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Special Issue "Semantic Sensor Network Technologies and Applications"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (15 March 2011).

Special Issue Editors

Prof. Dr. Young-Sik Jeong
E-Mail Website
Guest Editor
Department of Multimedia Engineering, Dongguk University, Seoul, Korea
Interests: Cloud computing, Ubiquitous computing, Internet of Things and M2M, Cyber physical system , Ubiquitous intelligent systems, Smart appliances
Special Issues and Collections in MDPI journals
Dr. Neal N. Xiong
E-Mail Website
Guest Editor
Department of Computer Science, Georgia State University, P.O. Box 2316, Atlanta, Georgia, 30303, USA
Interests: cloud computing, sensor networks, and semantic web

Published Papers (4 papers)

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Research

Open AccessArticle
Throughput Fairness Enhancement Using Differentiated Channel Access in Heterogeneous Sensor Networks
Sensors 2011, 11(7), 6629-6644; https://doi.org/10.3390/s110706629 - 27 Jun 2011
Cited by 3
Abstract
Nowadays, with wireless sensor networks (WSNs) being widely applied to diverse applications, heterogeneous sensor networks (HSNs), which can simultaneously support multiple sensing tasks in a common sensor field, are being considered as the general form of WSN system deployment. In HSNs, each application [...] Read more.
Nowadays, with wireless sensor networks (WSNs) being widely applied to diverse applications, heterogeneous sensor networks (HSNs), which can simultaneously support multiple sensing tasks in a common sensor field, are being considered as the general form of WSN system deployment. In HSNs, each application generates data packets with a different size, thereby resulting in fairness issues in terms of the network performance. In this paper, we present the design and performance evaluation of a differentiated channel access scheme (abbreviated to DiffCA) to resolve the fairness problem in HSNs. DiffCA achieves fair performance among the application groups by providing each node with an additional backoff counter, whose value varies according to the size of the packets. A mathematical model based on the discrete time Markov chain is presented and is analyzed to measure the performance of DiffCA. The numerical results show that the performance degradation of disadvantaged application groups can be effectively compensated for by DiffCA. Simulation results are given to verify the accuracy of the numerical model. Full article
(This article belongs to the Special Issue Semantic Sensor Network Technologies and Applications)
Open AccessArticle
Ontological Problem-Solving Framework for Dynamically Configuring Sensor Systems and Algorithms
Sensors 2011, 11(3), 3177-3204; https://doi.org/10.3390/s110303177 - 15 Mar 2011
Cited by 3
Abstract
The deployment of ubiquitous sensor systems and algorithms has led to many challenges, such as matching sensor systems to compatible algorithms which are capable of satisfying a task. Compounding the challenges is the lack of the requisite knowledge models needed to discover sensors [...] Read more.
The deployment of ubiquitous sensor systems and algorithms has led to many challenges, such as matching sensor systems to compatible algorithms which are capable of satisfying a task. Compounding the challenges is the lack of the requisite knowledge models needed to discover sensors and algorithms and to subsequently integrate their capabilities to satisfy a specific task. A novel ontological problem-solving framework has been designed to match sensors to compatible algorithms to form synthesized systems, which are capable of satisfying a task and then assigning the synthesized systems to high-level missions. The approach designed for the ontological problem-solving framework has been instantiated in the context of a persistence surveillance prototype environment, which includes profiling sensor systems and algorithms to demonstrate proof-of-concept principles. Even though the problem-solving approach was instantiated with profiling sensor systems and algorithms, the ontological framework may be useful with other heterogeneous sensing-system environments. Full article
(This article belongs to the Special Issue Semantic Sensor Network Technologies and Applications)
Open AccessArticle
An Efficient Transmission Power Control Scheme for Temperature Variation in Wireless Sensor Networks
Sensors 2011, 11(3), 3078-3093; https://doi.org/10.3390/s110303078 - 10 Mar 2011
Cited by 12
Abstract
Wireless sensor networks collect data from several nodes dispersed at remote sites. Sensor nodes can be installed in harsh environments such as deserts, cities, and indoors, where the link quality changes considerably over time. Particularly, changes in transmission power may be caused by [...] Read more.
Wireless sensor networks collect data from several nodes dispersed at remote sites. Sensor nodes can be installed in harsh environments such as deserts, cities, and indoors, where the link quality changes considerably over time. Particularly, changes in transmission power may be caused by temperature, humidity, and other factors. In order to compensate for link quality changes, existing schemes detect the link quality changes between nodes and control transmission power through a series of feedback processes, but these approaches can cause heavy overhead with the additional control packets needed. In this paper, the change of the link quality according to temperature is examined through empirical experimentation. A new power control scheme combining both temperature-aware link quality compensation and a closed-loop feedback process to adapt to link quality changes is proposed. We prove that the proposed scheme effectively adapts the transmission power to the changing link quality with less control overhead and energy consumption. Full article
(This article belongs to the Special Issue Semantic Sensor Network Technologies and Applications)
Open AccessCommunication
Smart Query Answering for Marine Sensor Data
Sensors 2011, 11(3), 2885-2897; https://doi.org/10.3390/s110302885 - 03 Mar 2011
Cited by 5
Abstract
We review existing query answering systems for sensor data. We then propose an extended query answering approach termed smart query, specifically for marine sensor data. The smart query answering system integrates pattern queries and continuous queries. The proposed smart query system considers [...] Read more.
We review existing query answering systems for sensor data. We then propose an extended query answering approach termed smart query, specifically for marine sensor data. The smart query answering system integrates pattern queries and continuous queries. The proposed smart query system considers both streaming data and historical data from marine sensor networks. The smart query also uses query relaxation technique and semantics from domain knowledge as a recommender system. The proposed smart query benefits in building data and information systems for marine sensor networks. Full article
(This article belongs to the Special Issue Semantic Sensor Network Technologies and Applications)
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