• International Journal of Internet, Broadcasting and Communication
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• v.7 no.1
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• pp.23-29
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• 2015

Energy constraints of wireless sensor networks are an important challenge. Data Transmission requires energy. Distance between origin and destination has an important role in energy consumption. In addition, the location of base station has a large impact on energy consumption and a specific method not proposed for it. In addition, a obtain model for location of base station proposed. Also a model for distributed clustering is presented by cluster heads. Eventually, a combination of discussed ideas is proposed to improve the energy consumption. The proposed ideas have been implemented over the LEACH-C protocol. Evaluation results show that the proposed methods have a better performance in energy consumption and lifetime of the network in comparison with similar methods.

• ETRI Journal
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• v.41 no.3
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• pp.326-336
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• 2019

A wireless power transfer technique can solve the power capacity problem in wireless rechargeable sensor networks (WRSNs). The charging strategy is a wide-spread research problem. In this paper, we propose a demand-based charging strategy (DBCS) for WRSNs. We improved the charging programming in four ways: clustering method, selecting to-be-charged nodes, charging path, and charging schedule. First, we proposed a multipoint improved K-means (MIKmeans) clustering algorithm to balance the energy consumption, which can group nodes based on location, residual energy, and historical contribution. Second, the dynamic selection algorithm for charging nodes (DSACN) was proposed to select on-demand charging nodes. Third, we designed simulated annealing based on performance and efficiency (SABPE) to optimize the charging path for a mobile charging vehicle (MCV) and reduce the charging time. Last, we proposed the DBCS to enhance the efficiency of the MCV. Simulations reveal that the strategy can achieve better performance in terms of reducing the charging path, thus increasing communication effectiveness and residual energy utility.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.1B
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• pp.10-15
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• 2009

Recently, there are tendency that wireless sensor network is one of the important techniques for the future IT industry and thereby application areas in it are getting growing. Researches based on the hierarchical network topology are evaluated in good at energy efficiency in related protocols for wireless sensor network. LEACH is the best well known routing protocol for the hierarchical topology. However, there are problems in the range of message broadcasting, which should be expand into the overall network coverage, in LEACH related protocols. Thereby, this paper proposes a new clustering scheme to solve the co-shared problems in them. The basic idea of our scheme is using the inherent memory restrictions in sensor nodes. The results show that the proposed scheme could support the load balancing by distributing the clusters with a reasonable number of member nodes and thereby the network life time would be extended in about 1.8 times longer than LEACH.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.913-916
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• 2010

Wireless sensor networks consist of small battery powered devices with limited energy resources. Once deployed, the small sensor nodes are usually inaccessible to the user, and thus replacement of the energy source is not feasible. Hence, energy efficiency is a key design issue that needs to be enhanced in order to improve the life span of the network. In BCDCP, all sensors send data from CH (Cluster Head) and then to BS (Base Station). BCDCP works well in small-scale network but in large scale network it is not appropriated since it uses much energy for long distance wireless communication. We propose a routing protocol - Triangular Clustering Routing Protocol (TCRP) - to prolong network life time through the balanced energy consumption. TCRP selects cluster head of triangular shape. The sensor field is divided into energy level and in every level we choose one node as a gate node. This gate node collects data and sends it to the leader node. Finally the leader node sends the aggregated data to the BS. We show TCRP outperforms BCDCP with several experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.11
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• pp.1170-1181
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• 2012

Wireless Sensor Networks(WSNs) are used in diverse applications. In general, sensor nodes that are easily deployed on specific areas have many resource constrains such as battery power, memory sizes, MCUs, RFs and so on. Hence, first of all, the efficient energy consumption is strongly required in WSNs. In terms of event states, event-driven deliverly model (i.e. surveillance and reconnaissance applications) has several characteristics. On the basis of such a model, clustering algorithms can be mostly used to manage sensor nodes' energy efficiently owing to the advantages of data aggregations. Since a specific node collects packets from its child nodes in a network topology and aggregates them into one packet to relay them once, amount of transmitted packets to a sink node can be reduced. However, most clustering algorithms have been designed without considering can be reduced. However, most clustering algorithms have been designed without considering characteristics of event-driven deliverly model, which results in some problems. In this paper, we propose enhanced clustering algorithms regarding with both targets' movement and energy efficiency in order for applications of surveillance and reconnaissance. These algorithms form some clusters to contend locally between nodes, which have already detected certain targets, by using a method which called CHEW (Cluster Head Election Window). Therefore, our proposed algorithms enable to reduce not only the cost of cluster maintenance, but also energy consumption. In conclusion, we analyze traces of the clusters' movements according to targets' locations, evaluate the traces' results and we compare our algorithms with others through simulations. Finally, we verify our algorithms use power energy efficiently.

