• The KIPS Transactions:PartC
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• v.17C no.1
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• pp.81-88
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• 2010

Sensors in sensor networks are operated by their embedded batteries and they can not work any more if the batteries run out. The data collected by sensors should be transferred to a sink node through the efficient routes. Many energy efficient routing algorithms were proposed. However, the previous algorithms consume more energy since they did not consider the transmission range and direction. In this paper we propose an algorithm TDRP(Transmission range and Direction Routing Protocol) that considers the transmission range and direction for the efficient data transmission. Since TDRP does not produce clusters or grids but four quadrants and send data to the nodes in one quadrant in the direction of the sink node, it has less network overhead. Furthermore since the proposed algorithm sends data to the smaller number of nodes compared to the previous algorithms, the energy efficiency is better than other algorithms in communication node fields that are located in packet transmit directions.

• Journal of Internet Computing and Services
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• v.15 no.4
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• pp.111-118
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• 2014

In mobile sensor networks, a large number of sensor nodes with battery powered are deployed randomly in a region. They monitor the environmental states and transmit data to its neighboring nodes. For mobile sensor networks, It is needed to maintain the connectivity autonomously among nodes as the sensor node moves. However, the existing works have focused on the energy savings in the fixed sensor networks. A specific algorithm considering node mobility is required in the mobile sensor networks. Along with energy efficiency, the transmission delay should be considered. In this paper, we propose an autonomous configuration scheme and a node scheduling algorithm when a moving node joins into the existing network. Through simulations, we show a superior performance of the proposed algorithm to the existing protocol.

• Journal of KIISE:Databases
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• v.36 no.3
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• pp.189-197
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• 2009

Top-k queries are important to many wireless sensor applications. Conventional Top-k query processing algorithms install a filter at each sensor node and suppress unnecessary sensor updates. However, they have some drawbacks that the sensor nodes consume energy extremely to probe sensor reading or update filters. Especially, it becomes worse, when the variation ratio of top-k result is higher. In this paper, we propose a novel Top-k query processing algorithm for energy-efficiency. First, each sensor determines its priority as the order of data gathering. Next, sensor nodes that have higher priority transmit their sensor readings to the base station until gathering k sensor readings. In order to show the superiority of our query processing algorithm, we simulate the performance with the existing query processing algorithms. As a result, our experimental results show that the network lifetime of our method is prolonged largely over the existing method.

• 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.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.4
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• pp.313-320
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• 2008

The dynamic clustering technique has some problems regarding energy consumption. In the cluster configuration aspect the cluster structure must be modified every time the head nodes are re-selected resulting in high energy consumption. Also, there is excessive energy consumption when a cluster head node receives identical data from adjacent cluster sources nodes. This paper proposes a solution to the problems described above from the energy efficiency perspective. The round-robin cluster header(RRCH) technique, which fixes the initially structured cluster and sequentially selects duster head nodes, is suggested for solving the energy consumption problem regarding repetitive cluster construction. Furthermore, the issue of redundant data occurring at the cluster head node is dealt with by broadcasting metadata of the initially received data to prevent reception by a sensor node with identical data. A simulation experiment was performed to verify the validity of the proposed approach. The results of the simulation experiments were compared with the performances of two of the must widely used conventional techniques, the LEACH(Low Energy Adaptive Clustering Hierarchy) and HEED(Hybrid, Energy Efficient Distributed Clustering) algorithms, based on energy consumption, remaining energy for each node and uniform distribution. The evaluation confirmed that in terms of energy consumption, the technique proposed in this paper was 29.3% and 21.2% more efficient than LEACH and HEED, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.12
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• pp.9-16
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• 2016

