872 research outputs found

    Coverage Repair Strategies for Wireless Sensor Networks Using Mobile Actor Based on Evolutionary Computing

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    A standard traveling salesman problem(TSP) under dual-objective strategy constrained is proposed in this paper, characterized by the fact that the demand of both as many as possible the numbers of nodes be visited in time and minimum trajectory distance. The motivation for this TSP problem under dual-objective strategy constrain stems from the coverage repair strategies for wireless sensor networks using mobile actor based on energy analysis, wherein a mobile robot replenishes sensors energy when it reaches the sensor node location. The Evolutionary Algorithm (EA) meta-heuristic elegantly solves this problem by the reasonable designed operators of crossover, mutation and local search strategy,which can accelerate convergence of the optimal solution. The global convergence of the proposed algorithm is proved, and the simulation results show the effectiveness of the proposed algorithm

    Coverage Repair Strategies for Wireless Sensor Networks using Mobile Actor Based on Evolutionary Computing

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    A standard traveling salesman problem(TSP) under dual-objective strategy constrained is proposed in this paper, characterized by the fact that the demand of both as many as possible the numbers of nodes be visited in time and minimum trajectory distance. The motivation for this TSP problem under dual-objective strategy constrain stems from the coverage repair strategies for wireless sensor networks using mobile actor based on energy analysis, wherein a mobile robot replenishes sensors energy when it reaches the sensor node location. The Evolutionary Algorithm (EA) meta-heuristic elegantly solves this problem by the reasonable designed operators of crossover, mutation and local search strategy,which can accelerate convergence of the optimal solution. The global convergence of the proposed algorithm is proved, and the simulation results show the effectiveness of the proposed algorithm

    Foundations of coverage algorithms in autonomic mobile sensor networks

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    Drones are poised to become a prominent focus of advances in the near future as hardware platforms manufactured via mass production become accessible to consumers in higher quantities at lower costs than ever before. As more ways to utilize such devices become more popular, algorithms for directing the activities of mobile sensors must expand in order to automate their work. This work explores algorithms used to direct the behavior of networks of autonomous mobile sensors, and in particular how such networks can operate to achieve coverage of a field using mobility. We focus special attention to the way limited mobility affects the performance (and other factors) of algorithms traditionally applied to area coverage and event detection problems. Strategies for maximizing event detection and minimizing detection delay as mobile sensors with limited mobility are explored in the first part of this work. Next we examine exploratory coverage, a new way of analyzing sensor coverage, concerned more with covering each part of the coverage field once, while minimizing mobility required to achieve this level of 1-coverage. This analysis is contained in the second part of this work. Extending the analysis of mobility, we next strive to explore the novel topic of disabled mobility in mobile sensors, and how algorithms might react to increase effectiveness given that some sensors have lost mobility while retaining other senses. This work analyzes algorithm effectiveness in light of disabled mobility, demonstrates how this particular failure mode impacts common coverage algorithms, and presents ways to adjust algorithms to mitigate performance losses. --Abstract, page iv

    An Integrated Testbed for Cooperative Perception with Heterogeneous Mobile and Static Sensors

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    Cooperation among devices with different sensing, computing and communication capabilities provides interesting possibilities in a growing number of problems and applications including domotics (domestic robotics), environmental monitoring or intelligent cities, among others. Despite the increasing interest in academic and industrial communities, experimental tools for evaluation and comparison of cooperative algorithms for such heterogeneous technologies are still very scarce. This paper presents a remote testbed with mobile robots and Wireless Sensor Networks (WSN) equipped with a set of low-cost off-the-shelf sensors, commonly used in cooperative perception research and applications, that present high degree of heterogeneity in their technology, sensed magnitudes, features, output bandwidth, interfaces and power consumption, among others. Its open and modular architecture allows tight integration and interoperability between mobile robots and WSN through a bidirectional protocol that enables full interaction. Moreover, the integration of standard tools and interfaces increases usability, allowing an easy extension to new hardware and software components and the reuse of code. Different levels of decentralization are considered, supporting from totally distributed to centralized approaches. Developed for the EU-funded Cooperating Objects Network of Excellence (CONET) and currently available at the School of Engineering of Seville (Spain), the testbed provides full remote control through the Internet. Numerous experiments have been performed, some of which are described in the paper

