• Journal of Computing Science and Engineering
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• v.4 no.2
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• pp.128-152
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• 2010

With the advance of computer and communication technologies, wireless sensor networks (WSNs) are increasingly used in many aspects of our daily life. However, since the battery lifetime of WSN nodes is restricted, the WSN lifetime is also limited. Therefore, it is crucial to determine this limited lifetime in advance for preventing service interruptions in critical applications. This paper proposes a feasible static analysis approach to estimating the worstcase lifetime of a WSN. Assuming known routes with a given sensor network topology and SMAC as the underlying MAC protocol, we statically estimate the lifetime of each sensor node with a fixed initial energy budget. These estimations are then compared with the results obtained through simulation which run with the same energy budget on each node. Experimental results of our research on TinyOS applications indicate that our approach can safely and accurately estimate worst-case lifetime of the WSN. To the best of our knowledge, our work is the first one to estimate the worst-case lifetime of WSNs through a static analysis method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2302-2324
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• 2014

Cluster-based wireless sensor network (WSN) can significantly reduce the energy consumption by data aggregation and has been widely used in WSN applications. However, due to the intrinsic many-to-one traffic pattern in WSN, the network lifetime is generally deteriorated by the unbalanced energy consumption in a cluster-based WSN. Therefore, energy efficiency and network lifetime improvement are two crucial and challenging issues in cluster-based WSNs. In this paper, we propose a Non-Uniform Node Distribution (NUND) scheme to improve the energy efficiency and network lifetime in cluster-based WSNs. Specifically, we first propose an analytic model to analyze the energy consumption and the network lifetime of the cluster-based WSNs. Based on the analysis results, we propose a node distribution algorithm to maximize the network lifetime with a fixed number of sensor nodes in cluster-based WSNs. Extensive simulations demonstrate that the theoretical analysis results determined by the proposed analytic model are consistent with the simulation results, and the NUND can significantly improve the energy efficiency and network lifetime.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.260-263
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• 2019

Recently, the need of researches and developments about WSN(Wireless Sensor Network) technologies, which can be applied to services to regions where the access is difficult or services that require continuous monitoring, has gradually increased due to its expansion and efficiency of the application areas. In this paper, we analyze existing researches which focused on reducing packet loss rate and increasing lifetime of sensor nodes. Then, we conduct studies about performance improvement factors where some schemes - clustering and location-based approaches - are applied and compare our study results with existing researches. Based on our studies, we are planning to conduct researches about a new scheme that could contribute to improve WSN's performance in terms of packet loss rate and network lifetime.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.389-392
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• 2007

In this paper, we propose an algorithm that improve network lifetime by adjusting cluster size according to location information of sensor node in wireless sensor network (WSN) using clustering technique. The sensed information in each cluster transfers to sink node through inter-cluster communications. Cluster head (CH) that nearby located in sink node much more spend own energy than far away CHs, because nearer CH forwards more data, so network lifetime is decreased. Proposed algorithm minimizes energy consumption in adjacent cluster to sink node by decreasing cluster site, and improve CH lifetime by distributing transmission paths. As a result of analysis, the proposed algorithm shows longer network lifetime in WSN.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.6
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• pp.1201-1206
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• 2007

In this paper, we propose an algorithm that improve network lifetime by adjusting cluster size according to location information of sensor node in wireless sensor network (WSN) using clustering algorithm. The collected sensing information by sensor nodes in each cluster are transferred to sink node using inter-cluster communications method. Cluster head (CH) that located nearby sink node spend much more energy than those of far from sink node, because nearer CH forwards more data, so network lifetime has a tendency to decrease. Proposed algorithm minimizes energy consumption in adjacent cluster to sink node by decreasing cluster size, and improve CH lifetime by distributing transmission paths. As a result of mathematical analysis, the proposed algorithm shows longer network lifetime in WSN.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.901-920
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• 2015

