• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11B
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• pp.685-692
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• 2007

Recent advances in wireless communications and electronics have enabled the development of low-cost, low-power, multi-functional sensors. A typical wireless sensor network (WSN) consists of a large number of sensor nodes that can measure and process data while communicating through wireless channels. In this paper, we propose a hybrid query processing (HQP) algorithm for user queries submitted to the WSN. Unlike previous algorithms that consider continuous queries only, HQP supports both continuous queries and ad-hoc queries. Specially. HQP tries to reduce energy consumption of ad-hoc queries by using query results cached at each sensor node which are created during the execution of the previous continuous query. HQP can also exploit a trade-off between energy consumption and data accuracy. We evaluate the performance of HQP under a variety of WSN configurations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2140-2156
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• 2023

The Wireless Sensor Network (WSN), is constructed out of teeny-tiny sensor nodes that are very low-cost, have a low impact on the environment in terms of the amount of power they consume, and are able to successfully transmit data to the base station. The primary challenges that are presented by WSN are those that are posed by the distance between nodes, the amount of energy that is consumed, and the delay in time. The sensor node's source of power supply is a battery, and this particular battery is not capable of being recharged. In this scenario, the amount of energy that is consumed rises in direct proportion to the distance that separates the nodes. Here, we present a Hybrid Firefly Glow-Worm Swarm Optimization (HF-GSO) guided routing strategy for preserving WSNs' low power footprint. An efficient fitness function based on firefly optimization is used to select the Cluster Head (CH) in this procedure. It aids in minimising power consumption and the occurrence of dead sensor nodes. After a cluster head (CH) has been chosen, the Glow-Worm Swarm Optimization (GSO) algorithm is used to figure out the best path for sending data to the sink node. Power consumption, throughput, packet delivery ratio, and network lifetime are just some of the metrics measured and compared between the proposed method and methods that are conceptually similar to those already in use. Simulation results showed that the proposed method significantly reduced energy consumption compared to the state-of-the-art methods, while simultaneously increasing the number of functioning sensor nodes by 2.4%. Proposed method produces superior outcomes compared to alternative optimization-based methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7A
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• pp.697-705
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• 2010

In Wireless Sensor Networks (WSNs), blanket (area) coverage analysis is generally carried to find the minimum number of active sensor nodes required to cover a monitoring interest area with the desired fractional coverage-threshold. Normally, the coverage analysis is performed using the stochastic geometry as a tool. The major component of such coverage analysis is the assumed sensing model. Hence, the accuracy of such analysis depends on the underlying assumption of the sensing model: how well the assumed sensing model characterizes the real sensing phenomenon. In this paper, we review the coverage analysis for different deterministic and probabilistic sensing models like Boolean and Shadow-fading model; and extend the analysis for Exponential and hybrid Boolean-Exponential model. From the analytical performance comparison, we demonstrate the redundancy (in terms of number of sensors) that could be resulted due to the coverage analysis based on the detection capability mal-characterizing sensing models.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.96-98
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• 2014

Wireless Sensor Network(WSN) is a wireless real-time information(Acquired from the sensor nodes that have the computing power and wireless communication capabilities.) collected, and to take advantage of processing techniques. Currently it is very diverse, such as environmental monitoring, health care, security, smart home, smart grid applications is that. Thus it is required in the wireless sensor network, the algorithm for the efficient use of the limited energy capacity. Suggested by the algorithm for selecting a cluster head node for a hybrid type and clustered, by comparing the amount of energy remaining and a connection between the nodes In this paper, we aim to increase efficiency and accuracy of the wireless sensor network.

