• Journal of the Korea Society of Computer and Information
• /
• v.13 no.6
• /
• pp.137-145
• /
• 2008

In general, a large-scale wireless sensor network(WSNs) is composed of hundreds of or thousands of sensor nodes. In this large-scale wireless sensor networks, it is required to maintain and manage the networks to lower management cost and obtain high energy efficiency. Users should be provided with sensing service at the level of quality for users through an efficient system. In evaluating the result data quality provided from this network to users, the number of sensors related to event detection has an important role. Accordingly, the network protocol which can provide proper QoS at the level of users demanding quality should be designed in a way such that the overall system function has not to be influenced even if some sensor nodes are in error. The energy consumption is minimized at the same time. The protocol suggested in this article is based on the LEACH protocol and is a role-based self-Organization one that is appropriate for large-scale networks which need constant monitoring.

• Proceedings of the Korean Information Science Society Conference
• /
• 2011.06a
• /
• pp.412-415
• /
• 2011

본 논문에서는 정적 무선 센서 네트워크상의 클러스터링 기법인 EECS(Energy Efficient Clustering Scheme)의 노드와 Base Station간의 거리를 고려한 head 선출 과정에 노드의 이동성 및 미래 위치 예측을 융합하여 확장한 새로운 동적환경상의 클러스터링 기법 EECS-M(Energy Efficient Clustering Scheme in Mobile wireless sensor networks)을 제안한다. 실험을 통하여 EECS-M이 동적 환경상의 LEACH-M, WCA 및 정적 환경상의 EECS, LEACH 클러스터링 알고리즘들에 비해 life time 및 life time 대비 네트워크의 잔여 에너지 측면에서 성능향상을 가진다는 것을 보인다.

• Proceedings of the SAREK Conference
• /
• 2009.06a
• /
• pp.459-464
• /
• 2009

This study has been conducted on how to determine the multi-evaporator vapor compression cycle system is charged correctly by using sensor readings which are used to control system. In this paper, the characteristics of the multi-evaporator were presented and sensor values were classified using fuzzy clustering. finally classification logic and it's performance were discussed by applying commercial VRF system.

• Proceedings of the KIEE Conference
• /
• 2008.07a
• /
• pp.1893-1894
• /
• 2008

Advances in hardware and wireless network technologies have placed us at the doorstep of a new era where small wireless devices will provide access to information anytime, anywhere as well as actively participate in creating smart environments. In this paper, we propose location-aware clustering method in wireless sensor networks. Previous clustering algorithm assumes that all nodes know its own location by GPS. But, it is unrealistic because of GPS module cost and large energy consumption. So, we operate localization ahead of cluster set-up phase. And Considering node density and geographic information, Cluster Heads are elected uniformly. Moreover, communication between CHs is prolonged network lifetime.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.405-405
• /
• 2000

We designed the artificial olfactory sensing system (Electronic Nose) using MOS type sensor array fur recognizing and analyzing odour. The response of individual sensors of sensor array, each processing a slightly different response towards the sample volatiles, can provide enough information to discriminate between sample odours. In this paper, we applied clustering algorithm for dimension reduction, such as linear projection mapping (PCA method), nonlinear mapping (Sammon mapping method) and the combination of PCA and Sammon mapping having a better discriminating ability. The odours used are VOC (Volatile chemical compound) and Toxic gases.

• Journal of Communications and Networks
• /
• v.16 no.4
• /
• pp.421-429
• /
• 2014

We consider the problem of scheduling communications in wireless sensor networks (WSNs) to ensure battery preservation through the use of the sleeping mode of sensors.We propose a communication protocol for 1-hop WSNs and extend it to multi-hop WSNs through the use of a 1-hop clustering algorithm.We propose to schedule communications in each cluster in a virtual communication ring so as to avoid collisions. Since clusters are cliques, only one sensor can speak or listen in a cluster at a time, and all sensors need to speak in each of their clusters at least once to realize the communication protocol. We model this situation as a mathematical program.

• Proceedings of the Korean Information Science Society Conference
• /
• 2005.07a
• /
• pp.427-429
• /
• 2005

Energy efficiency is the most challenging issue in wireless sensor network to prolong the life time of the network, as the sensors has to be unattended. Cluster based communication can reduce the traffic on the network and gives the opportunity to other sensors for periodic sleep and thus save energy. Passive clustering (PC) can perform a significant role to minimize the network load as it is less computational and light weight. First declaration wins method of PC without any priority generates severe collision in the network and forms the clusters very dense with large amount of overlapping region. We have proposed several modifications for the existing passive clustering algorithm to prolong the life time of the network with better cluster formation.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2008.11a
• /
• pp.1039-1042
• /
• 2008

Wireless sensor networks enable pervasive, ubiquitous, and seamless communication with the physical world. In this paper, we are concerned for clustering sensors into groups, so that sensors communicate information only to cluster heads and then the cluster heads communicate the aggregated information to the sink node, that the network can save energy. In this paper, we propose the algorithm for electing the cluster head and fuzzy registration of cluster head in a dynamic cluster wireless sensor networks. For making decision for clustering we will use fuzzy logic system. In simulation, we could achieve power regulation of total consumption and also the stabilization of the networks energy efficiency.

• Journal of information and communication convergence engineering
• /
• v.22 no.1
• /
• pp.1-6
• /
• 2024

Energy efficiency in wireless sensor networks (WSNs) is a critical issue because batteries are used for operation and communication. In terms of scalability, energy efficiency, data integration, and resilience, WSN-cluster-based routing algorithms often outperform routing algorithms without clustering. Low-energy adaptive clustering hierarchy (LEACH) is a cluster-based routing protocol with a high transmission efficiency to the base station. In this paper, we propose an energy consumption model for LEACH and compare it with the existing LEACH, advanced LEACH (ALEACH), and power-efficient gathering in sensor information systems (PEGASIS) algorithms in terms of network lifetime. The energy consumption model comprises energy-sensitive cluster formation and a cluster head selection technique. The setup and steady-state phases of the proposed model are discussed based on the cluster head selection. The simulation results demonstrated that a low-energy-consumption network was introduced, modeled, and validated for LEACH.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.7
• /
• pp.2488-2511
• /
• 2015

Data redundancy has high impact on Wireless Sensor Network's (WSN) performance and reliability. Spatial and temporal similarity is an inherent property of sensory data. By reducing this spatio-temporal data redundancy, substantial amount of nodal energy and bandwidth can be conserved. Most of the data gathering approaches use either temporal correlation or spatial correlation to minimize data redundancy. In Collective Prediction exploiting Spatio Temporal correlation (CoPeST), we exploit both the spatial and temporal correlation between sensory data. In the proposed work, the spatial redundancy of sensor data is reduced by similarity based sub clustering, where closely correlated sensor nodes are represented by a single representative node. The temporal redundancy is reduced by model based prediction approach, where only a subset of sensor data is transmitted and the rest is predicted. The proposed work reduces substantial amount of energy expensive communication, while maintaining the data within user define error threshold. Being a distributed approach, the proposed work is highly scalable. The work achieves up to 65% data reduction in a periodical data gathering system with an error tolerance of 0.6℃ on collected data.