• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.65-73
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• 2014

Since Time synchronization is also critical in Wireless Sensor Networks (WSN) like other networks, a time synchronization protocol for WSN called IBS(Indirect-Broadcast Synchronization) has been already proposed in 2012. As IBS operates in cluster tree topology, network lifetime may be mainly shortened by cluster head node[s], which usually consumes more power than cluster member (i.e. non-cluster head) nodes. In this paper, I propose enhanced version of IBS (called EIBS) which saves overall energy and prolongs network lifetime by re-constructing partial cluster tree locally. Compared with other tree construction approaches, this tree reconstruction algorithm is not only simpler, but also more efficient in the light of overall power consumption and network lifetime.

• The Journal of Information Technology
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• v.2 no.2
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• pp.13-22
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• 1999

In this paper, we purpose automatic diagnosis in online, as the fundamental study to diagnose the partial discharge mechanism and to predict the lifetime by introduction a neural network. In the proposed method, we use AE(acoustic emission) sensing system and calculate a quantitative statistic parameter by pulse number and amplitude. Using statically parameters such as the center of gravity(G) and the gradient if the discharge distribute(C), we analyzed the early stage and the middle stage. the quantitative statistic parameters are learned by a neural network. The diagnosis of insulation degradation and a lifetime prediction by the early stage time are achieved. On the basis of revealed excellent diagnosis ability through the neural network learning for the patterns during degradation, it was proved that the neural network is appropriate for degradation diagnosis and lifetime prediction in partial discharge.

• Journal of Information Processing Systems
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• v.6 no.3
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• pp.295-306
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• 2010

Network lifetime is a critical issue in Wireless Sensor Networks (WSNs). In which, a large number of sensor nodes communicate together to perform a predetermined sensing task. In such networks, the network life time depends mainly on the lifetime of the sensor nodes constituting the network. Therefore, it is essential to balance the energy consumption among all sensor nodes to ensure the network connectivity. In this paper, we propose an energy-efficient data routing protocol for wireless sensor networks. Contrary to the protocol proposed in [6], that always selects the path with minimum hop count to the base station, our proposed routing protocol may choose a longer path that will provide better distribution of the energy consumption among the sensor nodes. Simulation results indicate clearly that compared to the routing protocol proposed in [6], our proposed protocol evenly distributes the energy consumption among the network nodes thus maximizing the network life time.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.18-25
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• 2014

A implanted sensor's error probability is more likely to external sensor's error probability by biological characteristic in WBAN. In this paper, we present method that external sensor transmits frame instead of doing implanted sensor's retransmission for improving lifetime of implanted sensors in WBAN. The proposed method, LI(Lifetime Increment) protocol is to add external sensor's id in transmission data frame of a implanted sensor. When the retransmission is required, external sensor that have to registered id in data frame retransmits frame instead of implanted sensors' retransmission. The comparison result shows that the proposed protocol reduces power consumption and improves life time.

• ETRI Journal
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• v.40 no.5
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• pp.604-612
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• 2018

To solve the problem of unbalanced loads and the short network lifetime of heterogeneous wireless sensor networks, this paper proposes a node-selection algorithm based on energy balance and dynamic adjustment. The spacing and energy of the nodes are calculated according to the proximity to the network nodes and the characteristics of the link structure. The direction factor and the energy-adjustment factor are introduced to optimize the node-selection probability in order to realize the dynamic selection of network nodes. On this basis, the target path is selected by the relevance of the nodes, and nodes with insufficient energy values are excluded in real time by the establishment of the node-selection mechanism, which guarantees the normal operation of the network and a balanced energy consumption. Simulation results show that this algorithm can effectively extend the network lifetime, and it has better stability, higher accuracy, and an enhanced data-receiving rate in sufficient time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.4
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• pp.774-784
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• 2009

