760 research outputs found

    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

    Resilient Wireless Sensor Networks Using Topology Control: A Review

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    Wireless sensor networks (WSNs) may be deployed in failure-prone environments, and WSNs nodes easily fail due to unreliable wireless connections, malicious attacks and resource-constrained features. Nevertheless, if WSNs can tolerate at most losing k − 1 nodes while the rest of nodes remain connected, the network is called k − connected. k is one of the most important indicators for WSNs’ self-healing capability. Following a WSN design flow, this paper surveys resilience issues from the topology control and multi-path routing point of view. This paper provides a discussion on transmission and failure models, which have an important impact on research results. Afterwards, this paper reviews theoretical results and representative topology control approaches to guarantee WSNs to be k − connected at three different network deployment stages: pre-deployment, post-deployment and re-deployment. Multi-path routing protocols are discussed, and many NP-complete or NP-hard problems regarding topology control are identified. The challenging open issues are discussed at the end. This paper can serve as a guideline to design resilient WSNs

    Towards Real-time Wireless Sensor Networks

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    Wireless sensor networks are poised to change the way computer systems interact with the physical world. We plan on entrusting sensor systems to collect medical data from patients, monitor the safety of our infrastructure, and control manufacturing processes in our factories. To date, the focus of the sensor network community has been on developing best-effort services. This approach is insufficient for many applications since it does not enable developers to determine if a system\u27s requirements in terms of communication latency, bandwidth utilization, reliability, or energy consumption are met. The focus of this thesis is to develop real-time network support for such critical applications. The first part of the thesis focuses on developing a power management solution for the radio subsystem which addresses both the problem of idle-listening and power control. In contrast to traditional power management solutions which focus solely on reducing energy consumption, the distinguishing feature of our approach is that it achieves both energy efficiency and real-time communication. A solution to the idle-listening problem is proposed in Energy Efficient Sleep Scheduling based on Application Semantics: ESSAT). The novelty of ESSAT lies in that it takes advantage of the common features of data collection applications to determine when to turn on and off a node\u27s radio without affecting real-time performance. A solution to the power control problem is proposed in Real-time Power Aware-Routing: RPAR). RPAR tunes the transmission power for each packet based on its deadline such that energy is saved without missing packet deadlines. The main theoretical contribution of this thesis is the development of novel transmission scheduling techniques optimized for data collection applications. This work bridges the gap between wireless sensor networks and real-time scheduling theory, which have traditionally been applied to processor scheduling. The proposed approach has significant advantages over existing design methodologies:: 1) it provides predictable performance allowing for the performance of a system to be estimated upon its deployment,: 2) it is possible to detect and handle overload conditions through simple rate control mechanisms, and: 3) it easily accommodates workload changes. I developed this framework under a realistic interference model by coordinating the activities at the MAC, link, and routing layers. The last component of this thesis focuses on the development of a real-time patient monitoring system for general hospital units. The system is designed to facilitate the detection of clinical deterioration, which is a key factor in saving lives and reducing healthcare costs. Since patients in general hospital wards are often ambulatory, a key challenge is to achieve high reliability even in the presence of mobility. To support patient mobility, I developed the Dynamic Relay Association Protocol -- a simple and effective mechanism for dynamically discovering the right relays for forwarding patient data -- and a Radio Mapping Tool -- a practical tool for ensuring network coverage in 802.15.4 networks. We show that it is feasible to use low-power and low-cost wireless sensor networks for clinical monitoring through an in-depth clinical study. The study was performed in a step-down cardiac care unit at Barnes-Jewish Hospital. This is the first long-term study of such a patient monitoring system

    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

    A cell outage management framework for dense heterogeneous networks

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    In this paper, we present a novel cell outage management (COM) framework for heterogeneous networks with split control and data planes-a candidate architecture for meeting future capacity, quality-of-service, and energy efficiency demands. In such an architecture, the control and data functionalities are not necessarily handled by the same node. The control base stations (BSs) manage the transmission of control information and user equipment (UE) mobility, whereas the data BSs handle UE data. An implication of this split architecture is that an outage to a BS in one plane has to be compensated by other BSs in the same plane. Our COM framework addresses this challenge by incorporating two distinct cell outage detection (COD) algorithms to cope with the idiosyncrasies of both data and control planes. The COD algorithm for control cells leverages the relatively larger number of UEs in the control cell to gather large-scale minimization-of-drive-test report data and detects an outage by applying machine learning and anomaly detection techniques. To improve outage detection accuracy, we also investigate and compare the performance of two anomaly-detecting algorithms, i.e., k-nearest-neighbor- and local-outlier-factor-based anomaly detectors, within the control COD. On the other hand, for data cell COD, we propose a heuristic Grey-prediction-based approach, which can work with the small number of UE in the data cell, by exploiting the fact that the control BS manages UE-data BS connectivity and by receiving a periodic update of the received signal reference power statistic between the UEs and data BSs in its coverage. The detection accuracy of the heuristic data COD algorithm is further improved by exploiting the Fourier series of the residual error that is inherent to a Grey prediction model. Our COM framework integrates these two COD algorithms with a cell outage compensation (COC) algorithm that can be applied to both planes. Our COC solution utilizes an actor-critic-based reinforcement learning algorithm, which optimizes the capacity and coverage of the identified outage zone in a plane, by adjusting the antenna gain and transmission power of the surrounding BSs in that plane. The simulation results show that the proposed framework can detect both data and control cell outage and compensate for the detected outage in a reliable manner

