• The KIPS Transactions:PartC
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• v.13C no.6 s.109
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• pp.741-748
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• 2006

Due to the continuous development of sensor technology, Wireless Sensor Networks are rapidly growing and are expected to be applied to various applications. One of the most important factors in Wireless Sensor Networks is energy-efficient management of network resources. For this purpose, a lot of researches have been ongoing in the development of energy-efficient routing protocol. In this paper, a cluster head selection algorithm considering node density in addition to the cluster head selection algorithm of LEACH-C is proposed and simulated. This algorithm gives nearly the same computational speed compared to that of LEACH-C and shows improvement of network lifetime about 11% better than LEACH-C. The simulation result shows that consideration of density as well as distance between nodes in cluster head selection can be more energy-efficient than considering only the distance between nodes as LEACH-C in energy usage of Wireless Sensor Networks.

• Journal of Internet Computing and Services
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• v.10 no.3
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• pp.61-69
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• 2009

Most existing clustering protocols have been aimed to provide balancing the residual energy of each node and maximizing life-time of wireless sensor networks. In this paper, we present the threshold based cluster head replacement strategy for clustering protocols in wireless sensor networks. This protocol minimizes the number of cluster head selection by preventing the cluster head replacement up to the threshold of residual energy. Reducing the amount of head selection and replacement cost, the life-time of the entire networks can be extended compared with the existing clustering protocols. Our simulation results show that our protocol outperformed than LEACH in terms of balancing energy consumption and network life-time.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.154-161
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• 2010

The properties of sensor node having a restricted energy in WSN have a difficult in various application fields to apply. Our paper proposed the cluster head selection which is an effective energy in order to manage in wireless sensor network. The proposed algorithm improves an energy efficient and is applied to various network environment considering energy capacity between cluster head and nodes and distance between cluster head and base station(sink node). By using the ns-2 simulator, we evaluate the performance of the proposed scheme in comparison with the original LEACH-C. Experimental results validate our scheme, showing a better performance than original LEACH-C in terms of the number of outliving nodes and the quantity of energy consumption as time evolves.

• International journal of advanced smart convergence
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• v.6 no.3
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• pp.53-58
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• 2017

A WSN (Wireless Sensor Network) is a network that is composed of wireless sensor nodes. There is no restriction on the place where it can be installed because it is composed wirelessly. Instead, sensor nodes have limited energy. Therefore, to use the network for a long time, energy consumption should be minimized. Several protocols have been proposed to minimize energy consumption, and the typical protocol is the LEACH protocol. The LEACH protocol is a cluster-based protocol that minimizes energy consumption by dividing the sensor field into clusters. Depending on how you organize the clusters of sensor field, network lifetimes may increase or decrease. In this paper, we will improve the network lifetime by improving the cluster head selection method in LEACH Protocol.

• Proceedings of the IEEK Conference
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• summer
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• pp.330-333
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• 2004

Microsensor nodes is energy limited in sensor networks. If nodes had been stop in working, sensor network can't acquire sensing data in that area as well as routing path though the sensor can't be available. So, it's important to maximize the life of network in sensor network. In this paper, we look at communication protocol, which is modified by LEACH(Low-Energy Adaptive Clustering Hierarchy). We extend LEACH's stochastic cluster-head selection algorithm by a Position-based Selection (PB-Leach). This method is that the sink divides the topology into several areas and cluster head is only one in an area. PB-Leach can prevent that the variance of the number of Cluster-Head is large and Cluster-Heads are concentrated in specific area. Simulation results show that PB-Leach performs better than leach by about 100 to $250\%.$

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.127-132
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• 2008

