implementation were calculated. The system design targets to reduce system errors and increase the accuracy and the speed of detection. Synchronously and through interaction with the user and changes of relative settings and parameters will be able to offer the user accurate results on localization of TRs in the area minimizing false readings and False Triangulations (FTRNs). The system also enables the user to apply optimization techniques in order to increase the system detection rate and performance and keep the surveillance in the Field of Interest (FoI) on a high level. The optimization methodology applied for the system proves that the FSN system is able to operate with a high performance even when saturation phenomena appear. The unique outcome of the research conducted, is that this thesis paves the way to enhance the localization via Triangulation for a network of Fixed Sensors with known position. The value of this thesis is that the FSN system performs bearing only detection (Range free) with a certain accuracy and the Area of Interest (AOI) is covered efficiently

Efficiency and Accuracy Enhancement of Intrusion Detection System Using Feature Selection and Cross-layer Mechanism

The dramatic increase in the number of connected devices and the significant growth of the network traffic data have led to many security vulnerabilities and cyber-attacks. Hence, developing new methods to secure the network infrastructure and protect data from malicious and unauthorized access becomes a vital aspect of communication network design. Intrusion Detection Systems (IDSs), as common widely used security techniques, are critical to detect network attacks and unauthorized network access and thus minimize further cyber-attack damages. However, there are a number of weaknesses that need to be addressed to make reliable IDS for real-world applications. One of the fundamental challenges is the large number of redundant and non-relevant data. Feature selection emerges as a necessary step in efficient IDS design to overcome high dimensionality problem and enhance the performance of IDS through the reduction of its complexity and the acceleration of the detection process. Moreover, detection algorithm has significant impact on the performance of IDS. Machine learning techniques are widely used in such systems which is studied in details in this dissertation. One of the most destructive activities in wireless networks such as MANET is packet dropping. The existence of the intrusive attackers in the network is not the only cause of packet loss. In fact, packet drop can occur because of faulty network. Hence, in order detect the packet dropping caused by a malicious activity of an attacker, information from various layers of the protocol is needed to detect malicious packet loss effectively. To this end, a novel cross-layer design for malicious packet loss detection in MANET is proposed using features from physical layer, network layer and MAC layer to make a better detection decision. Trust-based mechanism is adopted in this design and a packet loss free routing algorithm is presented accordingly

LOCALIZED MOVEMENT CONTROL CONNECTIVITY RESTORATION ALGORITHMS FOR WIRELESS SENSOR AND ACTOR NETWORKS

Wireless Sensor and Actor Networks (WSANs) are gaining an increased interest because of their suitability for mission-critical applications that require autonomous and intelligent interaction with the environment. Hazardous application environments such as forest fire monitoring, disaster management, search and rescue, homeland security, battlefield reconnaissance, etc. make actors susceptible to physical damage. Failure of a critical (i.e. cut-vertex) actor partitions the inter-actor network into disjointed segments while leaving a coverage hole. Maintaining inter-actor connectivity is extremely important in mission-critical applications of WSANs where actors have to quickly plan an optimal coordinated response to detected events. Some proactive approaches pursued in the literature deploy redundant nodes to provide fault tolerance; however, this necessitates a large actor count that leads to higher cost and becomes impractical. On the other hand, the harsh environment strictly prohibits an external intervention to replace a failed node. Meanwhile, reactive approaches might not be suitable for time-sensitive applications. The autonomous and unattended nature of WSANs necessitates a self-healing and agile recovery process that involves existing actors to mend the severed inter-actor connectivity by reconfiguring the topology. Moreover, though the possibility of simultaneous multiple actor failure is rare, it may be precipitated by a hostile environment and disastrous events. With only localized information, recovery from such failures is extremely challenging. Furthermore, some applications may impose application-level constraints while recovering from a node failure. In this dissertation, we address the challenging connectivity restoration problem while maintaining minimal network state information. We have exploited the controlled movement of existing (internal) actors to restore the lost connectivity while minimizing the impact on coverage. We have pursued distributed greedy heuristics. This dissertation presents four novel approaches for recovering from node failure. In the first approach, volunteer actors exploit their partially utilized transmission power and reposition themselves in such a way that the connectivity is restored. The second approach identifies critical actors in advance, designates them preferably as noncritical backup nodes that replace the failed primary if such contingency arises in the future. In the third approach, we design a distributed algorithm that recovers from a special case of multiple simultaneous failures. The fourth approach factors in application-level constraints on the mobility of actors while recovering from node failure and strives to minimize the impact of critical node failure on coverage and connectivity. The performance of proposed approaches is analyzed and validated through extensive simulations. Simulation results confirm the effectiveness of proposed approaches that outperform the best contemporary schemes found in literature

A survey on fault diagnosis in wireless sensor networks

Wireless sensor networks (WSNs) often consist of hundreds of sensor nodes that may be deployed in relatively harsh and complex environments. In views of hardware cost, sensor nodes always adopt relatively cheap chips, which makes these nodes become error-prone or faulty in the course of their operation. Natural factors and electromagnetic interference could also influence the performance of the WSNs. When sensor nodes become faulty, they may have died which means they cannot communicate with other members in the wireless network, they may be still alive but produce incorrect data, they may be unstable jumping between normal state and faulty state. To improve data quality, shorten response time, strengthen network security, and prolong network lifespan, many studies have focused on fault diagnosis. This survey paper classifies fault diagnosis methods in recent five years into three categories based on decision centers and key attributes of employed algorithms: centralized approaches, distributed approaches, and hybrid approaches. As all these studies have specific goals and limitations, this paper tries to compare them, lists their merits and limits, and propose potential research directions based on established methods and theories

モバイルシンクを用いた無線センサネットワークにおける省電力データ収集に関する研究

Tohoku University加藤寧課