7,278 research outputs found

    Robotic Wireless Sensor Networks

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    In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future

    Dead Reckoning Localization Technique for Mobile Wireless Sensor Networks

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    Localization in wireless sensor networks not only provides a node with its geographical location but also a basic requirement for other applications such as geographical routing. Although a rich literature is available for localization in static WSN, not enough work is done for mobile WSNs, owing to the complexity due to node mobility. Most of the existing techniques for localization in mobile WSNs uses Monte-Carlo localization, which is not only time-consuming but also memory intensive. They, consider either the unknown nodes or anchor nodes to be static. In this paper, we propose a technique called Dead Reckoning Localization for mobile WSNs. In the proposed technique all nodes (unknown nodes as well as anchor nodes) are mobile. Localization in DRLMSN is done at discrete time intervals called checkpoints. Unknown nodes are localized for the first time using three anchor nodes. For their subsequent localizations, only two anchor nodes are used. The proposed technique estimates two possible locations of a node Using Bezouts theorem. A dead reckoning approach is used to select one of the two estimated locations. We have evaluated DRLMSN through simulation using Castalia simulator, and is compared with a similar technique called RSS-MCL proposed by Wang and Zhu .Comment: Journal Paper, IET Wireless Sensor Systems, 201

    A Multi-hop Topology Control Based on Inter-node Range Measurement for Wireless Sensor Networks Node Localization

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    In centralized range-based localization techniques, sufficiency of inter-node range information received by the base station strongly affects node position estimation results. Successful data aggregation is influenced by link stability of each connection of routes, especially in a multi-hop topology model. In general, measuring the inter-node range is only performed for position determination purposes. This research introduces the use of inter-node range measurement information for link selection in a multi-hop route composition in order to increase the rate of data aggregation. Due to irregularity problems of wireless media, two areas of node communication have been considered. The regular communication area is the area in which other nodes are able to perform symmetrical communication to the node without failure. The irregular area is the area in which other nodes are seldom able to communicate. Due to its instability, some existing methods tried to avoid the irregular area completely. The proposed method, named Virtual Boundaries (VBs) prioritizes these areas. The regular communication area’s nodes have high priority to be selected as link vertices; however, when there is no link candidate inside this area, nodes within the irregular area will be selected with respect to their range to the parent node. This technique resulted in a more robust multi-hop topology that can reduce isolated node numbers and increase the percentage of data collected by the base station accordingly

    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

    PSO Based Deployment of Hybrid Sensor Networks

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    With the rapid increase in the usage of wireless sensor networks, it is emerging as a technology for monitoring various physical activities. The essential characteristics of wireless sensor network are coverage, cost, connectivity and lifetime which are dependent upon the number and type of sensors being used for the required task. A random deployment strategy of sensor nodes may cause coverage holes in the sensing ?eld. The work presented here shall mainly focus on deployment strategy of WSNs which will improve the coverage area that poses the biggest challenge to the developers. Most of the problems related to WSNs are modelled and approached as multi objective functions through various genetic algorithms. PSO is one such technique that is e?cient and computationally e?cient in addressing various issues such as optimising sensor deployment and localization of sensor nodes. A modi?ed particle swarm optimization (PSO) technique using grid based strategy has been proposed for sensor deployment which is capable of e?ciently deploying the sensors with an objective of maximizing the coverage ratio. It will determine the optimum location of the mobile nodes after the initial random deployment .The optimality rate of this approach is also higher as compared to other genetic algorithms

    Robust Localization from Incomplete Local Information

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    We consider the problem of localizing wireless devices in an ad-hoc network embedded in a d-dimensional Euclidean space. Obtaining a good estimation of where wireless devices are located is crucial in wireless network applications including environment monitoring, geographic routing and topology control. When the positions of the devices are unknown and only local distance information is given, we need to infer the positions from these local distance measurements. This problem is particularly challenging when we only have access to measurements that have limited accuracy and are incomplete. We consider the extreme case of this limitation on the available information, namely only the connectivity information is available, i.e., we only know whether a pair of nodes is within a fixed detection range of each other or not, and no information is known about how far apart they are. Further, to account for detection failures, we assume that even if a pair of devices is within the detection range, it fails to detect the presence of one another with some probability and this probability of failure depends on how far apart those devices are. Given this limited information, we investigate the performance of a centralized positioning algorithm MDS-MAP introduced by Shang et al., and a distributed positioning algorithm, introduced by Savarese et al., called HOP-TERRAIN. In particular, for a network consisting of n devices positioned randomly, we provide a bound on the resulting error for both algorithms. We show that the error is bounded, decreasing at a rate that is proportional to R/Rc, where Rc is the critical detection range when the resulting random network starts to be connected, and R is the detection range of each device.Comment: 40 pages, 13 figure

    A survey of localization in wireless sensor network

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    Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network
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