• Journal of Korea Multimedia Society
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• v.12 no.11
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• pp.1609-1622
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• 2009

In wireless sensor networks, a clustering protocol is an efficient method to prolong network lifetime. In general, it results in more energy consumption at the cluster-head node. Hence, such a protocol must changes the cluster formation and cluster-head node in each round to prolong the network lifetime. But, this method also causes large amount of energy consumption during the set-up process of cluster formation. In order to improve energy efficiency, in this paper, we propose a new clustering algorithm. In this algorithm, we exclude duplicated data of adjacent nodes and transmits the threshold value. We define a group as the sensor nodes within close proximity of each other. In a group, a node senses and transmits data at a time on the round-robin basis. In a view of whole network, group is treated as one node. During the setup phase of a round, intra clusters are formed first and then they are re-clustered(network cluster) by choosing cluster-heads(group). In the group with a cluster-head, every member node plays the role of cluster-head on the round-robin basis. Hence, we can lengthen periodic round by a factor of group size. As a result of analysis and comparison, our scheme reduces energy consumption of nodes, and improve the efficiency of communications in sensor networks compared with current clustering methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3515-3538
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• 2015

Data accuracy can be increased by detecting and removing the incorrect data generated in wireless sensor networks. By increasing the data accuracy, network lifetime can be increased parallel. Network lifetime or operational time is the time during which WSN is able to fulfill its tasks by using microcontroller with on-chip memory radio transceivers, albeit distributed sensor nodes send summary of their data to their cluster heads, which reduce energy consumption gradually. In this paper a powerful algorithm using proactive fuzzy system is proposed and it is a mixture of fuzzy logic with comparative correlation techniques that ensure high data accuracy by detecting incorrect data in distributed wireless sensor networks. This proposed system is implemented in two phases there, the first phase creates input space partitioning by using robust fuzzy c means clustering and the second phase detects incorrect data and removes it completely. Experimental result makes transparent of combined correlated fuzzy system (CCFS) which detects faulty readings with greater accuracy (99.21%) than the existing one (98.33%) along with low false alarm rate.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.1
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• pp.1-11
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• 2020

Wireless sensor networks consist of a large number of tiny sensor nodes which have limited battery life. In order to maximize the network life span, we propose an optimal transmission radius, R, for control messages. We analyze the transmission radius as a function of the energy consumption of cluster head nodes and the energy consumption of member nodes to find the optimal value of R. In simulations we apply our proposed optimization of transmission range to LEACH-based single-hop and multi-hop networks to show that our proposed scheme outperforms other existing routing algorithms in terms of network life span.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.103-108
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• 2015

Maintaining efficient energy consumption and elongating network lifetime are the key issues in wireless sensor networks. Existing routing protocols usually select the cluster heads based on the proximity to the sensor nodes. In this case the cluster heads can be placed farther to the base station, than the distance between the sensor nodes and the base station, which yields inefficient energy consumption. In this work we propose a novel algorithm that select the nodes in a cluster and the cluster heads based on the locations of related nodes. We verify that the proposed algorithm gives better performance in terms of network life time than existing solutions.

• Journal of Sensor Science and Technology
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• v.17 no.6
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• pp.406-413
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• 2008

We have been implemented simple statistical pattern recognition methods for harmful gases classification using gas sensors array fabricated by MEMS (Micro Electro Mechanical System) technology. The performance of pattern recognition method as a gas classifier is highly dependent on the choice of pre-processing techniques for sensor and sensors array signals and optimal classification algorithms among the various classification techniques. We carried out pre-processing for each sensor's signal as well as sensors array signals to extract features for each gas. We adapted simple statistical pattern recognition algorithms, which were PCA (Principal Component Analysis) for visualization of patterns clustering and MLR (Multi-Linear Regression) for real-time system implementation, to classify harmful gases. Experimental results of adapted pattern recognition methods with pre-processing techniques have been shown good clustering performance and expected easy implementation for real-time sensing system.