• Proceedings of the Korean Information Science Society Conference
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• 2007.10d
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• pp.240-243
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• 2007

Geographic routing has been considered as an efficient simple, and scalable routing protocol for wireless sensor networks since it exploits pure location information instead of global topology information to route data packets. Geographic routing requires the sources nodes to be aware of the location of the sinks. In this paper, we propose a scheme named Sink Location Service for geographic routing in wireless Sensor Networks, in which the source nodes can get and update the location of sinks with low overhead. In this scheme, a source and a sink send data announcement and query messages along two paths respectively by geographic routing. The node located on the crossing point of the two paths informs the source about the location of the sink. Then the source can send data packet to the sink by geographic routing. How to guarantee that these two paths have at least one crossing point in any irregular profile of sensor network is the challenge of this paper.

• 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.

• The Transactions of the Korea Information Processing Society
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• v.3 no.7
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• pp.1707-1718
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• 1996

Given a signal net N=s, 1,...,n to be the set of nodes, with s the source and the remaining nodes sinks, an MRDPT (minimum-cost rectilinear Steiner distance -preserving tree) has the property that the length of every source to sink path is equal to the rectilinear distance between the source and sink. The minimum- cost rectilinear Steiner distance-preserving tree minimizes the total wore length while maintaining minimal source to sink length. Recently, some heuristic algorithms have been proposed for the problem offending the MRDPT. In this paper, we investigate an optimal structure on the MRDPT and present a theoretical breakthrough which shows that the min-cost flow formulation leads to an efficient O(n2logm)2) time algorithm. A more practical extension is also in vestigated along with interesting open problems.

• Journal of the Korea Computer Industry Society
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• v.8 no.4
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• pp.237-244
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• 2007

In this paper we investigate the benefits of a data aggregation to prolong the lifetime of wireless sensor networks. To reduce the overload of messages from source node to sink node, data aggregation technique is generally used at intermediate node in path. The DD-G(Directed Diffusion-Greedy) can diminish the consumption of node energy by establishing energy effective single path from source to destination. In this case, the nodes near sink node have some problems, i) overly concentration of energy consumption, ii) increase of message delay time. To solve these problems, we propose a new data aggregation method which consider distribution of network overload, especially at the nodes close to sink node. The result shows that it can save energy and network delay time.

• Convergence Security Journal
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• v.13 no.6
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• pp.69-76
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• 2013

A lot of researches have been done to improve the energy efficiency of Wireless Sensor Networks. But all the current researches are based on the idea of direct communication between cluster head and sink node. Previous results assume that node can intelligently regulate signal energy according to the distance between nodes. It is difficult to implement algorithms based on this assumption. We present a multi-level routing algorithm from the sink node to all other nodes which have fixed radio wave radius. We also show the energy saving efficiency and the implementation in real WSN using the simulation result.

• 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.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.5
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• pp.405-411
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• 2015

In this paper, we propose routing protocol for mobile wireless sensor networks with a mobile sink in cluster configuration. The proposed protocol extends LEACH-ME by introducing a mobile sink. The mobile sink moves to the cluster head with the highest number of member nodes to collect sensed data from cluster heads within its vicinity, which results in reducing energy consumption in forwarding packets to the sink. The simulation results show that the proposed protocol outperform LEACH-ME in terms of energy efficiency.

• Journal of Communications and Networks
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• v.18 no.2
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• pp.227-237
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• 2016

Data collection is a key function for wireless sensor networks. There has been numerous data collection scheduling algorithms, but they fail to consider the deep and complex relationship among network lifetime, sink aggregated information and sample cycle for wireless sensor networks. This paper gives the upper bound on the sample period under the given network topology. An optimal schedule algorithm focusing on aggregated information named OSFAI is proposed. In the schedule algorithm, the nodes in hotspots would hold on transmission and accumulate their data before sending them to sink at once. This could realize the dual goals of improving the network lifetime and increasing the amount of information aggregated to sink. We formulate the optimization problem as to achieve trade-off among sample cycle, sink aggregated information and network lifetime by controlling the sample cycle. The results of simulation on the random generated wireless sensor networks show that when choosing the optimized sample cycle, the sink aggregated information quantity can be increased by 30.5%, and the network lifetime can be increased by 27.78%.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.19-26
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• 2018

One of the distinct features of Wireless Sensor Networks (WSNs) is duty cycling mechanism, which is used to conserve energy and extend the network lifetime. Large duty cycle interval introduces lower energy consumption, meanwhile longer end-to-end (E2E) delay. In this paper, we introduce an energy consumption minimization problem for duty-cycled WSNs. We have applied Q-learning algorithm to obtain the maximum duty cycle interval which supports various delay requirements and given Delay Success ratio (DSR) i.e. the required probability of packets arriving at the sink before given delay bound. Our approach only requires sink to compute Q-leaning which makes it practical to implement. Nodes in the different group have the different duty cycle interval in our proposed method and nodes don't need to know the information of the neighboring node. Performance metrics show that our proposed scheme outperforms existing algorithms in terms of energy efficiency while assuring the required delay bound and DSR.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.252-262
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• 2024

The multi-hop wireless sensor network (WSN) suffers from energy limitation and eavesdropping attacks. We propose a simple and energy-efficient convergecast mechanism using inter-flow random linear network coding that can provide confidentiality to the multi-hop WSN. Our scheme consists of two steps, constructing a logical tree of sensor nodes rooted at the sink node, with using the Bloom filter, and transmitting sensory data encoded by sensor nodes along the logical tree upward to the sink where the encoded data are decoded according to our proposed multi-hop network coding (MHNC) mechanism. We conducted simulations using OMNET++ CASTALIA-3.3 framework and validated that MHNC outperforms the conventional mechanism in terms of packet delivery ratio, data delivery time and energy efficiency.