247 research outputs found

    Lifetime Maximization of Sensor Networks Through Optimal Data Collection Scheduling of Mobile Sink

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    The problem of maximizing lifetime of a sensor network is still challenging mainly due to the stringent delay-deadline of real-time applications and heterogeneity of sensor devices. The problem is further complicated when the network contains many obstacles. In maximizing network lifetime, existing literature works either merely address issues of application delay-deadline and presence of obstacles, or analyze primitive data collection approaches for such an environment. In this paper, we formulate optimal data collection schedule of a mobile sink in an obstructed sensor network as a mixed-integer linear programming (MILP) problem. The proposed data collection scheduling finds an optimal set of rendezvous nodes over a preformed Starfish routing backbone, and corresponding sojourn duration so as to maximize the network lifetime while maintaining delay-deadline constraint in an obstructed network. The proposed Starfish-scheduling ensures a loop-free traveling path for a mobile sink across the network. The results of performance evaluation, performed in network simulator-2, depict the suitability of Starfish scheduling as it outperforms state-of-the-art-works in terms of extending network lifetime and data delivery throughput as well as reducing average end-to-end delay

    Multi-dimensional data indexing and range query processing via Voronoi diagram for internet of things

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    In a typical Internet of Things (IoT) deployment such as smart cities and Industry 4.0, the amount of sensory data collected from physical world is significant and wide-ranging. Processing large amount of real-time data from the diverse IoT devices is challenging. For example, in IoT environment, wireless sensor networks (WSN) are typically used for the monitoring and collecting of data in some geographic area. Spatial range queries with location constraints to facilitate data indexing are traditionally employed in such applications, which allows the querying and managing the data based on SQL structure. One particular challenge is to minimize communication cost and storage requirements in multi-dimensional data indexing approaches. In this paper, we present an energy- and time-efficient multidimensional data indexing scheme, which is designed to answer range query. Specifically, we propose data indexing methods which utilize hierarchical indexing structures, using binary space partitioning (BSP), such as kd-tree, quad-tree, k-means clustering, and Voronoi-based methods to provide more efficient routing with less latency. Simulation results demonstrate that the Voronoi Diagram-based algorithm minimizes the average energy consumption and query response time

    Recent Trends in Communication Networks

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    In recent years there has been many developments in communication technology. This has greatly enhanced the computing power of small handheld resource-constrained mobile devices. Different generations of communication technology have evolved. This had led to new research for communication of large volumes of data in different transmission media and the design of different communication protocols. Another direction of research concerns the secure and error-free communication between the sender and receiver despite the risk of the presence of an eavesdropper. For the communication requirement of a huge amount of multimedia streaming data, a lot of research has been carried out in the design of proper overlay networks. The book addresses new research techniques that have evolved to handle these challenges

    Project Final Report: Ubiquitous Computing and Monitoring System (UCoMS) for Discovery and Management of Energy Resources

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    Efficient algorithms for MAC layer duty cycling and frame delivery in wireless sensor network

