Wireless sensor networks (WS�s) become a major tool for various security and surveillance applications to detect and monitor environmental changes, to control vehicle traffic, etc. For all these capabilities, we propose in this paper to use WS�s in rescue applications. These applications are critical in terms of network response time when disaster strikes. The network response time is the time required by sensor nodes to detect victims' positions and forward them to the sink node. In this paper, we consider two sensor nodes deployment strategies: linear and circular strategies. By deployment strategies, we mean initial nodes positioning and nodes movement procedures. Therefore, we simulate these two strategies under the WS�et simulator and derived the Monitored Area Sweep Time (MAST) (i.e., the time required by sensor nodes to scan all the area coordinates to find victims) and the energy dissipation due to node mobility. Simulation results are verified using analytical expressions of the zone sweep time and the energy dissipation. Finally, we extend the behavior of the sensor nodes deployment strategies to support nodes communication so that mobile sensors can forward victims' positions to the sink node.
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In this paper we present an algorithmic solution for the distributed, complete coverage, path planning problem. Real world applications such as lawn mowing, chemical spill clean-up, and humanitarian de-mining can be automated by the employment of a team of autonomous mobile robots. Our approach builds on a single robot coverage algorithm. A greedy auction algorithm (a market based mechanism) is used for task reallocation among the robots. The robots are initially distributed through space and each robot is allocated a virtually bounded area to cover. Communication between the robots is available without any restrictions.
The advent of Wireless Sensor Network (WSN) technologies is paving the way for a panoply of new ubiquitous computing applications, some of them with critical requirements. In the ART-WiSe framework, we are designing a two-tiered communication architecture for supporting real-time and reliable communications in WSNs. Within this context, we have been developing a test-bed application, for testing, validating and demonstrating our theoretical findings - a search&rescue/pursuit-evasion application. Basically, a WSN deployment is used to detect, localize and track a target robot and a station controls a rescuer/pursuer robot until it gets close enough to the target robot. This paper describes how this application was engineered, particularly focusing on the implementation of the localization mechanism.
Sensor deployment is an important problem in mobile wireless sensor networks. This paper presents a distributed self deployment algorithm for mobile sensors. Performance metrics to evaluate algorithm performance are coverage, uniformity, time and distance traveled till the algorithm converges. Our algorithm is compared with a simulated annealing based algorithm for deployment and is shown to exhibit excellent performance.
Many visions of the future include people immersed in an environment surrounded by sensors and intelligent devices, which use smart infrastructures to improve the quality of life and safety in emergency situations. Ubiquitous communication enables these sensors or intelligent devices to communicate with each other and the user or a decision maker by means of ad hoc wireless networking. Organization and optimization of network resources are essential to provide ubiquitous communication for a longer duration in large-scale networks and are helpful to migrate intelligence from higher and remote levels to lower and local levels. In this paper, distributed energy-efficient deployment algorithms for mobile sensors and intelligent devices that form an Ambient Intelligent network are proposed. These algorithms employ a synergistic combination of cluster structuring and a peer-to-peer deployment scheme. An energy-efficient deployment algorithm based on Voronoi diagrams is also proposed here. Performance of our algorithms is evaluated in terms of coverage, uniformity, and time and distance traveled until the algorithm converges. Our algorithms are shown to exhibit excellent performance.
- Andrew Howard
- Maja J. Matarić
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![Gaurav S. Sukhatme]()
This paper describes an incremental deployment algorithm for mobile sensor networks. A mobile sensor network is a distributed collection of nodes, each of which has sensing, computation, communication and locomotion capabilities. The algorithm described in this paper will deploy such nodes one-at-a-time into an unknown environment, with each node making use of information gathered by previously deployed nodes to determine its deployment location. The algorithm is designed to maximize network coverage while simultaneously ensuring that nodes retain line-of-sight relationships with one another. This latter constraint arises from the need to localize the nodes in an unknown environment: in our previous work on team localization (A. Howard, M.J. Matari, and G.S. Sukhatme, in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, EPFL, Switzerland, 2002; IEEE Transactions on Robotics and Autonomous Systems, 2002) we have shown how nodes can localize themselves by using other nodes as landmarks. This paper describes the incremental deployment algorithm and presents the results from an extensive series of simulation experiments. These experiments serve to both validate the algorithm and illuminate its empirical properties.
Research in wireless sensor networks has attracted a lot of attention in recent years. Real applications, such as habitat monitoring, environmental and structural monitoring, start to work in practical. In this paper, we argue that wireless sensor network is a very promising technology for fire rescue applications. First, we abstract four specific requirements of this application, including accountability of firefighters, real-time monitoring, intelligent scheduling and resource allocation, and web-enabled service and integration. To meet these requirements, we propose FireNet, a wireless sensor network architecture for this specific type of application. Based on these requirements and the characteristics of wireless sensor networks, several research challenges in terms of new protocols as well as hardware and software support are examined. Finally, we conclude that wireless sensor network is a very powerful and suitable tool to be applied in this application.
