Distributed Sensor Network Applications Research Articles

Wireless power transfer and energy harvesting in distributed sensor networks: Survey, opportunities, and challenges

Distributed sensor networks have emerged as part of the advancements in sensing and wireless technologies and currently support several applications, including continuous environmental monitoring, surveillance, tracking, and so on which are running in wireless sensor network environments, and large-scale wireless sensor network multimedia applications that require large amounts of data transmission to an access point. However, these applications are often hampered because sensor nodes are energy-constrained, low-powered, with limited operational lifetime and low processing and limited power-storage capabilities. Current research shows that sensors deployed for distributed sensor network applications are low-power and low-cost devices characterized with multifunctional abilities. This contributes to their quick battery drainage, if they are to operate for long time durations. Owing to the associated cost implications and mode of deployments of the sensor nodes, battery recharging/replacements have significant disadvantages. Energy harvesting and wireless power transfer have therefore become very critical for applications running for longer time durations. This survey focuses on presenting a comprehensive review of the current literature on several wireless power transfer and energy harvesting technologies and highlights their opportunities and challenges in distributed sensor networks. This review highlights updated studies which are specific to wireless power transfer and energy harvesting technologies, including their opportunities, potential applications, limitations and challenges, classifications and comparisons. The final section presents some practical considerations and real-time implementation of a radio frequency–based energy harvesting wireless power transfer technique using Powercast™ power harvesters, and performance analysis of the two radio frequency–based power harvesters is discussed. Experimental results show both short-range and long-range applications of the two radio frequency–based energy harvesters with high power transfer efficiency.

A graph based approach to supporting software reconfiguration in distributed sensor network applications

Considerable research has been performed in applying run-time reconfigurable component models to wireless sensor networks. The capability to dynamically deploy or update software components allows the changing requirements of sensor network applications to be effectively managed, while concrete interface definitions promote re-use. Realizing distributed reconfiguration in wireless sensor networks is complicated by the inherently asynchronous and unreliable nature of sensor network environments. In such an environment, traditional, centralized approaches to achieving distributed reconfiguration are impractical. This paper introduces a graph-based approach to specifying the reconfiguration of software resources that may be distributed across multiple sensor networks. This approach requires application developers to specify only high-level reconfiguration graphs, which are then optimized and enacted in a hierarchical and autonomic manner. We demonstrate and evaluate our approach using a case-study scenario.

Distributed state estimation for a stochastic linear hybrid system over a sensor network

In this study, the authors consider the distributed state estimation problem of a stochastic linear hybrid system (SLHS) observed over a sensor network. The SLHS is a dynamical system with interacting continuous state dynamics described by stochastic linear difference equations and discrete state (or mode) transitions governed by a Markovian process with a constant transition matrix. Most existing hybrid estimation algorithms are based on a centralised architecture which is not suitable for distributed sensor network applications. Further, the existing distributed hybrid estimation algorithms are restrictive in sensor network topology, or approximate the consensus process among connected sensor agents. This study proposes a distributed hybrid state estimation algorithm based on the multiple model based approach augmented with the optimal consensus estimation algorithm which can locally process the state estimation and share the estimation information with the neighbourhood of each sensor agent. This shared information comprises local mode-conditioned state estimates and edge-error covariances, and is used to bring about an agreement or a consensus across the network. The proposed distributed hybrid state estimation algorithm is demonstrated with an illustrative aircraft tracking example.

Design of A High-speed Parallel LDPC Encoder

In this paper, the traditional BP decoding algorithm of LDPC code is investigated in detail. The large computation load is a shortcoming of traditional BP decoding algorithm, and an improved BP decoding algorithm is then proposed to deal with the problem. In the iterative decoding process, the wrong bit information only needs to be updated for the decoding algorithm, which consequently improves the efficiency and reduces time-delay of decoding. According to the improved BP decoding algorithm, the high-speed parallel encoder is designed, which can be used in various distributed sensor network applications. Furthermore, the error correction performance of this high speed parallel encoder in the Gaussian channel is studied. The simulation is provided to illustrate that the improved high speed parallel encoder has lower computational complexity and higher decoding speed based on the premise of a little decoding performance loss.