    An Adaptive Partitioning Scheme for Sleep Scheduling and Topology Control in Wireless Sensor Networks

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    QoS BASED ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORK

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    A Wireless Sensor Networks (WSN) is composed of a large number of low-powered sensor nodes that are randomly deployed to collect environmental data. In a WSN, because of energy scarceness, energy efficient gathering of sensed information is one of the most critical issues. Thus, most of the WSN routing protocols found in the literature have considered energy awareness as a key design issue. Factors like throughput, latency and delay are not considered as critical issues in these protocols. However, emerging WSN applications that involve multimedia and imagining sensors require end-to-end delay within acceptable limits. Hence, in addition to energy efficiency, the parameters (delay, packet loss ratio, throughput and coverage) have now become issues of primary concern. Such performance metrics are usually referred to as the Quality of Service (QoS) in communication systems. Therefore, to have efficient use of a sensor node’s energy, and the ability to transmit the imaging and multimedia data in a timely manner, requires both a QoS based and energy efficient routing protocol. In this research work, a QoS based energy efficient routing protocol for WSN is proposed. To achieve QoS based energy efficient routing, three protocols are proposed, namely the QoS based Energy Efficient Clustering (QoSEC) for a WSN, the QoS based Energy Efficient Sleep/Wake Scheduling (QoSES) for a WSN, and the QoS based Energy Efficient Mobile Sink (QoSEM) based Routing for a Clustered WSN. Firstly, in the QoSEC, to achieve energy efficiency and to prolong network/coverage lifetime, some nodes with additional energy resources, termed as super-nodes, in addition to normal capability nodes, are deployed. Multi-hierarchy clustering is done by having super-nodes (acting as a local sink) at the top tier, cluster head (normal node) at the middle tier, and cluster member (normal node) at the lowest tier in the hierarchy. Clustering within normal sensor nodes is done by optimizing the network/coverage lifetime through a cluster-head-selection algorithm and a sleep/wake scheduling algorithm. QoSEC resolves the hot spot problem and prolongs network/coverage lifetime. Secondly, the QoSES addressed the delay-minimization problem in sleep/wake scheduling for event-driven sensor networks for delay-sensitive applications. For this purpose, QoSES assigns different sleep/wake intervals (longer wake interval) to potential overloaded nodes, according to their varied traffic load requirement defined a) by node position in the network, b) by node topological importance, and c) by handling burst traffic in the proximity of the event occurrence node. Using these heuristics, QoSES minimizes the congestion at nodes having heavy traffic loads and ultimately reduces end-to-end delay while maximizing the throughput. Lastly, the QoSEM addresses hot spot problem, delay minimization, and QoS assurance. To address hot-spot problem, mobile sink is used, that move in the network to gather data by virtue of which nodes near to the mobile sink changes with each movement, consequently hot spot problem is minimized. To achieve delay minimization, static sink is used in addition to the mobile sink. Delay sensitive data is forwarded to the static sink, while the delay tolerant data is sent through the mobile sink. For QoS assurance, incoming traffic is divided into different traffic classes and each traffic class is assigned different priority based on their QoS requirement (bandwidth, delay) determine by its message type and content. Furthermore, to minimize delay in mobile sink data gathering, the mobile sink is moved throughout the network based on the priority messages at the nodes. Using these heuristics, QoSEM incur less end-to-end delay, is energy efficient, as well as being able to ensure QoS. Simulations are carried out to evaluate the performance of the proposed protocols of QoSEC, QoSES and QoSEM, by comparing their performance with the established contemporary protocols. Simulation results have demonstrated that when compared with contemporary protocols, each of the proposed protocol significantly prolong the network and coverage lifetime, as well as improve the other QoS routing parameters, such as delay, packet loss ratio, and throughput

    Enabling Cyber Physical Systems with Wireless Sensor Networking Technologies

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    [[abstract]]Over the last few years, we have witnessed a growing interest in Cyber Physical Systems (CPSs) that rely on a strong synergy between computational and physical components. CPSs are expected to have a tremendous impact on many critical sectors (such as energy, manufacturing, healthcare, transportation, aerospace, etc) of the economy. CPSs have the ability to transform the way human-to-human, human-toobject, and object-to-object interactions take place in the physical and virtual worlds. The increasing pervasiveness of Wireless Sensor Networking (WSN) technologies in many applications make them an important component of emerging CPS designs. We present some of the most important design requirements of CPS architectures. We discuss key sensor network characteristics that can be leveraged in CPS designs. In addition, we also review a few well-known CPS application domains that depend on WSNs in their design architectures and implementations. Finally, we present some of the challenges that still need to be addressed to enable seamless integration of WSN with CPS designs.[[incitationindex]]SCI[[booktype]]ç´™
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