• Journal of KIISE:Information Networking
• /
• v.37 no.1
• /
• pp.50-56
• /
• 2010

This paper proposes a data gathering method by adapting the mobile sink to prolong the whole operation time of large WSNs. After partitioning a network into several clusters, a mobile sink visits each cluster and collects data from it. An efficient protocol improves the energy efficiency by delivering messages from the mobile sink to the cluster head as well as reduces the data gathering delay, which is the disadvantage of the mobile sink. For the scalability of sensor network, the network architecture should support the multihop transmission in the duster rather than the single hop transmission. The process for the data aggregation linked to the travelling path is proposed to improve the energy consumption of intermediate nodes. The experiment results show that the proposed model is more efficient than legacy methods in the energy consumption and the data gathering time.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.46 no.5
• /
• pp.79-85
• /
• 2009

A sink node and its neighbor nodes spend more energy than other nodes since a stationary sink node collects data from wireless sensor networks(WSNs). For larger WSNs, the unbalanced energy of nodes causes the operation of WSNs to stop rapidly. This paper proposes a data gathering method by adapting the mobile sink to prolong the life time of large WSNs. After partitioning a network into several clusters, a mobile sink visits each cluster and collects data from it. An efficient algorithm is proposed to improve the energy efficiency by delivering the message from the mobile sink to the cluster head as well as to reduce the data gathering delay, which is the disadvantage of the mobile sink. Also, The algorithm is analyzed for the energy consumption and the data gathering delay. The validity of the ananlysis result is confirmed by the simulation.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.30 no.7 s.155
• /
• pp.1034-1043
• /
• 2006

The purpose of this study was to investigate the difference of the visual evaluation about gathered skirts according to different gathering conditions and objects. The experiment is made of factorial design for three variables-fabric(cotton, wool, polyester), ratio of gathers(1.5T, 2.0T, 2.5T), objects(real thing, 2D digital picture, 3D shape). Questionnaire consists of 33 sematic differential scale expressing gathered skirts' image. The subjects were 50 male and female students majoring in clothing and textile. The data were analyzed by Frequency, Factor analysis, Anova, scheffe's test. The results obtained were summarized as follows; 1. As the open-ended response there were difference among the image according to different gathering conditions and obects. 2. The image of gathered skirts was composed of 6 factors; activities, attraction, attention, softness, moderateness, function. 3. For visual evaluation of gathering conditions as different objects, there were similar as softly in fabrics and lager in ratio of gathers. 4. For visual evaluation of different objects as gathering conditions, there was more difference effect of ratio of gathers than fabrics.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.14 no.2
• /
• pp.122-129
• /
• 2014

Effective information gathering and retrieval of the most relevant web documents on the topic of interest is difficult due to the large amount of information that exists in various formats. Current information gathering and retrieval techniques are unable to exploit semantic knowledge within documents in the "big data" environment; therefore, they cannot provide precise answers to specific questions. Existing commercial big data analytic platforms are restricted to a single data type; moreover, different big data analytic platforms are effective at processing different data types. Therefore, the development of a common big data platform that is suitable for efficiently processing various data types is needed. Furthermore, users often possess more than one intelligent device. It is therefore important to find an efficient preference profile construction approach to record the user context and personalized applications. In this way, user needs can be tailored according to the user's dynamic interests by tracking all devices owned by the user.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.3 no.6
• /
• pp.612-627
• /
• 2009

The high-level contribution of this paper is to illustrate the effectiveness of using graph theory tree traversal algorithms (pre-order, in-order and post-order traversals) to generate the chain of sensor nodes in the classical Power Efficient-Gathering in Sensor Information Systems (PEGASIS) data aggregation protocol for wireless sensor networks. We first construct an undirected minimum-weight spanning tree (ud-MST) on a complete sensor network graph, wherein the weight of each edge is the Euclidean distance between the constituent nodes of the edge. A Breadth-First-Search of the ud-MST, starting with the node located closest to the center of the network, is now conducted to iteratively construct a rooted directed minimum-weight spanning tree (rd-MST). The three tree traversal algorithms are then executed on the rd-MST and the node sequence resulting from each of the traversals is used as the chain of nodes for the PEGASIS protocol. Simulation studies on PEGASIS conducted for both TDMA and CDMA systems illustrate that using the chain of nodes generated from the tree traversal algorithms, the node lifetime can improve as large as by 19%-30% and at the same time, the energy loss per node can be 19%-35% lower than that obtained with the currently used distance-based greedy heuristic.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.16 no.3
• /
• pp.304-313
• /
• 2013

