• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.219-227
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• 2008

As found in research on constraint satisfaction problems, the choice of variable ordering heuristics is crucial for effective solving of constraint optimization problems. For the special problems such as energy-efficient clustering in heterogeneous wireless sensor networks, in which cluster heads have an inclination to be near a base station, we propose a new approach based on the static preferences variable orderings and provide a pnode heuristic algorithm for a specific application. The pnode algorithm selects the next variable with the highest Preference. In our problem, the preference becomes higher when the cluster heads are closer to the optimal region, which can be obtained a Priori due to the characteristic of the problem. Since cluster heads are the most dominant sources of Power consumption in the cluster-based sensor networks, we seek to minimize energy consumption by minimizing the maximum energy dissipation at each cluster heads as well as sensor nodes. Simulation results indicate that the proposed approach is more efficient than other methods for solving constraint optimization problems with static preferences.

• The KIPS Transactions:PartC
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• v.11C no.7 s.96
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• pp.923-930
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• 2004

Wireless sensor networks is a core technology of ubiquitous computing which enables the network to aware the different kind of context by integrating exiting wired/wireless infranet with various sensor devices and connecting collected environmental data with applications. However it needs an energy-efficient approach in network layer to maintain the dynamic ad hoc network and to maximize the network lifetime by using energy constrained node. Cluster-based data aggregation and routing are energy-efficient solution judging from architecture of sensor networks and characteristics of data. In this paper. we propose a new distributed clustering algorithm in using distance from the sink. This algorithm shows that it can balance energy dissipation among nodes while minimizing the overhead. We verify that our clustering is more en-ergy-efficient and thus prolongs the network lifetime in comparing our proposed clustering to existing probabilistic clustering for sensor network via simulation.

• The Magazine for Energy Service Companies
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• s.79
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• pp.12-19
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• 2012

본고에서는 ESCO 시장이 성장하기 위하여 건물부문 대상을 1만$m^2$이상 대형건물, 에너지다소비건물, 소규모 건물로 설정하여 정책 및 제도 개선방안을 모색한다. 이를 위해 각각의 개별적인 건물에너지 효율개선사업이 아닌, 유형별, 공간별로 집단화하여 ESCO사업으로 추진하고, ESCO에 대한 홍보와 관심을 유도하기 위한 시범사례를 구축 및 확산하기 위하여 해외사례와 시사점을 제시한다.