A wireless sensor network consisting of a large number of nodes with limited battery power should minimize energy consumption at each node to prolong the network lifetime. To improve the sensitivity of wireless sensor networks, an efficient scheduling algorithm and energy management technology for minimizing the energy consumption at each node is desired. ill this paper, we propose energy-aware routing mechanism for maximum lifetime and to optimize the solution quality for sensor network maintenance and to relay node from its adjacent cluster heads according to the node"s residual energy and its distance to the base station. Proposed protocol may minimize the energy consumption at each node, thus prolong the lifetime of the system regardless of where the sink is located outside or inside the cluster. Simulation results of proposed scheme show that our mechanism balances the energy consumption well among all sensor nodes and achieves an obvious improvement on the network lifetime. To verify propriety using NS-2, proposed scheme constructs sensor networks adapt to current model and evaluate consumption of total energy, energy consumption of cluster head, average energy dissipation over varying network areas with HEED and LEACH-C.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.64-69
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• 2017

The abstract should summarize the contents of the paper and written below the author information. Use th In Wide-area Wireless Sensor Networks, network lifetime is short due to energy consumption due to transmission distance. To improve this, we divide the sensor field into layers and reduce transmission distance through multi-hop transmission. However, there is a problem in that the transmission rate drops because there is no Cluster Head in the layer, or the transmission distance increases due to the layer, and energy is wasted. There are DL-LEACH and EDL-LEACH as Protocols to improve this. DL-LEACH uses either single-hop transmission or multi-hop transmission depending on the situation. As a result, the transmission distance is optimized, thereby reducing energy consumption. In case of EDL-LEACH, it is proposed to improve the data rate in DL-LEACH. It is the same as DL-LEACH, but the Cluster Head is mandatory for all layers to improve the transmission rate. Although there is no Cluster Head for each layer, the transmission rate is improved, but the network life is shortened. In this paper, we try to improve the network lifetime while maintaining the EDL-LEACH transmission rate. The shortened network lifetime is due to Cluster Head overload near the base station. To improve this, the Cluster Head distribution method is improved and the network lifetime is improved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1618-1637
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• 2014

Clustering wireless sensor network is an efficient way to reduce the energy consumption of individual nodes in a cluster. In clustering, multihop routing techniques increase the load of the Cluster head near the sink. This unbalanced load on the Cluster head increases its energy consumption, thereby Cluster heads die faster and create an energy hole problem. In this paper, we propose an Energy Balancing Cluster Head (EBCH) in wireless sensor network. At First, we balance the intra cluster load among the cluster heads, which results in nonuniform distribution of nodes over an unequal cluster size. The load received by the Cluster head in the cluster distributes their traffic towards direct and multihop transmission based on the load distribution ratio. Also, we balance the energy consumption among the cluster heads to design an optimum load distribution ratio. Simulation result shows that this approach guarantees to increase the network lifetime, thereby balancing cluster head energy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4B
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• pp.346-353
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• 2011

Routing schemes that service applications with various delay times, maintaining the long network life time are required in wireless sensor & actor networks. However, it is known that network lifetime and hop count of trees used in routing methods have the tradeoff between them. In this paper, we propose a Pareto Ant Colony Optimization algorithm to find the Pareto tree set such that it optimizes these both tradeoff objectives. As it enables applications which have different delay times to select appropriate routing trees, not only satisfies the requirements of various multiple applications but also guarantees long network lifetime. We show that the Pareto tree set found by proposed algorithm consists of trees that are closer to the Pareto optimal points in terms of hop count and network lifetime than minimum spanning tree which is a representative routing tree.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.833-852
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• 2019

In real time applications, due to their effective cost and small size, wireless networks play an important role in receiving particular data and transmitting it to a base station for analysis, a process that can be easily deployed. Due to various internal and external factors, networks can change dynamically, which impacts the localisation of nodes, delays, routing mechanisms, geographical coverage, cross-layer design, the quality of links, fault detection, and quality of service, among others. Conventional methods were programmed, for static networks which made it difficult for networks to respond dynamically. Here, machine learning strategies can be applied for dynamic networks effecting self-learning and developing tools to react quickly and efficiently, with less human intervention and reprogramming. In this paper, we present a wireless networks survey based on different machine learning algorithms and network lifetime parameters, and include the advantages and drawbacks of such a system. Furthermore, we present learning algorithms and techniques for congestion, synchronisation, energy harvesting, and for scheduling mobile sinks. Finally, we present a statistical evaluation of the survey, the motive for choosing specific techniques to deal with wireless network problems, and a brief discussion on the challenges inherent in this area of research.