Intrusion detection, area coverage and border surveillance are important applications of wireless sensor networks today. They can be (and are being) used to monitor large unprotected areas so as to detect intruders as they cross a border or as they penetrate a protected area. We consider the problem of how to optimally move mobile sensors to the fence (perimeter) of a region delimited by a simple polygon in order to detect intruders from either entering its interior or exiting from it. We discuss several related issues and problems, propose two models, provide algorithms and analyze their optimal mobility behavior.
Recently there has been a great deal of research on using mobility in sensor networks to assist in the initial deployment of nodes. Mobile sensors are useful in this environment because they can move to locations that meet sensing coverage requirements. This paper explores the motion capability to relocate sensors to deal with sensor failure or respond to new events. We define the problem of sensor relocation and propose a two-phase sensor relocation solution: redundant sensors are first identified and then relocated to the target location. We propose a Grid-Quorum solution to quickly locate the closest redundant sensor with low message complexity, and propose to use cascaded movement to relocate the redundant sensor in a timely, efficient and balanced way. Simulation results verify that the proposed solution outperforms others in terms of relocation time, total energy consumption, and minimum remaining energy.
- S.C. Wong
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![Bruce Macdonald]()
In applications such as vacuum cleaning, painting, demining and foraging, a mobile robot must cover an unknown surface. The efficiency and completeness of coverage is improved via the construction of a map of covered regions while the robot covers the surface. Existing methods generally use grid maps, which are susceptible to odometry error and may require considerable memory and computation. This paper proposes a topological map and presents a coverage algorithm in which natural landmarks are added as nodes in a partial map. The completeness of the algorithm is argued. Simulation tests show over 99% of the surface is covered; 85% for real (Khepera) robot tests. The path length is about 10% worse than optimal in simulation tests, and about 20% worse than optimal for the real robot, which are within theoretical upper bounds for approximates solutions to traveling salesman based coverage problems. The proposed algorithm generates shorter paths and covers a wider variety of environments than topological coverage based on Morse decompositions.
The effectiveness of cluster-based distributed sensor networks depends to a large extent on the coverage provided by the sensor deployment. We propose a virtual force algorithm (VFA) as a sensor deployment strategy to enhance the coverage after an initial random placement of sensors. For a given number of sensors, the VFA algorithm attempts to maximize the sensor field coverage. A judicious combination of attractive and repulsive forces is used to determine virtual motion paths and the rate of movement for the randomly-placed sensors. Once the effective sensor positions are identified, a one-time movement with energy consideration incorporated is carried out, i.e., the sensors are redeployed to these positions. We also propose a novel probabilistic target localization algorithm that is executed by the cluster head. The localization results are used by the cluster head to query only a few sensors (out of those that report the presence of a target) for more detailed information. Simulation results are presented to demonstrate the effectiveness of the proposed approach.
- Maxim A. Batalin
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![Gaurav S. Sukhatme]()
The traditional approach to measure the e#ciency of a (static) coverage task is the ratio of the intersection of the areas covered by sensors, to the total free space in the environment. Here we address the dynamic coverage problem, which requires all areas of free space in the environment to be covered by sensors in as short a time as possible. We introduce a frequency coverage metric that measures the frequency of every-point coverage, and propose a decentralized algorithm that utilizes locally available information about the environment to address this problem. Our algorithm produces exploratory, patrol-like behavior. Robots deploy communication beacons into the environment to mark previously visited areas. These nodes act as local signposts for robots which subsequently return to their vicinity. By deploying such (stationary) nodes into the environment robots can make local decisions about their motion strategy. We analyze the proposed algorithm and compare it with a baseline approach - a modified version of a static coverage algorithm described in [1].
In this paper, we present a family of adaptive protocols, called SPIN (Sensor Protocols for Information via Negotiation) , that eciently disseminates information among sensors in an energy-constrained wireless sensor network. Nodes running a SPIN communication protocol name their data using high-level data descriptors, called meta-data. They use meta-data negotiations to eliminate the transmission of redundant data throughout the network. In addition, SPIN nodes can base their communication decisions both upon application-specic knowledge of the data and upon knowledge of the resources that are available to them. This allows the sensors to eciently distribute data given a limited energy supply. We simulate and analyze the performance of two specic SPIN protocols, comparing them to other possible approaches and a theoretically optimal protocol. We nd that the SPIN protocols can deliver 60% more data for a given amount of energy than conventional approaches. We also nd that, in terms...
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