• ETRI Journal
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• v.44 no.3
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• pp.389-399
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• 2022

Wireless sensor networks (WSNs) are one of the basic building blocks of Internet of Things (IoT) systems. However, the wireless sensing nodes in WSNs suffer from energy constraint issues because the replacement/recharging of the batteries of the nodes tends to be difficult. Furthermore, a number of realistic IoT scenarios, such as habitat and battlefield monitoring, contain mobile sensing elements, which makes the energy issues more critical. This research paper focuses on realistic WSN scenarios that involve mobile sensing elements with the aim of mitigating the attendant energy constraint issues using the concept of radio-frequency (RF) energy extraction. The proposed technique incorporates a cluster head election workflow for WSNs that includes mobile sensing elements capable of RF energy harvesting. The extensive simulation analysis demonstrated the higher efficacy of the proposed technique compared with the existing techniques in terms of residual energy, number of functional nodes, and network lifetime, with approximately 50% of the nodes found to be functional at the 4000th, 5000th, and 6000th rounds for the proposed technique with initial energies of 0.25, 0.5 and 1 J, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3683-3703
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• 2018

Wireless sensor networks (WSNs) consist of set of sensor nodes. These sensor nodes are deployed in unattended area which are able to sense, process and transmit data to the base station (BS). One of the primary issues of WSN is energy efficiency. In many existing clustering approaches, initial centroids of cluster heads (CHs) are chosen randomly and they form unbalanced clusters, results more energy consumption. In this paper, an energy efficient clustering protocol to prevent unbalanced clusters based on firefly and midpoint algorithms called EEC-FM has been proposed, where midpoint algorithm is used for initial centroid of CHs selection and firefly is used for cluster formation. Using residual energy and Euclidean distance as the parameters for appropriate cluster formation of the proposed approach produces balanced clusters to eventually balance the load of CHs and improve the network lifetime. Simulation result shows that the proposed method outperforms LEACH-B, BPK-means, Park's approach, Mk-means, and EECPK-means with respect to balancing of clusters, energy efficiency and network lifetime parameters. Simulation result also demonstrate that the proposed approach, EEC-FM protocol is 45% better than LEACH-B, 17.8% better than BPK-means protocol, 12.5% better than Park's approach, 9.1% better than Mk-means, and 5.8% better than EECPK-means protocol with respect to the parameter half energy consumption (HEC).

• Journal of Korea Multimedia Society
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• v.13 no.6
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• pp.911-923
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• 2010

In wireless sensor networks (WSNs), cluster based data routing protocols have the advantages of reducing energy consumption and link maintenance cost. Unfortunately, most of clustering protocols have been designed for uniformly distributed sensor networks. However, some urgent situations do not allow thousands of sensor nodes being deployed uniformly. For example, air vehicles or balloons may take the responsibility for deploying sensor nodes hence leading a normally distributed topology. In order to improve energy efficiency in such sensor networks, in this paper, we propose a new cluster formation algorithm named DAEEC (Density Aware Energy-Efficient Clustering). In this algorithm, we define two kinds of clusters: Low Density (LD) clusters and High Density (HD) clusters. They are determined by the number of nodes participated in one cluster. During the data routing period, the HD clusters help the neighbor LD clusters to forward the sensed data to the central base station. Thus, DAEEC can distribute the energy dissipation evenly among all sensor nodes by considering the deployment density to improve network lifetime and average energy savings. Moreover, because the HD clusters are densely deployed they can work in a manner of our former algorithm EEVAR (Energy Efficient Variable Area Routing Protocol) to save energy. According to the performance analysis result, DAEEC outperforms the conventional data routing schemes in terms of energy consumption and network lifetime.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.9
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• pp.1799-1805
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• 2007

Wireless Ad-hoc networks may contain nodes of various types of which many can have limited power capabilities. A failure of a node due to energy exhaustion may impact the performance of the whole network hence, energy must be conserved. In this paper, we propose a Delay and Energy-Aware Routing (DEAR) algorithm a multiple metric path cost routing algorithm which considers not only the energy consumed by the node during transmission and reception but as well as the residual energy of the node and the delay incurred during route discovery. Based on our results, DEAR algorithm performs well and maximizes network lifetime by routing flows to nodes with sufficient energy such that the energy consumption is balanced among nodes in proportion to their energy reserves.

