Push & Pull: autonomous deployment of mobile sensors for a complete coverage

Mobile sensor networks are important for several strategic applications devoted to monitoring critical areas. In such hostile scenarios, sensors cannot be deployed manually and are either sent from a safe location or dropped from an aircraft. Mobile devices permit a dynamic deployment reconfiguration that improves the coverage in terms of completeness and uniformity. In this paper we propose a distributed algorithm for the autonomous deployment of mobile sensors called Push&Pull. According to our proposal, movement decisions are made by each sensor on the basis of locally available information and do not require any prior knowledge of the operating conditions or any manual tuning of key parameters. We formally prove that, when a sufficient number of sensors are available, our approach guarantees a complete and uniform coverage. Furthermore, we demonstrate that the algorithm execution always terminates preventing movement oscillations. Numerous simulations show that our algorithm reaches a complete coverage within reasonable time with moderate energy consumption, even when the target area has irregular shapes. Performance comparisons between Push&Pull and one of the most acknowledged algorithms show how the former one can efficiently reach a more uniform and complete coverage under a wide range of working scenarios.Comment: Technical Report. This paper has been published on Wireless Networks, Springer. Animations and the complete code of the proposed algorithm are available for download at the address: http://www.dsi.uniroma1.it/~novella/mobile_sensors

Target tracking in wireless sensor networks

The problem being tackled here relates to the problem of target tracking in wireless sensor networks. It is a specific problem in localization. Localization primarily refers to the detection of spatial coordinates of a node or an object. Target tracking deals with finding spatial coordinates of a moving object and being able to track its movements. In the tracking scheme illustrated, sensors are deployed in a triangular fashion in a hexagonal mesh such that the hexagon is divided into a number of equilateral triangles. The technique used for detection is the trilateration technique in which intersection of three circles is used to determine the object location. While the object is being tracked by three sensors, distance to it from a fourth sensor is also being calculated simultaneously. The difference is that closest three sensors detect at a frequency of one second while the fourth sensor detects the object location at twice the frequency. Using the distance information from the fourth sensor and a simple mathematical technique, location of object is predicted for every half second as well. The key thing to note is that the forth sensor node is not used for detection but only for estimation of the object at half second intervals and hence does not utilize much power. Using this technique, tracking capability of the system is increased. The scheme proposed can theoretically detect objects moving at speeds of up to 33 m/s unlike the paper [16] on which it is based which can detect objects moving only up to speeds of 5 m/s. While the earlier system [16] has been demonstrated with four sensors as well, but for that the arrangement of sensor nodes is a square. The technique demonstrated does not involve a change in the arrangement and utilizes the hexagonal mesh arrangement. Some other scenarios have been tackled such as when displacement of the object is zero at the end of one second. Its movement is predicted during that time interval. Also, incase an object moves in a circle, such motions are also tracked

On the vulnerabilities of voronoi-based approaches to mobile sensor deployment

Mobile sensor networks are the most promising solution to cover an Area of Interest (AoI) in safety critical scenarios. Mobile devices can coordinate with each other according to a distributed deployment algorithm, without resorting to human supervision for device positioning and network configuration. In this paper, we focus on the vulnerabilities of the deployment algorithms based on Voronoi diagrams to coordinate mobile sensors and guide their movements. We give a geometric characterization of possible attack configurations, proving that a simple attack consisting of a barrier of few compromised sensors can severely reduce network coverage. On the basis of the above characterization, we propose two new secure deployment algorithms, named SecureVor and Secure Swap Deployment (SSD). These algorithms allow a sensor to detect compromised nodes by analyzing their movements, under different and complementary operative settings. We show that the proposed algorithms are effective in defeating a barrier attack, and both have guaranteed termination. We perform extensive simulations to study the performance of the two algorithms and compare them with the original approach. Results show that SecureVor and SSD have better robustness and flexibility and excellent coverage capabilities and deployment time, even in the presence of an attac

