• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.289-293
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• 2009

In sensor networks, many methods have been proposed to process in-network aggregation effectively. Contrary to normal aggregation queries, skyline query processing that compare multi-dimension data for producing result is very hard. It is important to filter unnecessary data for energy-efficient skyline query processing. Existing approach like MFTAC restricts unnecessary data transitions by deploying filters to whole sensors. However, network lifetime is reduced by energy consumption for filters transmission. In this paper, we propose a lazy filtering-based skyline query processing algorithm of in-network for reducing energy consumption by filters transmission. The proposed algorithm creates the skyline filter table (SFT) in the data gathering process which sends from sensor nodes to the base station and filters out unnecessary transmissions using it. The experimental results show that the proposed algorithm reduces false positive by 53% and improves network lifetime by 44% on average over MFTAC.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2307-2314
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• 2008

The study that automates the variety of equipment using the USN(Ubiquitous Sensor Networks) has been executed, and the research field is ranged to almost all fields including a road, harbors. building, military affairs, agriculture and home. By deploying these sensors into the greenhouse environment, we can monitor the environmental change and the growth of plants 24 hours a day. However, the limited resources of a sensor node like limited energy, short transmission range etc, make it difficult to expand the size of the sensor networks. In this paper, we studied to expand the site of sensor networks by using WMN(Wireless Mesh Networks) with simulation. With this simulation, we could validate that using the Wireless Mesh Networks technology for expanding sensor networks is more efficient in the energy aspect than the normal sensor network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.12
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• pp.1135-1144
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• 2013

Deploying small cells is a reliable and influential solution to handle the skyrocketing traffic increase in the cellular network, and the small cell technology is evolving to ultra-dense network (UDN). In this paper we propose a small cell on/off algorithm with a simple but essential framework composed of access point (AP), user equipment (UE), and small cell controller (SCC). We propose Device-Assisted Networking for Cellular grEening (DANCE) algorithms that save the energy consumption by tying to minimize the number of turned-on APs while maintaining the network throughput. In doing so, SCC firstly gathers the feedback messages from UEs and then makes a decision including a set of turned-on APs and user association. DANCE algorithm has several variations depending on the number of bits of the UE's feedback message (1 bit vs. N bit), and is divided into AP-first, UE-first, or Proximity ON according to the criteria of selecting the turned-on APs. We perform extensive simulations under the realistic UDN environment, and the results confirm that the proposed algorithms, compared to the baseline, can significantly enhance the energy efficiency, e.g., more than a factor of 10.

• Journal of Energy Engineering
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• v.26 no.4
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• pp.107-117
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• 2017

Since South Korea started to apply Renewable Portfolio Standard (RPS) in 2012, there have been huge investment for deploying renewable technologies. Recently, the government determined to incentivize battery energy storage system(BESS) with renewable generations in order to induce the improvement of dispatching capability. In this paper, the annual pattern of PV generation based on actual generation data in South Korea is analyzed and the duration curve of capacity factor is proposed in order to provide the simplified analyzing methodology of present support policy for additional BESS installation for decision maker who is responsible for supply and demand planning. With suggested methodology, the range of appropriate BESS size with respect to the variation of system marginal price(SMP) and renewable energy certificate(REC) price can be derived briefly, and decision makers easily evaluate the effect of support scheme. Current policy for BESS installation support present additional BESS-related installation policy may give incentives to developers partially, however, the dependence between BESS size and benefit components (SMP and REC) can limit the deployment of the various portfolios of the BESS. Therefore, when improving the current policy in future, addressing the dependence between the technical aspects of battery size and the benefit components separately by the technical and economical parts is needed to set the suitable compensation rules for the renewable generation and BESS.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.989-1009
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• 2018

Rapid advances in science and technology with exponential development of smart mobile devices, workstations, supercomputers, smart gadgets and network servers has been witnessed over the past few years. The sudden increase in the Internet population and manifold growth in internet speeds has occasioned the generation of an enormous amount of data, now termed 'big data'. Given this scenario, storage of data on local servers or a personal computer is an issue, which can be resolved by utilizing cloud computing. At present, there are several cloud computing service providers available to resolve the big data issues. This paper establishes a framework that builds Hadoop clusters on the new single-board computer (SBC) Mobile Raspberry Pi. Moreover, these clusters offer facilities for storage as well as computing. Besides the fact that the regular data centers require large amounts of energy for operation, they also need cooling equipment and occupy prime real estate. However, this energy consumption scenario and the physical space constraints can be solved by employing a Mobile Raspberry Pi with Hadoop clusters that provides a cost-effective, low-power, high-speed solution along with micro-data center support for big data. Hadoop provides the required modules for the distributed processing of big data by deploying map-reduce programming approaches. In this work, the performance of SBC clusters and a single computer were compared. It can be observed from the experimental data that the SBC clusters exemplify superior performance to a single computer, by around 20%. Furthermore, the cluster processing speed for large volumes of data can be enhanced by escalating the number of SBC nodes. Data storage is accomplished by using a Hadoop Distributed File System (HDFS), which offers more flexibility and greater scalability than a single computer system.

