• KIPS Transactions on Software and Data Engineering
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• v.2 no.6
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• pp.383-394
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• 2013

As a way of augmenting constrained resources of mobile devices such as CPU and memory, many works on mobile cloud computing (MCC), where mobile devices utilize remote resources of cloud services or PCs, have been proposed. Typically, in MCC, many nodes with different operating systems and platform and diverse mobile applications or services are located, and a central manager autonomously performs several management tasks to maintain a consistent level of MCC overall quality. However, as there are a larger number of nodes, mobile applications, and services subscribed by the mobile applications and their interactions are extremely increased, a traditional management method of MCC reveals a fundamental problem of degrading its overall performance due to overloaded management tasks to the central manager, i.e. a bottle neck phenomenon. Therefore, in this paper, we propose a clustering-based optimization method to solve performance-related problems on large-scaled MCC and to stabilize its overall quality. With our proposed method, we can ensure to minimize the management overloads and stabilize the quality of MCC in an active and autonomous way.

• 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 the Korea Academia-Industrial cooperation Society
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• v.11 no.1
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• pp.166-174
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• 2010

SSDs are one of the best media to support portable and desktop computers' storage devices. Their features include non-volatility, low power consumption, and fast access time for read operations, which are sufficient to present flash memories as major database storage components for desktop and server computers. However, we need to improve traditional index management schemes based on B-Tree due to the relatively slow characteristics of flash memory operations, as compared to RAM memory. In order to achieve this goal, we propose a new index management scheme based on a compressed hot-cold clustering called CHC-Tree. CHC-Tree-based index management improves index operation performance by dividing index nodes into hot or cold segments and compressing pointers and keys in the index nodes and clustering the hot or cold segments. The offset compression techniques using unused free area in cold index node lead to reduce the number of slow erase operations in index node insert/delete processes. Simulation results show that our scheme significantly reduces the write and erase operation overheads, improving the index search performance of B-Tree by up to 26 percent, and the index update performance by up to 23 percent.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.6
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• pp.446-453
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• 2013

Clustering schemes have been adopted as an efficient solution to prolong network lifetime and improve network scalability. In such clustering schemes cluster ratio is represented by the rate of the number of cluster heads and the number of total nodes, and affects the performance of clustering schemes. In this paper, we mathematically analyze an optimal clustering ratio in wireless sensor networks. We consider a multi-hop to one-hop transmission case and aim to provide the optimal cluster ratio to minimize the system hop-count and maximize packet reception ratio between nodes. We examine its performance through a set of simulations. The simulation results show that the proposed optimal cluster ratio effectively reduce transmission count and enhance energy efficiency in wireless sensor networks.

• Journal of the Korea Society of Computer and Information
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• v.19 no.6
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• pp.49-59
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• 2014

Recently, wireless sensor networks(WSNs) are widely used for intrusion detection and ecology, environment, atmosphere, industry, traffic, fire monitoring. In this paper, an energy efficient clustering algorithm is proposed. The proposed algorithm forms clusters uniformly by selecting cluster head that optimally located based on receiving power. Besides, proposed algorithm can induce uniform energy consumption regardless of location of nodes by multi-hop transmission and MST formation with limited maximum depth. Through the above, proposed algorithm elongates network life time, reduces energy consumption of nodes and induces fair energy consumption compared to conventional LEACH and HEED. The results of simulation show that the proposed clustering algorithm elongates network life time through fair energy consumption.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.845-858
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• 2020