Wireless sensor network technologies applicable to various industrial fields are rapidly growing. Because it is difficult to change a battery for the once distributed wireless sensor network, energy efficient design is very critical. In order to achieve this purpose in network design, a number of studies have been examining the energy efficient routing protocol. The sensor network consumes energy in proportion to the distance of data transmission and the data to send. Cluster-based routing Protocols such as LEACH-C achieve energy efficiency through minimizing the distance of data transmission. In LEACH-C, however, the total distance between the nodes consisting the clusters are considered important in constructing clustering. This paper examines the cluster-head-selection-algorithm that reflect the distance between the base station and the cluster-head having a big influence on energy consumption. The Proposed method in this paper brought the result that the performance improved average $4{\sim}7%$ when LEACH-C and the base station are located beyond a certain distance. This result showed that the distance between cluster-head and the base station had a substantial influence on lifetime performance in the cluster-based routing protocol.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.3
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• pp.180-190
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• 2011

Efficient energy consumption is a critical factor for deployment and operation of wireless sensor networks (WSNs). To achieve energy efficiency there have been several hierarchical routing protocols that organize sensors into clusters where one sensor is a cluster-head to forward messages received from its cluster-member sensors to the base station of the WSN. In this paper, we propose a self-organized clustering method for cluster-head selection and cluster based routing for a WSN. To select cluster-heads and organize clustermembers for each cluster, every sensor uses only local information and simple decision mechanisms which are aimed at configuring a self-organized system. By these self-organized interactions among sensors and selforganized selection of cluster-heads, the suggested method can form clusters for a WSN and decide routing paths energy efficiently. We compare our clustering method with a clustering method that is a well known routing protocol for the WSNs. In our computational experiments, we show that the energy consumptions and the lifetimes of our method are better than those of the compared method. The experiments also shows that the suggested method demonstrate properly some self-organized properties such as robustness and adaptability against uncertainty for WSN's.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.11
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• pp.1241-1248
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• 2014

An efficient battery usage of sensor nodes is main goal in a sensor network, which is the substructure of Internet of Things. Maximizing the battery usage of sensor nodes makes the lifetime of sensor network increase as well as the reliability of the network improved. The previous solutions to solve these problems are mainly focused on the cluster head selection based on the remaining energy. In this paper, we consider both the head selection and the replacement interval which is determined by a threshold that is based on the remaining energy, density of alive nodes, and location. Our simulation results show that the proposed scheme has outstanding contribution in terms of maximizing the life time of the network and balancing energy consumption of all nodes.

• The KIPS Transactions:PartC
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• v.14C no.3 s.113
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• pp.277-284
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• 2007

The routing algorithm many used in the wireless sensor network features the clustering method to reduce the amount of data transmission from the energy efficiency perspective. However, the clustering method results in high energy consumption at the cluster head node. Dynamic clustering is a method used to resolve such a problem by distributing energy consumption through the re-selection of the cluster head node. Still, dynamic clustering modifies the cluster structure every time the cluster head node is re-selected, which causes energy consumption. In other words, the dynamic clustering approaches examined in previous studies involve the repetitive processes of cluster head node selection. This consumes a high amount of energy during the set-up process of cluster generation. In order to resolve the energy consumption problem associated with the repetitive set-up, this paper proposes the Round-Robin Cluster Header (RRCH) method that fixes the cluster and selects the head node in a round-robin method The RRCH approach is an energy-efficient method that realizes consistent and balanced energy consumption in each node of a generated cluster to prevent repetitious set-up processes as in the LEACH method. The propriety of the proposed method is substantiated with a simulation experiment.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.141-150
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• 2005

Wireless Sensor Networks have been rapidly developed due to the advances of sensor technology and are expected to be applied to various applications in many fields. In Wireless Sensor Networks, schemes for managing the network energy-efficiently are most important. For this purpose, there have been a variety of researches to suggest routing protocols. However, existing researches have ideal assumption that all sensor nodes have sensing data to transmit. In this paper, we designed and implemented a sensing-aware cluster selection algorithm based on LEACH-C for the sensor network in which part of sensors have sensing data. We also simulated proposed algorithm on several network situation and analyzed which situation is suitable for the algorithm. By the simulation result, selecting cluster head among the sensing nodes is most energy-efficient and the result shows application of sensing-awareness in cluster head selection when not all sensors have sensing data.