9,765 research outputs found
A Survey on Communication Networks for Electric System Automation
Published in Computer Networks 50 (2006) 877–897, an Elsevier journal. The definitive version of this publication is available from Science Direct. Digital Object Identifier:10.1016/j.comnet.2006.01.005In today’s competitive electric utility marketplace, reliable and real-time information become the key factor for reliable delivery of power to the end-users, profitability of the electric utility and customer satisfaction. The operational and commercial demands of electric utilities require a high-performance data communication network that supports both existing functionalities and future operational requirements. In this respect, since such a communication network constitutes the core of the electric system automation applications, the design of a cost-effective and reliable network architecture is crucial.
In this paper, the opportunities and challenges of a hybrid network architecture are discussed for electric system automation.
More specifically, Internet based Virtual Private Networks, power line communications, satellite communications and wireless communications (wireless sensor networks, WiMAX and wireless mesh networks) are described in detail. The motivation of this paper is to provide a better understanding of the hybrid network architecture that can provide heterogeneous electric system automation application requirements. In this regard, our aim is to present a structured framework for electric utilities who plan to utilize new communication technologies for automation and hence, to make the decision making process more effective and direct.This work was supported by NEETRAC under
Project #04-157
Wireless industrial monitoring and control networks: the journey so far and the road ahead
While traditional wired communication technologies have played a crucial role in industrial monitoring and control networks over the past few decades, they are increasingly proving to be inadequate to meet the highly dynamic and stringent demands of today’s industrial applications, primarily due to the very rigid nature of wired infrastructures. Wireless technology, however, through its increased pervasiveness, has the potential to revolutionize the industry, not only by mitigating the problems faced by wired solutions, but also by introducing a completely new class of applications. While present day wireless technologies made some preliminary inroads in the monitoring domain, they still have severe limitations especially when real-time, reliable distributed control operations are concerned. This article provides the reader with an overview of existing wireless technologies commonly used in the monitoring and control industry. It highlights the pros and cons of each technology and assesses the degree to which each technology is able to meet the stringent demands of industrial monitoring and control networks. Additionally, it summarizes mechanisms proposed by academia, especially serving critical applications by addressing the real-time and reliability requirements of industrial process automation. The article also describes certain key research problems from the physical layer communication for sensor networks and the wireless networking perspective that have yet to be addressed to allow the successful use of wireless technologies in industrial monitoring and control networks
Lifetime Improvement in Wireless Sensor Networks via Collaborative Beamforming and Cooperative Transmission
Collaborative beamforming (CB) and cooperative transmission (CT) have
recently emerged as communication techniques that can make effective use of
collaborative/cooperative nodes to create a virtual
multiple-input/multiple-output (MIMO) system. Extending the lifetime of
networks composed of battery-operated nodes is a key issue in the design and
operation of wireless sensor networks. This paper considers the effects on
network lifetime of allowing closely located nodes to use CB/CT to reduce the
load or even to avoid packet-forwarding requests to nodes that have critical
battery life. First, the effectiveness of CB/CT in improving the signal
strength at a faraway destination using energy in nearby nodes is studied.
Then, the performance improvement obtained by this technique is analyzed for a
special 2D disk case. Further, for general networks in which
information-generation rates are fixed, a new routing problem is formulated as
a linear programming problem, while for other general networks, the cost for
routing is dynamically adjusted according to the amount of energy remaining and
the effectiveness of CB/CT. From the analysis and the simulation results, it is
seen that the proposed method can reduce the payloads of energy-depleting nodes
by about 90% in the special case network considered and improve the lifetimes
of general networks by about 10%, compared with existing techniques.Comment: Invited paper to appear in the IEE Proceedings: Microwaves, Antennas
and Propagation, Special Issue on Antenna Systems and Propagation for Future
Wireless Communication
Gossip Algorithms for Distributed Signal Processing
Gossip algorithms are attractive for in-network processing in sensor networks
because they do not require any specialized routing, there is no bottleneck or
single point of failure, and they are robust to unreliable wireless network
conditions. Recently, there has been a surge of activity in the computer
science, control, signal processing, and information theory communities,
developing faster and more robust gossip algorithms and deriving theoretical
performance guarantees. This article presents an overview of recent work in the
area. We describe convergence rate results, which are related to the number of
transmitted messages and thus the amount of energy consumed in the network for
gossiping. We discuss issues related to gossiping over wireless links,
including the effects of quantization and noise, and we illustrate the use of
gossip algorithms for canonical signal processing tasks including distributed
estimation, source localization, and compression.Comment: Submitted to Proceedings of the IEEE, 29 page
Robotic Wireless Sensor Networks
In this chapter, we present a literature survey of an emerging, cutting-edge,
and multi-disciplinary field of research at the intersection of Robotics and
Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor
Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system
that aims to achieve certain sensing goals while meeting and maintaining
certain communication performance requirements, through cooperative control,
learning and adaptation. While both of the component areas, i.e., Robotics and
WSN, are very well-known and well-explored, there exist a whole set of new
opportunities and research directions at the intersection of these two fields
which are relatively or even completely unexplored. One such example would be
the use of a set of robotic routers to set up a temporary communication path
between a sender and a receiver that uses the controlled mobility to the
advantage of packet routing. We find that there exist only a limited number of
articles to be directly categorized as RWSN related works whereas there exist a
range of articles in the robotics and the WSN literature that are also relevant
to this new field of research. To connect the dots, we first identify the core
problems and research trends related to RWSN such as connectivity,
localization, routing, and robust flow of information. Next, we classify the
existing research on RWSN as well as the relevant state-of-the-arts from
robotics and WSN community according to the problems and trends identified in
the first step. Lastly, we analyze what is missing in the existing literature,
and identify topics that require more research attention in the future
Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications
Wireless sensor networks monitor dynamic environments that change rapidly
over time. This dynamic behavior is either caused by external factors or
initiated by the system designers themselves. To adapt to such conditions,
sensor networks often adopt machine learning techniques to eliminate the need
for unnecessary redesign. Machine learning also inspires many practical
solutions that maximize resource utilization and prolong the lifespan of the
network. In this paper, we present an extensive literature review over the
period 2002-2013 of machine learning methods that were used to address common
issues in wireless sensor networks (WSNs). The advantages and disadvantages of
each proposed algorithm are evaluated against the corresponding problem. We
also provide a comparative guide to aid WSN designers in developing suitable
machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial
A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks
In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs
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