    Distributed navigation of multi-robot systems for sensing coverage

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    A team of coordinating mobile robots equipped with operation specific sensors can perform different coverage tasks. If the required number of robots in the team is very large then a centralized control system becomes a complex strategy. There are also some areas where centralized communication turns into an issue. So, a team of mobile robots for coverage tasks should have the ability of decentralized or distributed decision making. This thesis investigates decentralized control of mobile robots specifically for coverage problems. A decentralized control strategy is ideally based on local information and it can offer flexibility in case there is an increment or decrement in the number of mobile robots. We perform a broad survey of the existing literature for coverage control problems. There are different approaches associated with decentralized control strategy for coverage control problems. We perform a comparative review of these approaches and use the approach based on simple local coordination rules. These locally computed nearest neighbour rules are used to develop decentralized control algorithms for coverage control problems. We investigate this extensively used nearest neighbour rule-based approach for developing coverage control algorithms. In this approach, a mobile robot gives an equal importance to every neighbour robot coming under its communication range. We develop our control approach by making some of the mobile robots playing a more influential role than other members of the team. We develop the control algorithm based on nearest neighbour rules with weighted average functions. The approach based on this control strategy becomes efficient in terms of achieving a consensus on control inputs, say heading angle, velocity, etc. The decentralized control of mobile robots can also exhibit a cyclic behaviour under some physical constraints like a quantized orientation of the mobile robot. We further investigate the cyclic behaviour appearing due to the quantized control of mobile robots under some conditions. Our nearest neighbour rule-based approach offers a biased strategy in case of cyclic behaviour appearing in the team of mobile robots. We consider a clustering technique inside the team of mobile robots. Our decentralized control strategy calculates the similarity measure among the neighbours of a mobile robot. The team of mobile robots with the similarity measure based approach becomes efficient in achieving a fast consensus like on heading angle or velocity. We perform a rigorous mathematical analysis of our developed approach. We also develop a condition based on relaxed criteria for achieving consensus on velocity or heading angle of the mobile robots. Our validation approach is based on mathematical arguments and extensive computer simulations

    Reliable cost-optimal deployment of wireless sensor networks

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    Wireless Sensor Networks (WSNs) technology is currently considered one of the key technologies for realizing the Internet of Things (IoT). Many of the important WSNs applications are critical in nature such that the failure of the WSN to carry out its required tasks can have serious detrimental effects. Consequently, guaranteeing that the WSN functions satisfactorily during its intended mission time, i.e. the WSN is reliable, is one of the fundamental requirements of the network deployment strategy. Achieving this requirement at a minimum deployment cost is particularly important for critical applications in which deployed SNs are equipped with expensive hardware. However, WSN reliability, defined in the traditional sense, especially in conjunction with minimizing the deployment cost, has not been considered as a deployment requirement in existing WSN deployment algorithms to the best of our knowledge. Addressing this major limitation is the central focus of this dissertation. We define the reliable cost-optimal WSN deployment as the one that has minimum deployment cost with a reliability level that meets or exceeds a minimum level specified by the targeted application. We coin the problem of finding such deployments, for a given set of application-specific parameters, the Minimum-Cost Reliability-Constrained Sensor Node Deployment Problem (MCRC-SDP). To accomplish the aim of the dissertation, we propose a novel WSN reliability metric which adopts a more accurate SN model than the model used in the existing metrics. The proposed reliability metric is used to formulate the MCRC-SDP as a constrained combinatorial optimization problem which we prove to be NP-Complete. Two heuristic WSN deployment optimization algorithms are then developed to find high quality solutions for the MCRC-SDP. Finally, we investigate the practical realization of the techniques that we developed as solutions of the MCRC-SDP. For this purpose, we discuss why existing WSN Topology Control Protocols (TCPs) are not suitable for managing such reliable cost-optimal deployments. Accordingly, we propose a practical TCP that is suitable for managing the sleep/active cycles of the redundant SNs in such deployments. Experimental results suggest that the proposed TCP\u27s overhead and network Time To Repair (TTR) are relatively low which demonstrates the applicability of our proposed deployment solution in practice

