Deployment and coverage maintenance in mobile sensor networks

Deployment of mobile nodes in a region of interest is a critical issue in building a mobile sensor network because it affects cost and detection capabilities of the system. The deployment of mobile sensors in essence is the movement of sensors from an initial position to a final optimal location. Considerable attention has recently been given to this deployment issue. Many of the distributed deployment schemes use the potential field method. In most cases, the negative gradient of the potential function becomes the feedback control input to a node. This assumes that the potential function is differentiable over the entire region. This assumption is valid primarily when the topology of the network is fixed. In this research, we analyze the stability of a network that uses piecewise smooth potential functions. A gravitation-like force is proposed to deploy a group of agents and to form a certain configuration. We use a nonsmooth version of the Lyapunov stability theory and LaSalle’s invariance principle to show asymptotic stability of the network which is governed by discontinuous dynamics. We propose a hierarchical structure using potential fields for mobile sensor network deployment. A group of mobile nodes first form a cluster using a potential field method and then cluster heads are used to establish a hexagonal structure that employs a higher level potential field. We consider specifically the problem of deploying a mobile sensor network so that a certain area coverage is realized and maintained. And we propose an algorithm for main taining the desired coverage that assumes the availability of a stochastic sensor model. The model reflects the decline of the sensor accuracy as the distance increases from the sensor. It is further assumed that each node’s sensor has a different sensing range to represent sensor performance deterioration due to power decay. The network deployment scheme combines artificial forces with individual sensor ranges. The validity and the effectiveness of the proposed algorithm are compared to the conventional methods in simulations. Simulation results confirm the effectiveness of the proposed algorithms with respect to a defined performance metric

Connectivity-guaranteed and obstacle-adaptive deployment schemes for mobile sensor networks

Mobile sensors can relocate and self-deploy into a network. While focusing on the problems of coverage, existing deployment schemes largely over-simplify the conditions for network connectivity: they either assume that the communication range is large enough for sensors in geometric neighborhoods to obtain location information through local communication, or they assume a dense network that remains connected. In addition, an obstacle-free field or full knowledge of the field layout is often assumed. We present new schemes that are not governed by these assumptions, and thus adapt to a wider range of application scenarios. The schemes are designed to maximize sensing coverage and also guarantee connectivity for a network with arbitrary sensor communication/sensing ranges or node densities, at the cost of a small moving distance. The schemes do not need any knowledge of the field layout, which can be irregular and have obstacles/holes of arbitrary shape. Our first scheme is an enhanced form of the traditional virtual-force-based method, which we term the Connectivity-Preserved Virtual Force (CPVF) scheme. We show that the localized communication, which is the very reason for its simplicity, results in poor coverage in certain cases. We then describe a Floor-based scheme which overcomes the difficulties of CPVF and, as a result, significantly outperforms it and other state-of-the-art approaches. Throughout the paper our conclusions are corroborated by the results from extensive simulations

Autonomous deployment and repair of a sensor network using an unmanned aerial vehicle

We describe a sensor network deployment method using autonomous flying robots. Such networks are suitable for tasks such as large-scale environmental monitoring or for command and control in emergency situations. We describe in detail the algorithms used for deployment and for measuring network connectivity and provide experimental data we collected from field trials. A particular focus is on determining gaps in connectivity of the deployed network and generating a plan for a second, repair, pass to complete the connectivity. This project is the result of a collaboration between three robotics labs (CSIRO, USC, and Dartmouth.)

Coordination of Mobile Mules via Facility Location Strategies

In this paper, we study the problem of wireless sensor network (WSN) maintenance using mobile entities called mules. The mules are deployed in the area of the WSN in such a way that would minimize the time it takes them to reach a failed sensor and fix it. The mules must constantly optimize their collective deployment to account for occupied mules. The objective is to define the optimal deployment and task allocation strategy for the mules, so that the sensors' downtime and the mules' traveling distance are minimized. Our solutions are inspired by research in the field of computational geometry and the design of our algorithms is based on state of the art approximation algorithms for the classical problem of facility location. Our empirical results demonstrate how cooperation enhances the team's performance, and indicate that a combination of k-Median based deployment with closest-available task allocation provides the best results in terms of minimizing the sensors' downtime but is inefficient in terms of the mules' travel distance. A k-Centroid based deployment produces good results in both criteria.Comment: 12 pages, 6 figures, conferenc

WSN and RFID integration to support intelligent monitoring in smart buildings using hybrid intelligent decision support systems

The real time monitoring of environment context aware activities is becoming a standard in the service delivery in a wide range of domains (child and elderly care and supervision, logistics, circulation, and other). The safety of people, goods and premises depends on the prompt reaction to potential hazards identified at an early stage to engage appropriate control actions. This requires capturing real time data to process locally at the device level or communicate to backend systems for real time decision making. This research examines the wireless sensor network and radio frequency identification technology integration in smart homes to support advanced safety systems deployed upstream to safety and emergency response. These systems are based on the use of hybrid intelligent decision support systems configured in a multi-distributed architecture enabled by the wireless communication of detection and tracking data to support intelligent real-time monitoring in smart buildings. This paper introduces first the concept of wireless sensor network and radio frequency identification technology integration showing the various options for the task distribution between radio frequency identification and hybrid intelligent decision support systems. This integration is then illustrated in a multi-distributed system architecture to identify motion and control access in a smart building using a room capacity model for occupancy and evacuation, access rights and a navigation map automatically generated by the system. The solution shown in the case study is based on a virtual layout of the smart building which is implemented using the capabilities of the building information model and hybrid intelligent decision support system.The Saudi High Education Ministry and Brunel University (UK

Distributed Network Anomaly Detection on an Event Processing Framework

Network Intrusion Detection Systems (NIDS) are an integral part of modern data centres to ensure high availability and compliance with Service Level Agreements (SLAs). Currently, NIDS are deployed on high-performance, high-cost middleboxes that are responsible for monitoring a limited section of the network. The fast increasing size and aggregate throughput of modern data centre networks have come to challenge the current approach to anomaly detection to satisfy the fast growing compute demand. In this paper, we propose a novel approach to distributed intrusion detection systems based on the architecture of recently proposed event processing frameworks. We have designed and implemented a prototype system using Apache Storm to show the benefits of the proposed approach as well as the architectural differences with traditional systems. Our system distributes modules across the available devices within the network fabric and uses a centralised controller for orchestration, management and correlation. Following the Software Defined Networking (SDN) paradigm, the controller maintains a complete view of the network but distributes the processing logic for quick event processing while performing complex event correlation centrally. We have evaluated the proposed system using publicly available data centre traces and demonstrated that the system can scale with the network topology while providing high performance and minimal impact on packet latency