• Journal of Information Processing Systems
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• v.6 no.1
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• pp.53-66
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• 2010

The energy efficiency is a key design issue to improve the lifetime of the underwater sensor networks (UWSN) consisting of sensor nodes equipped with a small battery of limited energy resource. In this paper, we apply a hexagon tessellation with an ideal cell size to deploy the underwater sensor nodes for two-dimensional UWSN. Upon this setting, we propose an enhanced hybrid transmission method that forwards data packets in a mixed transmission way based on location dependent direct transmitting or uniform multi-hop forwarding. In order to select direct transmitting or uniform multi-hop forwarding, the proposed method applies the threshold annulus that is defined as the distance between the cluster head node and the base station (BS). Our simulation results show that the proposed method enhances the energy efficiency compared with the existing multi-hop forwarding methods and hybrid transmission methods

• Journal of Internet Computing and Services
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• v.9 no.5
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• pp.165-173
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• 2008

Hybrid ad hoc networks are integrated networks referred to Home Networks, Telematics and Sensor networks can offer various services. Specially, in ad hoc network where each node is responsible for forwarding neighbor nodes' data packets, it should net only reduce the overall energy consumption but also balance individual battery power. Unbalanced energy usage will result in earlier node failure in overloaded nodes. it leads to network partitioning and reduces network lifetime. Therefore, this paper studied the routing protocol considering efficiency of energy. The suggested algorithm can predict the status of energy in each node using the energy prediction model. This can reduce the overload of establishing route path and balance individual battery power. The suggested algorithm can reduce power consumption as well as increase network lifetime.

• ETRI Journal
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• v.34 no.6
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• pp.922-931
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• 2012

With the increasing demands for mobile wireless sensor networks in recent years, designing an energy-efficient clustering and routing protocol has become very important. This paper provides an analytical model to evaluate the power consumption of a mobile sensor node. Based on this, a clustering algorithm is designed to optimize the energy efficiency during cluster head formation. A genetic algorithm technique is employed to find the near-optimal threshold for residual energy below which a node has to give up its role of being the cluster head. This clustering algorithm along with a hybrid routing concept is applied as the near-optimal energy-efficient routing technique to increase the overall efficiency of the network. Compared to the mobile low energy adaptive clustering hierarchy protocol, the simulation studies reveal that the energy-efficient routing technique produces a longer network lifetime and achieves better energy efficiency.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4B
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• pp.258-268
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• 2012

Wireless Sensor Network(WSN) is constituted by low-cost and low-energy, So the most important issue is that the task of the sensor performs successfully by using less energy. In previous WSN, determination of the header and gathering sensor data solution by header give great affection to the performance of network. In this paper, we propose a Hybrid transmission method which considers the direction of data collections. In the proposed hybrid routing method, all of the sensors determine that transmission the data to the sink node directly or indirectly using the head node depend on the location of the head node in the cluster. The performance is compared with the LEACH(Low Energy Adaptive Clustering Hierarchy) by experimental analysis. The results show that the preposed method can reduce the communication distance and energy consumption by avoiding the detour direction of transmission of the data.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.2
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• pp.54-64
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• 2010

Localization is the most important feature in the sensor network environment because it is a basic element enabling people and things to aware the circumference environment. Existing localization methods can be categorized as either range-based or range-free. While range-based is known to be not suitable because of the irregularity of radio propagation and the additional device requirement. range-free is much appropriated for the resource constrained sensor network because it can actively locate by means of the communication radio. But its location accuracy is just depended on the density of circumference nodes; it is very low in low-density sensor network environment. This paper proposes a mobile object tracking method, named DRTS(Distributed Range-hybrid Tracking Scheme), with combining range-based and range-free. It is optimally making use of the location, communication range, and received signal strength from circumference nodes. Especially, it can greatly improve the mobile tracking accuracy by adapting a new prediction method, named EGP(Estimative Gird Points) into the proposed location estimation method. The simulation results show that our method outperforms the other localization and tracking methods in the tracking accuracy point of view.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.43-44
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• 2007

The Underwater Wireless Sensor Network (UWSN) consists of sensor nodes equipped with a small battery of limited energy resource. Hence, the energy efficiency is a key design issue that needs to be addressed in order to improve the lifetime of the network. In this paper, we use a hexagon tessellation with and ideal cell size to deploy the underwater sensor nodes for the UWSN and propose an enhanced hybrid transmission method that considers the load balancing once the data transmission occurs.