390 research outputs found

    Availability and End-to-end Reliability in Low Duty Cycle Multihop Wireless Sensor Networks

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    A wireless sensor network (WSN) is an ad-hoc technology that may even consist of thousands of nodes, which necessitates autonomic, self-organizing and multihop operations. A typical WSN node is battery powered, which makes the network lifetime the primary concern. The highest energy efficiency is achieved with low duty cycle operation, however, this alone is not enough. WSNs are deployed for different uses, each requiring acceptable Quality of Service (QoS). Due to the unique characteristics of WSNs, such as dynamic wireless multihop routing and resource constraints, the legacy QoS metrics are not feasible as such. We give a new definition to measure and implement QoS in low duty cycle WSNs, namely availability and reliability. Then, we analyze the effect of duty cycling for reaching the availability and reliability. The results are obtained by simulations with ZigBee and proprietary TUTWSN protocols. Based on the results, we also propose a data forwarding algorithm suitable for resource constrained WSNs that guarantees end-to-end reliability while adding a small overhead that is relative to the packet error rate (PER). The forwarding algorithm guarantees reliability up to 30% PER

    Power Optimization for Wireless Sensor Networks

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    Joint optimization for wireless sensor networks in critical infrastructures

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    Energy optimization represents one of the main goals in wireless sensor network design where a typical sensor node has usually operated by making use of the battery with limited-capacity. In this thesis, the following main problems are addressed: first, the joint optimization of the energy consumption and the delay for conventional wireless sensor networks is presented. Second, the joint optimization of the information quality and energy consumption of the wireless sensor networks based structural health monitoring is outlined. Finally, the multi-objectives optimization of the former problem under several constraints is shown. In the first main problem, the following points are presented: we introduce a joint multi-objective optimization formulation for both energy and delay for most sensor nodes in various applications. Then, we present the Karush-Kuhn-Tucker analysis to demonstrate the optimal solution for each formulation. We introduce a method of determining the knee on the Pareto front curve, which meets the network designer interest for focusing on more practical solutions. The sensor node placement optimization has a significant role in wireless sensor networks, especially in structural health monitoring. In the second main problem of this work, the existing work optimizes the node placement and routing separately (by performing routing after carrying out the node placement). However, this approach does not guarantee the optimality of the overall solution. A joint optimization of sensor placement, routing, and flow assignment is introduced and is solved using mixed-integer programming modelling. In the third main problem of this study, we revisit the placement problem in wireless sensor networks of structural health monitoring by using multi-objective optimization. Furthermore, we take into consideration more constraints that were not taken into account before. This includes the maximum capacity per link and the node-disjoint routing. Since maximum capacity constraint is essential to study the data delivery over limited-capacity wireless links, node-disjoint routing is necessary to achieve load balancing and longer wireless sensor networks lifetime. We list the results of the previous problems, and then we evaluate the corresponding results

    Unified Power Management in Wireless Sensor Networks, Doctoral Dissertation, August 2006

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    Radio power management is of paramount concern in wireless sensor networks (WSNs) that must achieve long lifetimes on scarce amount of energy. Previous work has treated communication and sensing separately, which is insufficient for a common class of sensor networks that must satisfy both sensing and communication requirements. Furthermore, previous approaches focused on reducing energy consumption in individual radio states resulting in suboptimal solutions. Finally, existing power management protocols often assume simplistic models that cannot accurately reflect the sensing and communication properties of real-world WSNs. We develop a unified power management approach to address these issues. We first analyze the relationship between sensing and communication performance of WSNs. We show that sensing coverage often leads to good network connectivity and geographic routing performance, which provides insights into unified power management under both sensing and communication performance requirements. We then develop a novel approach called Minimum Power Configuration that ingegrates the power consumption in different radio states into a unified optimization framework. Finally, we develop two power management protocols that account for realistic communication and sensing properties of WSNs. Configurable Topology Control can configure a network topology to achieve desired path quality in presence of asymmetric and lossy links. Co-Grid is a coverage maintenance protocol that adopts a probabilistic sensing model. Co-Grid can satisfy desirable sensing QoS requirements (i.e., detection probability and false alarm rate) based on a distributed data fusion model

    On the performance, availability and energy consumption modelling of clustered IoT systems

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    Wireless sensor networks (WSNs) form a large part of the ecosystem of the Internet of Things (IoT), hence they have numerous application domains with varying performance and availability requirements. Limited resources that include processing capability, queue capacity, and available energy in addition to frequent node and link failures degrade the performance and availability of these networks. In an attempt to efficiently utilise the limited resources and to maintain the reliable network with efficient data transmission; it is common to select a clustering approach, where a cluster head is selected among the diverse IoT devices. This study presents the stochastic performance as well as the energy evaluation model for WSNs that have both node and link failures. The model developed considers an integrated performance and availability approach. Various duty cycling schemes within the medium-access control of the WSNs are also considered to incorporate the impact of sleeping/idle states that are presented using analytical modeling. The results presented using the proposed analytical models show the effects of factors such as failures, various queue capacities and system scalability. The analytical results presented are in very good agreement with simulation results and also present an important fact that the proposed models are very useful for identification of thresholds between WSN system characteristics

    A Survey on Classification of Routing Protocols in Wireless Sensor Networks

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    Late progressions in remote innovation has prompted gigantic development in organization of Wireless Sensor Networks (WSNs). WSNs are involved sensors and actuators hubs, thickly conveyed over some geographic area to detect, gather, handle and send information remotely to focal information authority. The correspondence among various remote sensor hubs is controlled by directing conventions; consequently the execution of WSN exceedingly relies on upon embraced steering strategy. Numerous such vitality proficient and quality steering conventions have been outlined throughout the years so as to build the execution of correspondence in WSNs. In this paper, a comprehensive survey and scientific classification of steering conventions is talked about on the premise of system structures and information transmission procedures. This review will help WSN framework fashioners to choose fitting directing convention for specific application
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