Wireless Sensor Networks, especially supporting for surveillance service, are one of the core properties of network-centric warfare(NCW) that is a key factor of victory in future battlefields. Such a tactical surveillance sensor network must be designed not just for energy efficiency but for real-time requirements of emergency data transmission towards a control center. This paper proposes efficient clustering-based methods for supporting mobile sinks so that the network lifetime can be extended while emergency data can be served as well. We analyze the performance of the proposed scheme and compare it with other existing schemes through simulation via Qualnet 5.0.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.2
• /
• pp.247-268
• /
• 2011

Due to the application-specific nature of wireless sensor networks, the sensitivity to such a requirement as data reporting interval varies according to the type of application. Such considerations require an application-specific, parameter tuning paradigm allowing us to maximize energy conservation prolonging the operational network lifetime. In this paper, we propose a reporting interval adaptive, sensor control platform for energy-saving data gathering in wireless sensor networks. The ultimate goal is to extend the network lifetime by providing sensors with high adaptability to application-dependent or time-varying, reporting interval requirements. The proposed sensor control platform is based upon a two phase clustering (TPC) scheme which constructs two types of links within each cluster - namely, direct link and relay link. The direct links are used for control and time-critical, sensed data forwarding while the relay links are used only for multi-hop data reporting. Sensors opportunistically use the energy-saving relay link depending on the user reporting, interval constraint. We present factors that should be considered in deciding the total number of relay links and how sensors are scheduled for sensed data forwarding within a cluster for a given reporting interval and link quality. Simulation and implementation studies demonstrate that the proposed sensor control platform can help individual sensors save a significant amount of energy in reporting data, particularly in dense sensor networks. Such saving can be realized by the adaptability of the sensor to the reporting interval requirements.

• Proceedings of the Korean Geotechical Society Conference
• /
• 2007.09a
• /
• pp.431-439
• /
• 2007

Data logger is generally needed for gathering field information automatically(or manually), using various sensors. However it, currently used in the county, is produced and developed by overseas. It is difficult to upgrade related program due to developed system and limited user in terms of environment it is used. On the other hand, several companies developed and sold unique data logger based their technique expertise in the country. But enhancement and practical use of related technology has much difficulties because feasibility, marketability and demand for technique are uncertain. In this study, it is the main purpose to offer basic information to select equipment suitable for field characteristic through analysis and comparison with features about method of information collection, operating program and process technique data logger which is used primarily in geotechnical engineering in both domestic and international.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.1
• /
• pp.27-35
• /
• 2008

A navigation system is one of the important components of an unmanned ground vehicle (UGV). A GPS receiver collects data signals transmitted by (Earth orbiting) satellites. However, these data signals may contain many errors resulting misinformation and depending on one's position (environment), reception may be impossible. The proposed self-driven algorithm uses three low-cost GPS in order to minimize errors of existing inexpensive single GPS's driving algorithm. By using reliable final data, which is analyzed and combined from each of three GPS's received data signals, gathering a vehicle's steering performance information and its current pin-point position is improved even with error containing signals or from a place where signal gathering is impossible. The purpose of this thesis is to explain navigation system algorithm using multiple GPS and compass sensor and prove the algorithm through experiments.

• The KIPS Transactions:PartC
• /
• v.17C no.6
• /
• pp.459-464
• /
• 2010

Due to the application-specific nature of wireless sensor networks, the sensitivity to such a requirement as data reporting latency may vary depending on the type of applications, thus requiring application-specific algorithm and protocol design paradigms which help us to maximize energy conservation and thus the network lifetime. In this paper, we implement and evaluate a novel delay-adaptive sensor scheduling scheme for energy-saving data gathering which is based on a two phase clustering (TPC), in wireless sensor networks. The TPC is implemented on sensor Mote hardwares. With the help of TPC implemented, sensors selectively use direct links for control and forwarding time critical sensed data and relay links for data forwarding based on the user delay constraints given. Implementation study shows that TPC helps the sensors to increase a significant amount of energy while collecting sensed data from sensors in a real environment.