    A pragmatic approach to area coverage in hybrid wireless sensor networks

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    Success of Wireless Sensor Networks (WSN) largely depends on whether the deployed network can provide desired area coverage with acceptable network lifetime. In hostile or harsh environments such as enemy territories in battlefields, fire or chemical spills, it is impossible to deploy the sensor nodes in a predeter- mined regular topology to guarantee adequate coverage. Random deployment is thus more practical and feasible for large target areas. On the other hand, random deployment of sensors is highly susceptible to the occurrence of coverage holes in the target area. A potential solution for enhancing the existing coverage achieved by random deployments involves the use of mobility capable sensors that would help fill the coverage holes. This thesis seeks to address the problem of determining the current coverage achieved by the non-deterministic deployment of static sensor nodes and subsequently enhancing the coverage using mobile sensors. The main contributions of this dissertation are the design and evaluation of MAPC (Mobility Assisted Probabilistic Coverage), a distributed protocol for ensuring area coverage in hybrid wireless sensor networks. The primary contribution is a pragmatic approach to sensor coverage and maintenance that we hope would lower the technical barriers to its field deployment. Most of the assumptions made in the MAPC protocol are realistic and implementable in real-life applications e.g., practical boundary estimation, coverage calculations based on a realistic sensing model, and use of movement triggering thresholds based on real radio characteristics etc. The MAPC is a comprehensive three phase protocol. In the first phase, the static sensors calculate the area coverage using the Probabilistic Coverage Algorithm (PCA). This is a deviation from the idealistic assumption used in the binary detection model, wherein a sensor can sense accurately within a well defined (usually circular) region. Static sensors execute the PCA algorithm, in a distributed way, to identify any holes in the coverage. In the second phase, MAPC scheme moves the mobile nodes in an optimal manner to fill these uncovered locations. For different types of initial deployments, the proposed movement algorithms consume only 30-40% of the energy consumed by the basic virtual force algorithm. In addition, this thesis addresses the problem of coverage loss due to damaged and energy depleted nodes. The problem has been formulated as an Integer Linear Program and implementable heuristics are developed that perform close to optimal solutions. By replacing in-operational nodes in phase three, MAPC scheme ensures the continuous operation of the WSN. Experiments with real mote hardware were conducted to validate the boundary and coverage estimation part of the MAPC protocol. Extensive discrete event simulations (using NS2) were also performed for the complete MAPC protocol and the results demonstrate that MAPC can enhance and maintain the area coverage by efficiently moving mobile sensor nodes to strategic positions in the uncovered area

    Coverage Protocols for Wireless Sensor Networks: Review and Future Directions

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    The coverage problem in wireless sensor networks (WSNs) can be generally defined as a measure of how effectively a network field is monitored by its sensor nodes. This problem has attracted a lot of interest over the years and as a result, many coverage protocols were proposed. In this survey, we first propose a taxonomy for classifying coverage protocols in WSNs. Then, we classify the coverage protocols into three categories (i.e. coverage aware deployment protocols, sleep scheduling protocols for flat networks, and cluster-based sleep scheduling protocols) based on the network stage where the coverage is optimized. For each category, relevant protocols are thoroughly reviewed and classified based on the adopted coverage techniques. Finally, we discuss open issues (and recommend future directions to resolve them) associated with the design of realistic coverage protocols. Issues such as realistic sensing models, realistic energy consumption models, realistic connectivity models and sensor localization are covered
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