This paper proposes a modified end-to-end secure low energy adaptive clustering hierarchy (ME-LEACH) algorithm for enhancing the lifetime of a wireless sensor network (WSN). Energy limitations are a major constraint in WSNs, hence every activity in a WSN must efficiently utilize energy. Several protocols have been introduced to modulate the way a WSN sends and receives information. The end-to-end secure low energy adaptive clustering hierarchy (E-LEACH) protocol is a hierarchical routing protocol algorithm proposed to solve high-energy dissipation problems. Other methods that explore the presence of the most powerful nodes on each cluster as cluster heads (CHs) are the sparsity-aware energy efficient clustering (SEEC) protocol and an energy efficient clustering-based routing protocol that uses an enhanced cluster formation technique accompanied by the fuzzy logic (EERRCUF) method. However, each CH in the E-LEACH method sends data directly to the base station causing high energy consumption. SEEC uses a lot of energy to identify the most powerful sensor nodes, while EERRCUF spends high amounts of energy to determine the super cluster head (SCH). In the proposed method, a CH will search for the nearest CH and use it as the next hop. The formation of CH chains serves as a path to the base station. Experiments were conducted to determine the performance of the ME-LEACH algorithm. The results show that ME-LEACH has a more stable and higher throughput than SEEC and EERRCUF and has a 35.2% better network lifetime than the E-LEACH algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.1-9
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• 2017

Recently, the active research into wireless sensor networks has led to the development of sensor nodes with improved performance, including their mobility and location awareness. One of the most important goals of such sensor networks is to transmit the data generated by mobile sensors nodes. Since these sensor nodes move in the mobile wireless sensor networks (MWSNs), the energy consumption required for them to transmit the sensed data to the fixed sink is increased. In order to solve this problem, the use of mobile sinks to collect the data while moving inside the network is studied herein. The important issues are the mobility and energy consumption in MWSNs. Because of the sensor nodes' limited energy, their energy consumption for data transmission affects the lifetime of the network. In this paper, a mobile-sink based energy-efficient clustering scheme is proposed for use in mobile wireless sensor networks (MECMs). The proposed scheme improves the energy efficiency when selecting a new cluster head according to the mobility of the mobile sensor nodes. In order to take into consideration the mobility problem, this method divides the entire network into several cluster groups based on mobile sinks, thereby decreasing the overall energy consumption. Through both analysis and simulation, it was shown that the proposed MECM is better than previous clustering methods in mobile sensor networks from the viewpoint of the network energy efficiency.

• 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.

• ETRI Journal
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• v.39 no.2
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• pp.275-283
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• 2017

A green technology for reducing energy consumption has become a critical factor in ICT industries. However, for the telecommunications sector in particular, most network elements are not usually optimized for power efficiency. Here, we propose a novel energy-efficient packet switching method for use in an IP network for reducing unnecessary energy consumption. As a green networking approach, we first classify the network nodes into either header or member nodes. The member nodes then put the routing-related module at layer 3 to sleep under the assumption that the layer in the OSI model can operate independently. The entire set of network nodes is then partitioned into clusters consisting of one header node and multiple member nodes. Then, only the header node in a cluster conducts IP routing and its member nodes conduct packet switching using a specially designed identifier, a tag. To investigate the impact of the proposed scheme, we conducted a number of simulations using well-known real network topologies and achieved a more energy- efficient performance than that achieved in previous studies.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.7
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• pp.62-70
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• 2015

The energy of a sensor in a Wireless Sensor Network (WSN) puts a limit on the lifetime of the network. To prolong the lifetime, a clustering plan is used. Clustering technology gets its energy efficiency through reducing the number of communication occurrences between the sensors and the base station (BS). In the distributed clustering protocol, LEACH-like (Low Energy Adaptive Clustering Hierarchy - like), the number of sensor's cluster head (CH) roles is different depending on the sensor's residual energy, which prolongs the time at which half of nodes die (HNA) and network lifetime. The position of the CH in each cluster tends to be at the center of the side close to BS, which forces cluster members to consume more energy to send data to the CH. In this paper, a protocol, pseudo-LEACH, is proposed, in which a cluster with a CH placed at the center of the cluster is formed. The scheme used allows the network to consume less energy. As a result, the timing of the HNA is extended and the stable network period increases at about 10% as shown by the simulation using MATLAB.