• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2804-2823
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• 2013

Wireless sensor network (WSN) is a promising technology for monitoring physical phenomena at fine-grained spatial and temporal resolution. However, the typical approach of sending each sensed measurement out of the network for detailed spatial analysis of transient physical phenomena may not be an efficient or scalable solution. This paper focuses on in-network physical phenomena detection schemes, particularly the distributed computation of the boundary of physical phenomena (i.e. event), to support energy efficient spatial analysis in wireless sensor networks. In-network processing approach reduces the amount of network traffic and thus achieves network scalability and lifetime longevity. This study investigates the recent advances in distributed event detection based on in-network processing and includes a concise comparison of various existing schemes. These boundary detection schemes identify not only those sensor nodes that lie on the boundary of the physical phenomena but also the interior nodes. This constitutes an event geometry which is a basic building block of many spatial queries. In this paper, we introduce the challenges and opportunities for research in the field of in-network distributed event geometry boundary detection as well as illustrate the current status of research in this field. We also present new areas where the event geometry boundary detection can be of significant importance.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.780-786
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• 2012

Surveillance has become one of promising application areas of wireless sensor networks which allow for pervasive monitoring of concerned environmental phenomena by facilitating context awareness through sensor fusion. Existing systems that depend on a postmortem context analysis of sensor data on a centralized server expose several shortcomings, including a single point of failure, wasteful energy consumption due to unnecessary data transfer as well as deficiency of scalability. As an opposite direction, this paper proposes an energy-efficient distributed context-aware surveillance in which sensor nodes in the wireless sensor network collaborate with neighbors in a distributed manner to analyze and aware surrounding context. We design and implement multi-modal sensor stations for use as sensor nodes in our wireless sensor network implementing our distributed context awareness. This paper presents an initial experimental performance result of our proposed system. Results show that multi-modal sensor performance of our sensor station, a key enabling factor for distributed context awareness, is comparable to each independent sensor setting. They also show that its initial performance of context-awareness is satisfactory for a set of introductory surveillance scenarios in the current interim stage of our ongoing research.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.1
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• pp.123-131
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• 2011

In this paper, modeling and design of a distributed detection system are considered for an active sonar sensor network. The sensor network has a parallel configuration and it consists of a fusion center and a set of receiver nodes. A system with two receiver nodes is considered to investigate a theoretical aspect of design. To be specific, AND rule and OR rule are considered as the fusion rules of the sensor network. For the fusion rules, it is shown that a threshold rule of each sensor node has uniformly most powerful properties. Optimum threshold for each sensor is obtained that maximizes the probability of detection given probability of false alarm. Numerical experiments were also performed to investigate the detection characteristics of a distributed detection system with multiple sensor nodes. The experimental results show how signal strength, false alarm probability, and the distance between nodes in a sensor field affect the system detection performances.

• Journal of Sensor Science and Technology
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• v.28 no.5
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• pp.277-283
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• 2019

In this paper, we propose a distributed fusion estimation for sensor networks using a receding horizon strategy. Communication channels were modelled as Markov jump systems, and a posterior probability distribution for communication channel characteristics was calculated and incorporated into the filter to allow distributed fusion estimation to handle path loss observation situations automatically. To implement distributed fusion estimation, a Kalman-Consensus filter was then used to obtain the average consensus, based on the estimates of sensors randomly distributed across sensor networks. The advantages of the proposed algorithms were then verified using a large-scale sensor network example.

• ETRI Journal
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• v.33 no.5
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• pp.704-711
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• 2011

This paper proposes hybrid distributed stochastic addressing (HDSA), which combines the advantages of distributed addressing and stochastic addressing, to solve the problems encountered when constructing a network in a ZigBee-based wireless sensor network. HDSA can assign all the addresses for ZigBee beyond the limit of addresses assigned by the existing distributed address assignment mechanism. Thus, it can make the network scalable and can also utilize the advantages of tree routing. The simulation results reveal that HDSA has better addressing performance than distributed addressing and better routing performance than other on-demand routing methods.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.874-877
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• 2008

Nowadays the existing data processing systems can only support some simple query for sensor network. It is increasingly important to process the vast data streams in sensor network, and achieve effective acknowledges for users. In this paper, we propose a holistic distributed k-means algorithm for sensor network. In order to verify the effectiveness of this method, we compare it with central k-means algorithm to process the data streams in sensor network. From the evaluation experiments, we can verify that the proposed algorithm is highly capable of processing vast data stream with less computation time. This algorithm prefers to cluster the data streams at the distributed nodes, and therefore it largely reduces redundant data communications compared to the central processing algorithm.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.93-99
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• 2021

The sensor networks should be appropriately designed by applied network purpose, so that they can support proper application functions. Based on the design of suitable network model, the network lifetime can be maximized than using other general strategies which have not the consideration of specific network environments. In this paper, we propose a non-deterministic agent scheme to the mobile sink in distributed wireless sensor networks. The sensor network area can be divided into several sensor regions. Hence, to these such networks, the specified suitable scheme is requested by the applied network model to implement satisfactory network management. In this paper, we theoretically represent the proposed scheme, and provide the evaluation with the simulation results.

• ETRI Journal
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• v.31 no.5
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• pp.525-533
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• 2009

This paper proposes a distributed borrowing addressing (DIBA) scheme to solve problems of failure in address assignments resulting from limited tree depth and width when the distributed address assignment mechanism is used in a ZigBee/IEEE 802.15.4 wireless sensor network. DIBA is a method of borrowing addresses from neighbor nodes for newly entering nodes and assigning the borrowed addresses. Its network or sensing coverage can increase with almost the same overhead as the existing method. DIBA is a simple and lightweight means of addressing and routing, making it suitable for wireless sensor networks. Simulations showed that DIBA is a distributed addressing scheme with consistently excellent performance.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.4
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• pp.418-424
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• 2013

Both simulation and physical implementation are valuable tasks in sensor network routing protocols. In this paper, we propose an efficient underground utilities monitoring method within several constraints using wireless sensor network. First, in order to physically implement protocol of network which is applied, the distributed event-based simulation, which applies an existing nesC codes of sensor network routing protocols, is implemented and analyzed. Also, we have performed the simulation and analyzed the execution results for application model of routing protocols for monitoring underground utilities in the VIPTOS(Visual Ptolemy and TinyOS) environments which combine TOSSIM and Ptolemy II based on distributed event.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2134-2153
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• 2013

A network-coding-based scheme is proposed to improve the energy efficiency of distributed storage systems in WSNs (Wireless Sensor Networks). We mainly focus on two problems: firstly, consideration is given to effective distributed storage technology; secondly, we address how to effectively repair the data in failed storage nodes. For the first problem, we propose a method to obtain a sparse generator matrix to construct network codes, and this sparse generator matrix is proven to be the sparsest. Benefiting from this matrix, the energy consumption required to implement distributed storage is reduced. For the second problem, we designed a network-coding-based iterative repair method, which adequately utilizes the idea of re-encoding at intermediate nodes from network coding theory. Benefiting from the re-encoding, the energy consumption required by data repair is significantly reduced. Moreover, we provide an explicit lower bound of field size required by this scheme, which implies that it can work over a small field and the required computation overhead is very low. The simulation result verifies that the proposed scheme not only reduces the total energy consumption required to implement distributed storage system in WSNs, but also balances energy consumption of the networks.