• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.406-409
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• 2008

Clustering data streams has an importance over many applications like sensor networks. Existing hierarchical methods follow a semi fuzzy clustering that yields duplicate clusters. In order to solve the problems, we propose an extended online divisive agglomerative clustering on data streams. It builds a tree-like top-down hierarchy of clusters that evolves with data streams using geometric time frame for snapshots. It is an enhancement of the Online Divisive Agglomerative Clustering (ODAC) with a pruning strategy to avoid duplicate clusters. Our main features are providing update time and memory space which is independent of the number of examples on data streams. It can be utilized for clustering sensor data and network monitoring as well as web click streams.

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.75-84
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• 2014

In this paper, we constructed a sensor network environment where various sensors are used. Then, we evaluated the performance when this environment adopted existing clustering algorithms that are designed for only single type sensors network. In our experiments, we considered two different types of the networks. In the first, all nodes are equipped with identical sensors. In the second, all nodes are equipped with three different types of sensors. We measured performance variations of several clustering schemes in accordance with sensor data accuracy, sensor node resource depletion timing, amount of available energy, node isolation ratio, and network lifetime. According to our performance analysis, we proved that existing clustering algorithms are partially inefficient to maintain the various-sensor network. Consequently we suggest that a new algorithm is required to take aim at the various sensor network.

• Journal of Applied Reliability
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• v.5 no.4
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• pp.465-486
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• 2005

A unreliable network system results in unsatisfied performance. A performance criterion of a network is throughput and availability. One of the most compelling technological advances of this decade has been the advent of deploying wireless networks of heterogeneous smart sensor nodes for complex information gathering tasks, The advancement and popularization of wireless communication technologies make more efficiency to network devices with wireless technology than with wired technology. Recently, the research of wireless sensor network has been drawing much attentions. In this paper, We evaluate throughput and availability of wireless sensor network, which have hierarchical structure based on clustering and estimate the maximum hroughput, average throughput and availability of the network considering several link failure patterns likely to happen at a cluster consisted of sensor nodes. Also increasing a number of sensor nodes in a cluster, We analysis the average throughput and availability of the network.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.926-940
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• 2018

In clustering-based approaches, cluster heads closer to the sink are usually burdened with much more relay traffic and thus, tend to die early. To address this problem, distance-aware clustering approaches, such as energy-efficient unequal clustering (EEUC), that adjust the cluster size according to the distance between the sink and each cluster head have been proposed. However, the network lifetime of such approaches is highly dependent on the distribution of the sensor nodes, because, in randomly distributed sensor networks, the approaches do not guarantee that the cluster energy consumption will be proportional to the cluster size. To address this problem, we propose a novel approach called CACD (Clustering Algorithm Considering node Distribution), which is not only distance-aware but also node density-aware approach. In CACD, clusters are allowed to have limited member nodes, which are determined by the distance between the sink and the cluster head. Simulation results show that CACD is 20%-50% more energy-efficient than previous work under various operational conditions considering the network lifetime.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.27-30
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• 2005

Because of unreplenishable power resources, reducing node energy consumption to extend network lifetime is an important requirement in wireless sensor networks. In addition both path length and path cost are important metrics affecting sensor lifetime. We propose a dynamic clustering scheme based on location in wireless sensor networks. Our scheme can localize the effects of route failures, reduce control traffic overhead, and thus enhance the reachability to the destination. We have evaluated the performance of our clustering scheme through a simulation and analysis. We provide simulation results showing a good performance in terms of approximation ratios.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.4991-4996
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• 2010

Clustering method in wireless sensor network is the technique that forms the cluster to aggregate the data and transmit them at the same time that they can use the energy efficiently. Even though cluster group model is based on clustering, it differs from previous method that reducing the total energy consumption by separating energy overload to cluster group head and cluster head. In this thesis, I calculate the optimal cluster group number and cluster number in this kind of cluster group model according to threshold of energy consumption model. By using that I can minimize the total energy consumption in sensor network and maximize the network lifetime. I also show that proposed cluster group model is better than previous clustering method at the point of network energy efficiency.

• Journal of Korea Multimedia Society
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• v.19 no.3
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• pp.573-584
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• 2016

Recent application range of sensor networks is becoming diverse. It means collected sensor data types are becoming diverse too. These sensor data have their own characteristics. Thus achieving energy efficiency, existing sensor network management policy consider their own characteristics. However, it is inefficient to apply the existing network management schemes for controlling such kind of data at the same time. Because, existing network management schemes considered one type of data only. Therefore, we propose a novel routing scheme that is able to efficient energy conservation through effective data controlling on multi-sensor application environment.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.5
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• pp.199-202
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• 2013

In the cluster mechanism of the wireless sensor network, the network lifetime is affected by how cluster heads are selected. One of the representative clustering mechanisms, the low-energy adaptive clustering hierarchy (LEACH), selects cluster heads periodically, resulting in high energy consumption in cluster reconstruction. On the other hand, the adaptive clustering algorithm via waiting timer (ACAWT) proposes a non-periodic re-clustering mechanism that reconstructs clusters if the remaining energy level of a cluster head reaches a given threshold. In this paper, we propose a re-clustering mechanism that uses multiple remaining node energy levels and does re-clustering when the remaining energy level of a cluster head reaches one level lower. Also, in determining cluster heads, both of the number of neighbor nodes and the remaining energy level are considered so that cluster heads can be more evenly placed. From the simulations based on the Qualnet simulator, we validate that our proposed mechanism outperforms ACAWT in terms of the network lifetime.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.1
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• pp.341-360
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• 2012

The network topology for a wide area sensor network has to support connectivity and a prolonged lifetime for the many applications used within it. The concepts of structure and group in sociology are similar to the concept of cluster in wireless sensor networks. The clustering method is one of the preferred ways to produce a topology for reduced electrical energy consumption. We herein propose a cluster topology method based on sociological structures and concepts. The proposed sociological clustering topology (SOCT) is a method that forms a network in two phases. The first phase, which from a sociological perspective is similar to forming a state within a nation, involves using nodes with large transmission capacity to set up the global area for the cluster. The second phase, which is similar to forming a city inside the state, involves using nodes with small transmission capacity to create regional clusters inside the global cluster to provide connectivity within the network. The experimental results show that the proposed method outperforms other methods in terms of energy efficiency and network lifetime.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.415-417
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• 2005

Core operations (e.9. TDMA scheduler, synchronized sleep period, data aggregation) of many proposed protocols for different layer of sensor network necessitate clock synchronization. Our Paper mingles the scheme of dynamic clustering and diffusion based asynchronous averaging algorithm for clock synchronization in sensor network. Our proposed algorithm takes the advantage of dynamic clustering and then applies asynchronous averaging algorithm for synchronization to reduce number of rounds and operations required for converging time which in turn save energy significantly than energy required in diffusion based asynchronous averaging algorithm.