• Journal of the Korea Society for Simulation
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• v.29 no.3
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• pp.73-82
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• 2020

In the fourth industrial revolution, wireless sensor networks (WSNs) are an important element of collecting and analyzing data in a variety of environments without human intervention. This sensor network is greatly affected by topology and routing protocols. Routing protocols, which affect energy consumption, are executed after deploying sensor nodes. Once built, they are difficult to change. Before the WSN is deployed, a routing protocol is carefully selected in view of various environments and the performance of the protocol is evaluated. In this paper, we propose a model to simulate multiple routing protocols using a discrete event system specification (DEVS). The DEVS-based proposed model simulates various situations without changes and structures of the its model as algorithms of the routing protocols are implemented in its coordinators model. To verify normal behaviors of the proposed model, the number of report delivery and the energy consumption of the sensor network were compared using representative protocols LEACH and Dijkstra. As a result, it was confirmed that the proposed model executes normally in both routing protocols.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.47-58
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• 2018

The heterogeneous cellular network (HCN) is most significant as a key technology for future fifth generation (5G) wireless networks. The heterogeneous network considered consists of randomly macrocell base stations (MBSs) overlaid with femtocell base stations (BSs). The stochastic geometry has been shown to be a very powerful tool to model, analyze, and design networks with random topologies such as wireless ad hoc, sensor networks, and multi- tier cellular networks. The HCNs can be energy-efficiently designed by deploying various BSs belonging to different networks, which has drawn significant attention to one of the technologies for future 5G wireless networks. In this paper, we propose switching off/on systems enabling the BSs in the cellular networks to efficiently consume the power by introducing active/sleep modes, which is able to reduce the interference and power consumption in the MBSs and FBSs on an individual basis as well as improve the energy efficiency of the cellular networks. We formulate the minimization of the power onsumption for the MBSs and FBSs as well as an optimization problem to maximize the energy efficiency subject to throughput outage constraints, which can be solved the Karush Kuhn Tucker (KKT) conditions according to the femto tier BS density. We also formulate and compare the coverage probability and the energy efficiency in HCNs scenarios with and without coordinated multi-point (CoMP) to avoid coverage holes.

• Journal of KIISE:Databases
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• v.36 no.6
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• pp.476-485
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• 2009

In sensor networks, many methods have been proposed to process in-network aggregation effectively. Unlike general aggregation queries, skyline query processing compares multi-dimensional data for the result. Therefore, it is very difficult to process the skyline queries in sensor networks. It is important to filter unnecessary data for energy-efficient skyline query processing. Existing approach like MFTAC restricts unnecessary data transitions by deploying filters to whole sensors. However, network lifetime is reduced by energy consumption for many false positive data and filters transmission. In this paper, we propose a bottom up filtering-based skyline query processing algorithm of in-network for reducing energy consumption by filters transmission and a PBFiltering technique for improving performance of filtering. The proposed algorithm creates the skyline filter table (SFT) in the data gathering process which sends from sensor nodes to the base station and filters out unnecessary transmissions using it. The experimental results show that our algorithm reduces false positives and improves the network lifetime over the existing method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3641-3655
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• 2016

Wireless sensor networks (WSNs) provide a promising approach to monitor the physical environments, to prolong the network lifetime by exploiting the mutual correlation among sensor readings has become a research focus. In this paper, we design a hierarchical network framework which guarantees layered-compression. Meanwhile, a data sorting-based adaptive spatial compression scheme (DS-ASCS) is proposed to explore the spatial correlation among signals. The proposed scheme reduces the amount of data transmissions and alleviates the network congestion. It also obtains high compression performance by sorting original sensor readings and selectively discarding the small coefficients in transformed matrix. Moreover, the compression ratio of this scheme varies according to the correlation among signals and the value of adaptive threshold, so the proposed scheme is adaptive to various deploying environments. Finally, the simulation results show that the energy of sorted data is more concentrated than the unsorted data, and the proposed scheme achieves higher reconstruction precision and compression ratio as compared with other spatial compression schemes.

• The KIPS Transactions:PartC
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• v.15C no.6
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• pp.513-522
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• 2008

Efficient data dissemination is one of the important subjects for sensor networks. High accessibility of the sensed data can be kept by deploying the data centric storage approach in which data is stored over the nodes in the sensor network itself rather than external storages or systems. The advantage of this approach is its direct accessibility in a real-time without the severe burden on delay and power dissipation on the data path to the external storages or systems. However, if the queries from many users are concentrated to the few nodes with data, then the response time could be increased and it could lead to the reduction of network life time by rapid energy dissipation caused by concentrated network load. In this paper, we propose a adaptive data centric storage scheme based on proxy trajectory (APT) mechanism. We highlight the data centric storage mechanism by taking account of supporting large number of users, and make it feasible to provide high-performance accessibility when a non-uniform traffic pattern is offered. Storing data around the localized users by considering spatial data-access locality, the proxy trajectory of APT provides fast response for the users. The trajectory, furthermore, may help the mobile users to roams freely within the area they dwell.