Wireless sensor networks (WSN) are composed of sensor nodes and a base station. The sensor nodes deploy a non-accessible area, receive critical information, and transmit it to the base station. The information received is applied to real-time monitoring, distribution, medical service, etc.. Recently, the WSN was extended to mobile wireless sensor networks (MWSN). The MWSN has been applied to wild animal tracking, marine ecology, etc.. The important issues are mobility and energy consumption in MWSN. Because of the limited energy of the sensor nodes, the energy consumption for data transmission affects the lifetime of the network. Therefore, efficient data transmission from the sensor nodes to the base station is necessary for sensing data. This paper, proposes an energy consumption model using two-tier clustering in mobile sensor networks (TTCM). This method divides the entire network into two layers. The mobility problem was considered, whole energy consumption was decreased and clustering methods of recent researches were analyzed for the proposed energy consumption model. Through analysis and simulation, the proposed TTCM was found to be better than the previous clustering method in mobile sensor networks at point of the network energy efficiency.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.6 s.324
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• pp.49-58
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• 2004

The existing route re-establishment methods which intend to extend the lifetime of the network attempt to find a new route in order not to overly consume energy of certain nodes. These methods outperforms other routing algorithms in the network lifetime aspect because that they try to consume energy evenly for the entire network. However, these algorithms involve heavy signaling overheads because they find new routes based on flooding method and route re-establishment occurs often. Because of the overhead they often can not achieve the level of performance they intend to. In this paper, we propose a new route selection algorithm which takes into account costs for the packet transmission and the route re-establishment. Since the proposed algerian considers future route re-establishment costs when it first find the route, it spends less energy to transmit given amount of data while evenly consuming energy as much as possible. Simulation results show that the proposed algorithm outperforms the existing route re-establishment methods in that after simulation it has the largest network energy which is the total summation of remaining energy of each node, the smallest energy consumed for route re-establishment, and the smallest energy needed for maintaining a session.

• Journal of Korea Multimedia Society
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• v.14 no.9
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• pp.1138-1151
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• 2011

Sensor network clustering scheme is an efficient method that prolongs network lifetime. However, when it is applied to an environment in which collected data of the sensor nodes easily overlap, sensor node unnecessarily consumes energy. Accordingly, we proposed a data prediction scheme that sensor node can predict current data to exclude redundant data transmission and to minimize data transmission among the cluster head node and member nodes. Our scheme excludes redundant data collection by neighbor nodes. Thus it is possible that energy efficient data transmission. Moreover, to alleviate unnecessary data transmission, we introduce data prediction graph whether transmit or not through analyze between prediction and current data. According to the result of performance analysis, our method consume less energy than the existing clustering method. Nevertheless, transmission efficiency and data accuracy is increased. Consequently, network lifetime is prolonged.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.141-150
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• 2005

Wireless Sensor Networks have been rapidly developed due to the advances of sensor technology and are expected to be applied to various applications in many fields. In Wireless Sensor Networks, schemes for managing the network energy-efficiently are most important. For this purpose, there have been a variety of researches to suggest routing protocols. However, existing researches have ideal assumption that all sensor nodes have sensing data to transmit. In this paper, we designed and implemented a sensing-aware cluster selection algorithm based on LEACH-C for the sensor network in which part of sensors have sensing data. We also simulated proposed algorithm on several network situation and analyzed which situation is suitable for the algorithm. By the simulation result, selecting cluster head among the sensing nodes is most energy-efficient and the result shows application of sensing-awareness in cluster head selection when not all sensors have sensing data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.2
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• pp.29-34
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• 2008

In this paper, we proposed a system protocol for detecting injurious insect to support energy saving transmission in wireless bio sensor networks. The main ideas and features of the system are as follows. First, the route establishment method which is based on the energy efficiency and stability by using time-division tree structure. Second, multi-hop direction-based data gatering structure. In this structure, the selected fading method is used to transmit packet via the established tree structure for supporting power saving and route lifetime efficiently. Finally, we can get the node power saving and reduce transmission delay, thus network lifetime and efficiency are improved. The performance evaluation of the proposed protocol is via OPNET(Optimized Network Engineering Tool).