3,642 research outputs found

    Adaptive Time Synchronization for Homogeneous WSNs

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    Wireless sensor networks (WSNs) are being used for observing real‐world phenomenon. It is important that sensor nodes (SNs) must be synchronized to a common time in order to precisely map the data collected by SNs. Clock synchronization is very challenging in WSNs as the sensor networks are resource constrained networks. It is essential that clock synchronization protocols designed for WSNs must be light weight i.e. SNs must be synchronized with fewer synchronization message exchanges. In this paper, we propose a clock synchronization protocol for WSNs where first of all cluster heads (CHs) are synchronized with the sink and then the cluster nodes (CNs) are synchronized with their respective CHs. CNs are synchronized with the help of time synchronization node (TSN) chosen by the respective CHs. Simulation results show that proposed protocol requires considerably fewer synchronization messages as compared with the reference broadcast synchronization (RBS) protocol and minimum variance unbiased estimation (MUVE) method. Clock skew correction mechanism applied in proposed protocol guarantees long term stability and hence decreases re‐ synchronization frequency thereby conserving more energ

    Clock Synchronization in Wireless Sensor Networks: An Overview

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    The development of tiny, low-cost, low-power and multifunctional sensor nodes equipped with sensing, data processing, and communicating components, have been made possible by the recent advances in micro-electro-mechanical systems (MEMS) technology. Wireless sensor networks (WSNs) assume a collection of such tiny sensing devices connected wirelessly and which are used to observe and monitor a variety of phenomena in the real physical world. Many applications based on these WSNs assume local clocks at each sensor node that need to be synchronized to a common notion of time. This paper reviews the existing clock synchronization protocols for WSNs and the methods of estimating clock offset and clock skew in the most representative clock synchronization protocols for WSNs

    Clock Synchronization in Wireless Sensor Networks: Analysis and Design of Error Precision Based on Lossy Networked Control Perspective

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    Motivated by the importance of the clock synchronization in wireless sensor networks (WSNs), due to the packet loss, the synchronization error variance is a random variable and may exceed the designed boundary of the synchronization variance. Based on the clock synchronization state space model, this paper establishes the model of synchronization error variance analysis and design issues. In the analysis issue, assuming sensor nodes exchange clock information in the network with packet loss, we find a minimum clock information packet arrival rate in order to guarantee the synchronization precision at synchronization node. In the design issue, assuming sensor node freely schedules whether to send the clock information, we look for an optimal clock information exchange rate between synchronization node and reference node which offers the optimal tradeoff between energy consumption and synchronization precision at synchronization node. Finally, simulations further verify the validity of clock synchronization analysis and design from the perspective of synchronization error variance

    Distributed Local Linear Parameter Estimation using Gaussian SPAWN

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    We consider the problem of estimating local sensor parameters, where the local parameters and sensor observations are related through linear stochastic models. Sensors exchange messages and cooperate with each other to estimate their own local parameters iteratively. We study the Gaussian Sum-Product Algorithm over a Wireless Network (gSPAWN) procedure, which is based on belief propagation, but uses fixed size broadcast messages at each sensor instead. Compared with the popular diffusion strategies for performing network parameter estimation, whose communication cost at each sensor increases with increasing network density, the gSPAWN algorithm allows sensors to broadcast a message whose size does not depend on the network size or density, making it more suitable for applications in wireless sensor networks. We show that the gSPAWN algorithm converges in mean and has mean-square stability under some technical sufficient conditions, and we describe an application of the gSPAWN algorithm to a network localization problem in non-line-of-sight environments. Numerical results suggest that gSPAWN converges much faster in general than the diffusion method, and has lower communication costs, with comparable root mean square errors

    Timed Analysis of Security Protocols

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    We propose a method for engineering security protocols that are aware of timing aspects. We study a simplified version of the well-known Needham Schroeder protocol and the complete Yahalom protocol, where timing information allows the study of different attack scenarios. We model check the protocols using UPPAAL. Further, a taxonomy is obtained by studying and categorising protocols from the well known Clark Jacob library and the Security Protocol Open Repository (SPORE) library. Finally, we present some new challenges and threats that arise when considering time in the analysis, by providing a novel protocol that uses time challenges and exposing a timing attack over an implementation of an existing security protocol

    Representing Conversations for Scalable Overhearing

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    Open distributed multi-agent systems are gaining interest in the academic community and in industry. In such open settings, agents are often coordinated using standardized agent conversation protocols. The representation of such protocols (for analysis, validation, monitoring, etc) is an important aspect of multi-agent applications. Recently, Petri nets have been shown to be an interesting approach to such representation, and radically different approaches using Petri nets have been proposed. However, their relative strengths and weaknesses have not been examined. Moreover, their scalability and suitability for different tasks have not been addressed. This paper addresses both these challenges. First, we analyze existing Petri net representations in terms of their scalability and appropriateness for overhearing, an important task in monitoring open multi-agent systems. Then, building on the insights gained, we introduce a novel representation using Colored Petri nets that explicitly represent legal joint conversation states and messages. This representation approach offers significant improvements in scalability and is particularly suitable for overhearing. Furthermore, we show that this new representation offers a comprehensive coverage of all conversation features of FIPA conversation standards. We also present a procedure for transforming AUML conversation protocol diagrams (a standard human-readable representation), to our Colored Petri net representation

    Bioinspired Principles for Large-Scale Networked Sensor Systems: An Overview

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    Biology has often been used as a source of inspiration in computer science and engineering. Bioinspired principles have found their way into network node design and research due to the appealing analogies between biological systems and large networks of small sensors. This paper provides an overview of bioinspired principles and methods such as swarm intelligence, natural time synchronization, artificial immune system and intercellular information exchange applicable for sensor network design. Bioinspired principles and methods are discussed in the context of routing, clustering, time synchronization, optimal node deployment, localization and security and privacy
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