3,916 research outputs found
Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications
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
AWARE: Platform for Autonomous self-deploying and operation of Wireless sensor-actuator networks cooperating with unmanned AeRial vehiclEs
This paper presents the AWARE platform that seeks to enable the cooperation of autonomous aerial vehicles with ground wireless sensor-actuator networks comprising both static and mobile nodes carried by vehicles or people. Particularly, the paper presents the middleware, the wireless sensor network, the node deployment by means of an autonomous helicopter, and the surveillance and tracking functionalities of the platform. Furthermore, the paper presents the first general experiments of the AWARE project that took place in March 2007 with the assistance of the Seville fire brigades
Software Defined Networks based Smart Grid Communication: A Comprehensive Survey
The current power grid is no longer a feasible solution due to
ever-increasing user demand of electricity, old infrastructure, and reliability
issues and thus require transformation to a better grid a.k.a., smart grid
(SG). The key features that distinguish SG from the conventional electrical
power grid are its capability to perform two-way communication, demand side
management, and real time pricing. Despite all these advantages that SG will
bring, there are certain issues which are specific to SG communication system.
For instance, network management of current SG systems is complex, time
consuming, and done manually. Moreover, SG communication (SGC) system is built
on different vendor specific devices and protocols. Therefore, the current SG
systems are not protocol independent, thus leading to interoperability issue.
Software defined network (SDN) has been proposed to monitor and manage the
communication networks globally. This article serves as a comprehensive survey
on SDN-based SGC. In this article, we first discuss taxonomy of advantages of
SDNbased SGC.We then discuss SDN-based SGC architectures, along with case
studies. Our article provides an in-depth discussion on routing schemes for
SDN-based SGC. We also provide detailed survey of security and privacy schemes
applied to SDN-based SGC. We furthermore present challenges, open issues, and
future research directions related to SDN-based SGC.Comment: Accepte
The Bus Goes Wireless: Routing-Free Data Collection with QoS Guarantees in Sensor Networks
Abstract—We present the low-power wireless bus (LWB), a new communication paradigm for QoS-aware data collection in lowpower sensor networks. The LWB maps all communication onto network floods by using Glossy, an efficient flooding architecture for wireless sensor networks. Therefore, unlike current solutions, the LWB requires no information of the network topology, and inherently supports networks with mobile nodes and multiple data sinks. A LWB prototype implemented in Contiki guarantees bounded end-to-end communication delay and duplicate-free, inorder packet delivery—key QoS requirements in many control and mission-critical applications. Experiments on two testbeds demonstrate that the LWB prototype outperforms state-of-theart data collection and link layer protocols, in terms of reliability and energy efficiency. For instance, we measure an average radio duty cycle of 1.69 % and an overall data yield of 99.97 % in a typical data collection scenario with 85 sensor nodes on Twist. I
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