An Energy Aware Unequal Clustering Algorithm using Fuzzy Logic for Wireless Sensor Networks

In wireless sensor networks, clustering provides an effective way of organising the sensor nodes to achieve load balancing and increasing the lifetime of the network. Unequal clustering is an extension of common clustering that exhibits even better load balancing. Most existing approaches do not consider node density when clustering, which can pose significant problems. In this paper, a fuzzy-logic based cluster head selection approach is proposed, which considers the residual energy, centrality and density of the nodes. In addition, a fuzzy-logic based clustering range assignment approach is used, which considers the suitability and the position of the nodes in assigning the clustering range. Furthermore, a weight function is used to optimize the selection of the relay nodes. The proposed approach was compared with a number of well known approaches by simulation. The results showed that the proposed approach performs better than the other algorithms in terms of lifetime and other metrics

A Distributed Evolutionary Algorithmic Approach to the Coverage Problem for Submersible Sensors

Untethered, underwater sensors, deployed for event detection and tracking and operating in an autonomous mode will be required to self-assemble into a configuration, which optimizes their coverage, effectively minimizing the probability that an event in the target area goes undetected. This organized, cooperative, and autonomous, spreading-out of the sensors is complicated due to sensors localized communication. A given sensor will not in general have position and velocity information for all sensors, but only for those in its communication area. A possible approach to this problem, motivated by an evolutionary optimization technique, Particle Swarm Optimization (PSO) is proposed and extended in a novel way. A distributed version of PSO is developed. A distributed version of PSO is explored using experimental fitness to address the coverage problem in a two dimensional area

Real-time auditing of domotic robotic cleaners

Domotic Robotic Cleaners are autonomous devices that are designed to operate almost entirely unattended. In this paper we propose a system that aims to evaluate the performance of such devices by analysis of their trails. This concept of trails is central to our approach, and it encompasses the traditional notion of a path followed by a robot between arbitrary numbers of points in a physical space. We enrich trails with context-specific metadata, such as proximity to landmarks, frequency of visitation, duration, etc. We then process the trail data collected by the robots, we store it an appropriate data structure and derive useful statistical information from the raw data. The usefulness of the derived information is twofold: it can primarily be used to audit the performance of the robotic cleaner –for example, to give an accurate indication of how well a space is covered (cleaned). And secondarily information can be analyzed in real-time to affect the behavior of specific robots – for example to notify a robot that specific areas have not been adequately covered. Towards our first goal, we have developed and evaluated a prototype of our system that uses a particular commercially available robotic cleaner. Our implementation deploys adhoc wireless local networking capability available through a surrogate device mounted onto this commodity robot; the device senses relative proximity to a grid of RFID tags attached to the floor. We report on the performance of this system in experiments conducted in a laboratory environment, which highlight the advantages and limitations of our approach

Mobile Search Strategies and Detection Analysis of Nuclear Radiation Sources

This work focuses on detection analysis and search strategies for nuclear radiation sources in metropolitan areas with mobile sensor networks. A mobile sensor detecting a stationary nuclear source experiences continually changing statistics. In this work we provide an analysis of the probability of detection of a nuclear source that incorporates these continual changes. We apply the analysis technique to several patterns of motion including linear and circular paths. Analysis is also presented for cases in which there is a significant vertical offset between source and mobile sensor (the three-dimensional problem). The resulting expressions are computationally simple to evaluate and have application to both analysis and simulation of nuclear detection systems in a variety of scenarios. In metropolitan areas, with vehicles equipped with detectors and Global Position System (GPS) devices, we consider the design of a robust detection system to provide consistent surveillance. Various strategies for providing this surveillance with a mobile sensor network are considered and the results are compared. Both time-from-last-visit based algorithms and detection algorithms that utilize both time and probability-of-miss estimates are considered. The algorithms are shown to perform well in a variety of scenarios, and it is further shown that the algorithms that utilize probability information outperform those that do not