Wireless Sensor Networks (WSNs) are widely used in geographically isolated applications like military border area monitoring, battle field surveillance, forest fire detection systems, etc. Uninterrupted power supply is not possible in isolated locations and hence sensor nodes live on their own battery power. Localization of sensor nodes in isolated locations is important to identify the location of event for further actions. Existing localization algorithms consume more energy at sensor nodes for computation and communication thereby reduce the lifetime of entire WSNs. Existing approaches also suffer with less localization coverage and localization accuracy. The objective of the proposed work is to increase the lifetime of WSNs while increasing the localization coverage and localization accuracy. A novel intelligent unmanned aerial vehicle anchor node (IUAN) is proposed to reduce the communication cost at sensor nodes during localization. Further, the localization computation cost is reduced at each sensor node by the proposed intelligent arc selection (IAS) algorithm. IUANs construct the location-distance messages (LDMs) for sensor nodes deployed in isolated locations and reach the Control Station (CS). Further, the CS aggregates the LDMs from different IUANs and computes the position of sensor nodes using IAS algorithm. The life time of WSN is analyzed in this paper to prove the efficiency of the proposed localization approach. The proposed localization approach considerably extends the lifetime of WSNs, localization coverage and localization accuracy in isolated environments.

• ETRI Journal
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• v.39 no.3
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• pp.353-363
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• 2017

Recently, sink mobility has been shown to be highly beneficial in improving network lifetime in wireless sensor networks (WSNs). Numerous studies have exploited mobile sinks (MSs) to collect sensed data in order to improve energy efficiency and reduce WSN operational costs. However, there have been few studies on the effectiveness of MS operation on WSN closed operating cycles. Therefore, it is important to investigate how data is collected and how to plan the trajectory of the MS in order to gather data in time, reduce energy consumption, and improve WSN network lifetime. In this study, we combine two methods, the cluster-head election algorithm and the MS trajectory optimization algorithm, to propose the optimal MS movement strategy. This study aims to provide a closed operating cycle for WSNs, by which the energy consumption and running time of a WSN is minimized during the cluster election and data gathering periods. Furthermore, our flexible MS movement scenarios achieve both a long network lifetime and an optimal MS schedule. The simulation results demonstrate that our proposed algorithm achieves better performance than other well-known algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5437-5454
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• 2016

A Wireless Sensor Network (WSN) is composed of several sensor nodes which are severely restricted to energy and memory. Energy is the lifeblood of sensors and thus energy conservation is a critical necessity of WSN. This paper proposes a clustering algorithm namely Energy Efficient Trustworthy Clustering algorithm (EETCA), which focuses on three phases such as chief node election, chief node recycling process and bi-level trust computation. The chief node election is achieved by Dempster-Shafer theory based on trust. In the second phase, the selected chief node is recycled with respect to the current available energy. The final phase is concerned with the computation of bi-level trust, which is triggered for every time interval. This is to check the trustworthiness of the participating nodes. The nodes below the fixed trust threshold are blocked, so as to ensure trustworthiness. The system consumes lesser energy, as all the nodes behave normally and unwanted energy consumption is completely weeded out. The experimental results of EETCA are satisfactory in terms of reduced energy consumption and prolonged lifetime of the network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.514-537
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• 2020

Wireless sensor network (WSN) is a distributed network composed of many sensory nodes. It is precisely due to the clustering unevenness and cluster head election randomness that the energy consumption of WSN is excessive. Therefore, a many-objective optimization WSN energy balance model is proposed for the first time in the clustering stage of LEACH protocol. The four objective is considered that the cluster distance, the sink node distance, the overall energy consumption of the network and the network energy consumption balance to select the cluster head, which to better balance the energy consumption of the WSN network and extend the network lifetime. A many-objective optimization algorithm to optimize the model (LEACH-ABF) is designed, which combines adaptive balanced function strategy with penalty-based boundary selection intersection strategy to optimize the clustering method of LEACH. The experimental results show that LEACH-ABF can balance network energy consumption effectively and extend the network lifetime when compared with other algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1298-1310
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• 2019

Network coding (NC) is a promising technology that can improve available bandwidth and packet throughput in wireless sensor networks (WSNs). Sliding window is an improved technology of NC, which is a supplement of TCP/IP technology and can improve data throughput and network lifetime on WSNs. This paper proposes a network coding-based maximum lifetime algorithm for sliding window in WSNs (NC-MLSW) which improves the throughput and network lifetime in WSN. The packets on the source node are sent on the WSNs. The intermediate node encodes the received original packet and forwards the newly encoded packet to the next node. Finally, the destination node decodes the received encoded data packet and recovers the original packet. The performance of the NC-MLSW algorithm is studied using NS2 simulation software and the network packet throughput, network lifetime and data packet loss rate were evaluated. The simulations experiment results show that the NC-MLSW algorithm can obviously improve the network packet throughput and network lifetime.