Wideband E-Shaped Microstrip Antenna for Wireless Sensor Networks

Problem statement: Wireless Sensor Networks (WSN) is currently receiving significant attention due to their unlimited potential. It is still very early in the lifetime of such systems and many research challenges exist, out of which one of the challenges is sensor processing and fusion under limited capacities, the most important component in sensor is its TX/RX antenna. Approach: For high-speed wireless local area networks and other wireless communication systems covering the 5.33-5.71 GHz frequency band. In this frequency band microstrip antennas have attracted with its low-profile in nature. Microstrip antenna was proposed to meet the challenges, which combines the advantages of compactness with the low cost and low profile of a patch antenna. Results: The key parameters governing the antenna optimization have been determined with the help of High Frequency Simulation Software (HFSS). As a consequence, 5.5GHz microstrip antenna with size 22×16×3.2 mm had been realized on duroid with 2.2. Conclusion: This combination of performance metrics is highly desirable for autonomous distributed sensor network applications where a small sensor node volume and excellent power efficiency are required.

Estimation in Gaussian Graphical Models Using Tractable Subgraphs: A Walk-Sum Analysis

Graphical models provide a powerful formalism for statistical signal processing. Due to their sophisticated modeling capabilities, they have found applications in a variety of fields such as computer vision, image processing, and distributed sensor networks. In this paper, we present a general class of algorithms for estimation in Gaussian graphical models with arbitrary structure. These algorithms involve a sequence of inference problems on tractable subgraphs over subsets of variables. This framework includes parallel iterations such as embedded trees, serial iterations such as block Gauss-Seidel, and hybrid versions of these iterations. We also discuss a method that uses local memory at each node to overcome temporary communication failures that may arise in distributed sensor network applications. We analyze these algorithms based on the recently developed walk-sum interpretation of Gaussian inference. We describe the walks ldquocomputedrdquo by the algorithms using walk-sum diagrams, and show that for iterations based on a very large and flexible set of sequences of subgraphs, convergence is guaranteed in walk-summable models. Consequently, we are free to choose spanning trees and subsets of variables adaptively at each iteration. This leads to efficient methods for optimizing the next iteration step to achieve maximum reduction in error. Simulation results demonstrate that these nonstationary algorithms provide a significant speedup in convergence over traditional one-tree and two-tree iterations.

Versatile robotic platform for structural health monitoring and surveillance

Utilizing robotic based reconfigurable nodal structural health monitoring systems has many advantages over static or human positioned sensor systems. However, creating a robot capable of traversing a variety of civil infrastructures is a difficult task, as these structures each have unique features and characteristics posing a variety of challenges to the robot design. This paper outlines the design and implementation of a novel robotic platform for deployment on ferromagnetic structures as an enabling structural health monitoring technology. The key feature of this design is the utilization of an attachment device which is an advancement of the common magnetic base found in the machine tool industry. By mechanizing this switchable magnetic circuit and redesigning it for light weight and compactness, it becomes an extremely efficient and robust means of attachment for use in various robotic and structural health monitoring applications. The ability to engage and disengage the magnet as needed, the very low power required to do so, the variety of applicable geometric configurations, and the ability to hold indefinitely once engaged make this device ideally suited for numerous robotic and distributed sensor network applications. Presented here are examples of the mechanized variable force magnets, as well as a prototype robot which has been successfully deployed on a large construction site. Also presented are other applications and future directions of this technology.

Protecting mobile code in the wild

Proposed applications for mobile code systems include autonomous shopping agents, autonomic systems, distributed sensor network applications, and interstellar space networks. I argue the case for mobile code systems as the next-generation distributed programming paradigm and discuss the security problems that must be addressed before this vision is practically realizable. The security discussion will focus on protecting mobile code programs that execute in the wild from malicious actions by remote hosts.