383 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

    Qos Provisioning for Energy Efficiency in Mobile Ad-Hoc Network

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    In mobile ad-hoc networks Quality of Service QoS of a multicast routing protocol is one of the most key performance metrics Slotconditions and network topology frequently change Topology dynamic and in order to achieve a certain level of QoS complexalgorithms and protocols are needed Network graph conditionsare neglected during the design of aexisting multicast protocol However vulnerability against network graph errors can severely affect theperformance of a multicast protocol To address this here the author proposesanenergy efficient network graph pre-processing approach to enable traffic engineering and enhance the performance of energy efficiency in terms of network efficiency by QoSprovisioning to cater the multicast routing issue in MANETS In this approach prioritized admission control PAC scheme is implemented to improvise D2D Device to Device communications into cellular network to overcome the limitations of MANET

    Mesh based and Hybrid Multicast routing protocols for MANETs: Current State of the art

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    This paper discusses various multicast routing protocols which are proposed in the recent past each having its own unique characteristic, with a motive of providing a complete understanding of these multicast routing protocols and present the scope of future research in this field. Further, the paper specifically discusses the current development in the development of mesh based and hybrid multicasting routing protocols. The study of this paper addresses the solution of most difficult task in Multicast routing protocols for MANETs under host mobility which causes multi-hop routing which is even more severe with bandwidth limitations. The Multicast routing plays a substantial part in MANETs

    Performance Comparison of Minimum Hop and Minimum Edge Based Multicast Routing Under Different Mobility Models for Mobile Ad Hoc Networks

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    Towards Optimal Distributed Node Scheduling in a Multihop Wireless Network through Local Voting

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    In a multihop wireless network, it is crucial but challenging to schedule transmissions in an efficient and fair manner. In this paper, a novel distributed node scheduling algorithm, called Local Voting, is proposed. This algorithm tries to semi-equalize the load (defined as the ratio of the queue length over the number of allocated slots) through slot reallocation based on local information exchange. The algorithm stems from the finding that the shortest delivery time or delay is obtained when the load is semi-equalized throughout the network. In addition, we prove that, with Local Voting, the network system converges asymptotically towards the optimal scheduling. Moreover, through extensive simulations, the performance of Local Voting is further investigated in comparison with several representative scheduling algorithms from the literature. Simulation results show that the proposed algorithm achieves better performance than the other distributed algorithms in terms of average delay, maximum delay, and fairness. Despite being distributed, the performance of Local Voting is also found to be very close to a centralized algorithm that is deemed to have the optimal performance

    Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

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    Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

    A Dynamic Data Driven Application System for Vehicle Tracking

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    AbstractTracking the movement of vehicles in urban environments using fixed position sensors, mobile sensors, and crowd-sourced data is a challenging but important problem in applications such as law enforcement and defense. A dynamic data driven application system (DDDAS) is described to track a vehicle's movements by repeatedly identifying the vehicle under investigation from live image and video data, predicting probable future locations, and repositioning sensors or retargeting requests for information in order to reacquire the vehicle. An overview of the envisioned system is described that includes image processing algorithms to detect and recapture the vehicle from live image data, a computational framework to predict probable vehicle locations at future points in time, and a power aware data distribution management system to disseminate data and requests for information over ad hoc wireless communication networks. A testbed under development in the midtown area of Atlanta, Georgia in the United States is briefly described
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