Coverage Protocols for Wireless Sensor Networks: Review and Future Directions

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

Knowledge Discovery in the SCADA Databases Used for the Municipal Power Supply System

This scientific paper delves into the problems related to the develop-ment of intellectual data analysis system that could support decision making to manage municipal power supply services. The management problems of mu-nicipal power supply system have been specified taking into consideration modern tendencies shown by new technologies that allow for an increase in the energy efficiency. The analysis findings of the system problems related to the integrated computer-aided control of the power supply for the city have been given. The consideration was given to the hierarchy-level management decom-position model. The objective task targeted at an increase in the energy effi-ciency to minimize expenditures and energy losses during the generation and transportation of energy carriers to the Consumer, the optimization of power consumption at the prescribed level of the reliability of pipelines and networks and the satisfaction of Consumers has been defined. To optimize the support of the decision making a new approach to the monitoring of engineering systems and technological processes related to the energy consumption and transporta-tion using the technologies of geospatial analysis and Knowledge Discovery in databases (KDD) has been proposed. The data acquisition for analytical prob-lems is realized in the wireless heterogeneous medium, which includes soft-touch VPN segments of ZigBee technology realizing the 6LoWPAN standard over the IEEE 802.15.4 standard and also the segments of the networks of cellu-lar communications. JBoss Application Server is used as a server-based plat-form for the operation of the tools used for the retrieval of data collected from sensor nodes, PLC and energy consumption record devices. The KDD tools are developed using Java Enterprise Edition platform and Spring and ORM Hiber-nate technologies

A Systematic Approach to Constructing Incremental Topology Control Algorithms Using Graph Transformation

Communication networks form the backbone of our society. Topology control algorithms optimize the topology of such communication networks. Due to the importance of communication networks, a topology control algorithm should guarantee certain required consistency properties (e.g., connectivity of the topology), while achieving desired optimization properties (e.g., a bounded number of neighbors). Real-world topologies are dynamic (e.g., because nodes join, leave, or move within the network), which requires topology control algorithms to operate in an incremental way, i.e., based on the recently introduced modifications of a topology. Visual programming and specification languages are a proven means for specifying the structure as well as consistency and optimization properties of topologies. In this paper, we present a novel methodology, based on a visual graph transformation and graph constraint language, for developing incremental topology control algorithms that are guaranteed to fulfill a set of specified consistency and optimization constraints. More specifically, we model the possible modifications of a topology control algorithm and the environment using graph transformation rules, and we describe consistency and optimization properties using graph constraints. On this basis, we apply and extend a well-known constructive approach to derive refined graph transformation rules that preserve these graph constraints. We apply our methodology to re-engineer an established topology control algorithm, kTC, and evaluate it in a network simulation study to show the practical applicability of our approachComment: This document corresponds to the accepted manuscript of the referenced journal articl

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Smart FRP Composite Sandwich Bridge Decks in Cold Regions

INE/AUTC 12.0

Cobertura Fornecendo em Redes de Sensores Direcionais através de Algoritmos de Aprendizagem (Autômatos de Aprendizagem)

Today, wireless sensor networks due to application development are widely used. There are significant issues in these networks; they can be more effective if they would be fixed. One of these problems is the low coverage of these networks due to their low power. If coverage increases only by increasing the power of sending and receiving power, it can increase network consumption as a catastrophic disaster, while the lack of energy is one of the most important constraints on these networks. To do this, the antenna coverage is oriented in some sensor networks to cover the most important places. This method tries to improves the efficiency and coverage of directional sensor networks by providing a mechanism based on the learning algorithm of the machine called learning automata. Results show this method outperform the before methods at least 20%.Hoy en día, las redes de sensores inalámbricos debido al desarrollo de aplicaciones son ampliamente utilizadas. Hay problemas importantes en estas redes; pueden ser más efectivos si se solucionan. Uno de estos problemas es la baja cobertura de estas redes debido a su baja potencia. Si la cobertura aumenta solo elevando la potencia de envío y recepción de energía, puede aumentar el consumo de red como un desastre catastrófico, mientras que la falta de energía es una de las limitaciones más importantes de estas redes. Para hacer esto, la cobertura de la antena está orientada en algunas redes de sensores para cubrir los lugares más importantes. Este método intenta mejorar la eficiencia y la cobertura de las redes de sensores direccionales al proporcionar un mecanismo basado en el algoritmo de aprendizaje de la máquina denominado autómatas de aprendizaje. Los resultados muestran que este método supera los métodos anteriores al menos un 20%.Hoy en día, as redes de sensores inalámbricos debitaram o desenvolvimento de aplicações sonoras extensamente utilizadas. Obras do feno importantes nas redes; pueden ser más effectivos e se solucionan. Uns de esos protes es la baja cobertura de es redes debido a su baja potencia. Se a porta leva sozinho a aumentar a potência de envio e a recepção de energia, aumentar o consumo de energia como um desastre catastrófico, a falta de energia de energia é uma das limitações mais importantes destas redes. Para hacer esto, a cobertura da antena está orientada nas algunas redes de sensores para cubrir os lugares mais importantes. This method intenta mejor a eficiencia and the coverage of the networks of sensors directionals are provided in engine based on the algorithm of aprendizado of the machine denominado autómatas de aprendizaje. Los resultados muestran que este método supera os métodos anteriores a menos de 20%