Special Issue "Environmental Wireless Sensor Networks"
A special issue of Journal of Sensor and Actuator Networks (ISSN 2224-2708).
Deadline for manuscript submissions: 1 October 2014
Dr. Kirk Martinez
Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, UK
Interests: wireless sensor networks; power management; environmental monitoring
Prof. Dr. Jane K. Hart
Geography and Environment University of Southampton Southampton SO17 1BJ, UK
Phone: (023) 8059 4615
Fax: (023) 8059 3295
Interests: glaciers and climate change; subglacial processes (experiments and sedimentology); environmental sensor networks
Wireless Sensor Networks design for earth science applications have led to an area of research often described as Environmental Sensor Networks. These have to tackle the often hostile environments being sensed, including volcanoes, oceans, forests, and glaciers.
This Special Issue will bring together papers that describe complete systems and their deployment, as well as key technological advances brought about by challenging conditions.
Topics of interest include, but are not limited to:
- radio communications for deployed WSNs
- energy management
- energy harvesting
- data management
- user-centered design and interfaces
- system management
- novel platforms and hardware
- autonomous behavior
- use of 6LowPan in real-world deployments
Dr. Kirk Martinez
Prof. Dr. Jane K. Hart
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Sensor and Actuator Networks is an international peer-reviewed Open Access quarterly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 300 CHF (Swiss Francs). English correction and/or formatting fees of 250 CHF (Swiss Francs) will be charged in certain cases for those articles accepted for publication that require extensive additional formatting and/or English corrections.
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: WDFS: A Distributed Data Sharing System for In-Network Processing
Authors: Joshua Kiepert and Sin Ming Loo
Affiliation: Department of Electrical and Computer Engineering, Boise State University, Boise, ID 83725, USA
Abstract: Wireless sensor networks (WSNs) have emerged as versatile platforms for a wide range of scientific data acquisition applications. WSN systems are utilized in many application domains including: environmental monitoring, target tracking, surveillance, personal health monitoring, and many others. Current research efforts are moving toward WSN system designs which enable direct in-network processing of acquired sensor data to avoid the high energy costs associated with the bulk transmission of data to outside systems for processing. Implementation of collaborative in-network processing algorithms is a non-trivial issue for WSN system development. Design complexity for in-network processing algorithms is compounded by the fact that there are few frameworks available to enable general purpose, energy-aware, data sharing within WSN environments. This article presents a novel WSN communications and data sharing framework called Wireless sensor network Distributed File System (WDFS), which is designed to enable general purpose collaborative in-network sensor data processing. WDFS presents a common symbolic distributed file system that provides virtual views which uniquely present sensor data, node characteristics, and network topology to each sensor node in the network. The features provided by WDFS significantly simplify the development and implementation of in-network collaborative processing algorithms needed for data aggregation, sensor data analysis, and sensor data fusion applications within WSN systems.
Title: Context-Aware Optimization of Sensor Network Deployment
Authors: Meysam Argany 1, Mir Abolfazl Mostafavi 1, Christian Gagné 2
Affiliations: 1 Center for Research in Geomatics, Laval University, Quebec, Canada
2 Department of Electrical Engineering and Computer Engineering, Laval University, Quebec, Canada
Abstract: Adequate coverage is an important issue in sensor networks in order to fulfill the sensing applications. For this purpose different optimization methods are widely used for deployment of sensor networks to achieve a desired level of coverage. Most of these algorithms suffer from over simplification of the sensing environment. In this paper, we study the problem of placing sensors to get optimum coverage by integrating contextual information in optimization algorithms, and introduce a local context-aware sensor network deployment optimization method. Finally we present the obtained results that show the effectiveness of the proposed approach
Type of Paper: Review
Title: On the Modeling of Solar-Powered Wireless Sensor Nodes
Authors: Sebastian Bader, Xinyu Ma and Bengt Oelmann
Affiliations: Department of Electronics Design, Mid Sweden University, Sundsvall, Sweden
Abstract: Solar energy harvesting allows for wireless sensor networks to be operated over extended periods of time. In order to select an appropriate harvesting architecture and dimension its components, an effective method for the comparison of system implementations is required. System simulations have the capability to accomplish this in an accurate and efficient manner. In this paper, we evaluate the existing work on solar energy harvesting architectures and common methods for their modeling. An analysis of the existing approaches demonstrates a mismatch between the requirement to be both accurate and efficient, and the proposed modeling methods, which are either accurate or efficient. As a result, we propose a data-driven modeling method based on artificial neural networks. Preliminary results of an initial investigation demonstrate the capability of this method to accurately capture the behavior of a solar energy harvesting architecture, while providing a time-efficient model generation procedure.
Last update: 26 June 2014