• The KIPS Transactions:PartC
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• v.17C no.5
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• pp.433-440
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• 2010

Energy efficiency, low latency and scalability for wireless sensor networks are important requirements, especially, the wireless sensor network consist of a large number of sensor nodes should be minimized energy consumption of each node to extend network lifetime with limited battery power. An efficient algorithm and energy management technology for minimizing the energy consumption at each sensor node is also required to improve transfer rate. Thus, this paper propose no-overlap multi-pass protocol provides for sensor data transmission in the wireless sensor network environment. The proposed scheme should minimize network overhead through reduced a sensor data translation use to searched multi-path and added the multi-path in routing table. Proposed routing protocol may minimize the energy consumption at each node, thus prolong the lifetime of the sensor network regardless of where the sink node is located outside or inside the received signal strength range. To verify propriety proposed scheme constructs sensor networks adapt to current model using the real data and evaluate consumption of total energy.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.2
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• pp.216-220
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• 2008

Sensor nodes in wireless network have several limitations such as lack of energy resource and network bandwidth. There are many researches to extend lifetime of sensor network and enhance availability. However, most of the previous researches didn't consider the mobile sink node. Those researches aren't suitable in the environment having mobile sinks. In this paper. we propose a scheme that reduces communication overheads and energy consumptions and improves reliability in routing path setup. Proposed scheme has excellent scalability without degrading performance in environment where many sink nodes exist and/or the network size is huge. Proposed scheme saves the energy consumption up to 70% in comparison with the previous grid-based and cluster-based protocol. As a result, proposed scheme increases the lifetime of sensor network and enhances availability of wireless sensor network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4301-4319
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• 2017

Adopting mobile chargers (MC) in rechargeable wireless sensors network (R-WSN) to recharge sensors can increase network efficiency (e.g., reduce MC travel distance per tour, reduce MC effort, and prolong WSN lifetime). In this study, we propose a mechanism to split the sensing field into partitions that may be equally spaced but differ in distance to the base station. Moreover, we focus on minimizing the MC effort by providing a new charging mechanism called the sector-based charging schedule (SBCS), which works to dispatch the MC in charging trips to the sector that sends many charging requests and suggesting an efficient sensor-charging algorithm. Specifically, we first utilize the high ability of the BS to divide the R-WSN field into sectors then it select the cluster head for each sector to reduce the intra-node communication. Second, we formulate the charging productivity as NP-hard problem and then conduct experimental simulations to evaluate the performance of the proposed mechanism. An extensive comparison is performed with other mechanisms. Experimental results demonstrate that the SBCS mechanism can prolong the lifetime of R-WSNs by increasing the charging productivity about 20% and reducing the MC effort by about 30%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.649-651
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• 2017

A clustering problem is one of the organizational problems to improve the network lifetime and scalability in wireless ad-hoc networks. This problem is a difficult combinatorial optimization problem associated with the design and operation of these networks. In this paper, we propose an efficient clustering algorithm to maximize the network lifetime and consider scalability in wireless ad-hoc networks. The clustering problem is known to be NP-hard. We thus solve the problem by using optimization approaches that are able to efficiently obtain high quality solutions within a reasonable time for a large size network. The proposed algorithm selects clusterheads and configures clusters by considering both nodes' power and the clustering cost. We evaluate this performance through some experiments in terms of nodes' transmission energy. Simulation results indicate that the proposed algorithm performs much better than the existing algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.3
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• pp.534-539
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• 2005

The key in wireless sensor networks, which consist of a number of sensor nodes, is an energy efficiency. Many routing protocols have been proposed for prolonging network lifetime and reducing traffic in wireless sensor networks. Wireless sensor networks usually use wireless ad-hoc network protocols for routing, but these protocols are not well-suited for wireless sensor networks due to many reasons. In this paper, RM-flooding protocol is proposed for reducing routing overhead occurred when packet flooding. The nodes using this routing protocol can consume the limited energy effectively, and exchange information with remote nodes usulg information receiving from multipath. So, RM-flooding prolongs the network's lifetime.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.608-614
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• 2009

In wireless sensor networks, there are hundreds to thousands of small battery powered devices which are called sensors. As sensors have a limited energy resources, there is a need to use it effectively. A clustering based routing protocol forms clusters by distributed algorithm. Member nodes send their data to their cluster heads then cluster heads integrate data and send to sink node. In this paper we propose an energy efficient cluster-head selection algorithm. We have used some factors(a previous cluster head experience, a existence of data to transmit and an information that neighbors have data or not) to select optimum cluster-head and eventually improve network lifetime. Our simulation results show its effectiveness in balancing energy consumption and prolonging the network lifetime compared with LEACH and HEED algorithms.