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    In Wireless Sensor Networks, with small, limited capacity devices now more prevalent, the issue of Neighbour Discovery has shifted. These devices utilise duty cycling methods in order to conserve battery power. Hence, the main issue is now that these devices may be awake at the same time in order to discover each other. When mobility increases complexity further. Rather than attempt to negate the issue of mobility, instead this thesis seeks to utilise a predictable sink mobility pattern in order to influence the duty cycling of static nodes. Literature demonstrates a move towards Mobility Awareness in Neighbour Discovery in mobile Wireless Sensor Networks. However, there is a gap identified with sink mobility in use. Therefore, this thesis aims to establish to what extent the mobility pattern of a Mobile Sink Node in a Wireless Sensor Network may be exploited at the MAC layer, to influence the performance of static nodes. Such that network efficiency may be improved with energy consumption reduced and balanced across nodes. This study proposes three novel lightweight algorithms, with processing which does not add to the energy consumption within sensor nodes, these being Mobility Aware Duty Cycling Algorithm (MADCAL), Mobility Aware Duty Cycling and Dynamic Preambling Algorithm (MADCaDPAL) and Dynamic Mobility and Energy Aware Algorithm (DMEAAL). These located in the MAC layer of static nodes and utilising knowledge of predictable sink node mobility. This is in order to create a dynamic communication threshold between static nodes on the sink path and the sink itself. Subsequently lessening competition for sink communication between nodes. In MADCAL this threshold is used to influence the sleep function in order that static nodes only awake and move to Clear Channel Assessment once the sink is within their threshold, improving energy consumption by up to 15%. The MADCaDPAL algorithm takes this approach further, using the threshold to directly influence Clear Channel Assessment and the sending of preambles, as such, closing off the threshold when the sink leaves it. This shows energy consumption lessening by close to 80% with a significant improvement in frame delivery to the sink. Finally, the DMEAAL algorithm utilises previous results to influence energy consumption in real-time by utilising a cross-layer approach, comparing current consumption to optimal target energy consumption and adjusting the threshold for each static node accordingly. This shows benefit in evening out results across nodes, thus improving network lifetime. All algorithms are achieved without the energy-consuming beacon messaging associated with Neighbour Discovery. Analysis and simulation results, tested on a lightweight implementation of a carrier-sense multiple-access-based MAC protocol, show a significant improvement in energy consumption and frame delivery in both controlled and random environments. In utilising a cross-layer approach to access energy consumption in static nodes, is it also shown to be possible to even out energy consumption across nodes by altering the communication threshold in real-time. As such, improving network lifetime by removing spikes in energy consumption in individual nodes

    Smart Wireless Sensor Networks

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    The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks

    Data Quality Management in Large-Scale Cyber-Physical Systems

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    Cyber-Physical Systems (CPSs) are cross-domain, multi-model, advance information systems that play a significant role in many large-scale infrastructure sectors of smart cities public services such as traffic control, smart transportation control, and environmental and noise monitoring systems. Such systems, typically, involve a substantial number of sensor nodes and other devices that stream and exchange data in real-time and usually are deployed in uncontrolled, broad environments. Thus, unexpected measurements may occur due to several internal and external factors, including noise, communication errors, and hardware failures, which may compromise these systems quality of data and raise serious concerns related to safety, reliability, performance, and security. In all cases, these unexpected measurements need to be carefully interpreted and managed based on domain knowledge and computational models. Therefore, in this research, data quality challenges were investigated, and a comprehensive, proof of concept, data quality management system was developed to tackle unaddressed data quality challenges in large-scale CPSs. The data quality management system was designed to address data quality challenges associated with detecting: sensor nodes measurement errors, sensor nodes hardware failures, and mismatches in sensor nodes spatial and temporal contextual attributes. Detecting sensor nodes measurement errors associated with the primary data quality dimensions of accuracy, timeliness, completeness, and consistency in large-scale CPSs were investigated using predictive and anomaly analysis models via utilising statistical and machine-learning techniques. Time-series clustering techniques were investigated as a feasible mean for detecting long-segmental outliers as an indicator of sensor nodes’ continuous halting and incipient hardware failures. Furthermore, the quality of the spatial and temporal contextual attributes of sensor nodes observations was investigated using timestamp analysis techniques. The different components of the data quality management system were tested and calibrated using benchmark time-series collected from a high-quality, temperature sensor network deployed at the University of East London. Furthermore, the effectiveness of the proposed data quality management system was evaluated using a real-world, large-scale environmental monitoring network consisting of more than 200 temperature sensor nodes distributed around London. The data quality management system achieved high accuracy detection rate using LSTM predictive analysis technique and anomaly detection associated with DBSCAN. It successfully identified timeliness and completeness errors in sensor nodes’ measurements using periodicity analysis combined with a rule engine. It achieved up to 100% accuracy in detecting potentially failed sensor nodes using the characteristic-based time-series clustering technique when applied to two days or longer time-series window. Timestamp analysis was adopted effectively for evaluating the quality of temporal and spatial contextual attributes of sensor nodes observations, but only within CPS applications in which using gateway modules is possible

    Dagstuhl News January - December 2011

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    "Dagstuhl News" is a publication edited especially for the members of the Foundation "Informatikzentrum Schloss Dagstuhl" to thank them for their support. The News give a summary of the scientific work being done in Dagstuhl. Each Dagstuhl Seminar is presented by a small abstract describing the contents and scientific highlights of the seminar as well as the perspectives or challenges of the research topic
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