• IEIE Transactions on Smart Processing and Computing
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• v.4 no.2
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• pp.115-125
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• 2015

This paper presents a Cuckoo search algorithm to secure adversaries misdirecting multi-hop routing in Mobile ad hoc networks (MANETs) using a robust Trust Predicated Routing Framework with an optimized cluster head selection. The clustering technique designed in this framework leads to efficient routing in MANETs. The heavy work load in the node causes an energy drop in cluster head, which leads to re-clustering of the group, and another cluster head is selected to avoid packet loss during data transmission. The problem in the re-clustering process is that the overall efficiency of the routing process is reduced and the processing time is increased. A Cuckoo search based optimization algorithm is proposed to solve the problem of re-clustering by selecting the secondary cluster head within the initially formed cluster group and eliminating the reclustering process. The proposed framework enables a node to select a reliable and secure route for MANET and the performance can be evaluated by comparing the simulated results with the AODV routing protocol, which shows that the performance of the proposed routing protocol are improved significantly.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.1
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• pp.30-35
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• 2015

The most important factor within the wireless sensor network is to have effective network usage and increase the lifetime of the individual nodes in order to operate the wireless network more efficiently. Therefore, many routing protocols have been developed. The LEACH protocol presented by Wendi Hein Zelman, especially well known as a simple and efficient clustering based routing protocol. However, because LEACH protocol in an irregular network is the total data throughput efficiency dropped, the stability of the cluster is declined. Therefore, to increase the stability of the cluster head, in this paper, it proposes a stochastic cluster head selection method for improving the LEACH protocol. To this end, it proposes a SH-LEACH (Stochastic Cluster Head Selection Method-LEACH) that it is combined to the HEED and LEACH protocol and the proposed algorithm is verified through the simulation.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.14-24
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• 2010

Because WSNs operate with limited resources of sensor nodes, its life is extended by cluster-based routing methods. In this study, we use data on direction, distance, density and residual energy in order to maximize the energy efficiency of cluster-based routing methods. Through this study, we expect to minimize the frequency of isolated nodes when selecting a new cluster head autonomously using information on the direction of the upper cluster head, and to reduce energy consumption by switching sensor nodes, which are included in both of the new cluster and the previous cluster and thus do not need to update information, into the sleep mode and updating information only for newly included sensor nodes at the setup phase using distance data. Furthermore, we enhance overall network efficiency by implementing secure and energy-efficient communication through key management robust against internal and external attacks in cluster-based routing techniques. This study suggests the modified cluster head selection scheme which uses the conserved energy in the steady-state phase by reducing unnecessary communications of unchanged nodes between selected cluster head and previous cluster head in the setup phase, and thus prolongs the network lifetime and provides secure and equal opportunity for being cluster head.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.6
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• pp.77-86
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• 2008

Traditional cluster-based routing method is a representative method for increasing the energy efficiencies. In these cluster-based routing methods, the selected cluster head collect/aggregate the information and send the aggregated information to the base station. But they have to solve the unnecessary energy dissipation of frequent information exchange between the cluster head and whole member nodes in cluster. In this paper, we minimize the frequency of the information exchange for reducing the unnecessary transmit/receive frequencies as calculate the overlapped area or number of overlapped member nodes between the selected cluster head and previous cluster head in the setup phase. And besides, we consider the direction of super cluster head for optimal cluster formation. So, we propose the modified cluster selection scheme that optimizes the energy dissipation in the setup phase and reuses the saved energy in the steady phase efficiently that prolongs the whole wireless sensor network lifetime by uniformly selecting the cluster head.

• International journal of advanced smart convergence
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• v.5 no.1
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• pp.66-72
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• 2016

In this paper, we proposed the clustering algorithm using fuzzy inference system for improving adaptability the cluster head selection of TEEN. The stochastic selection method cannot guarantee available of cluster head. Furthermore, because the formation of clusters is not optimized, the network lifetime is impeded. To improve this problem, we propose the algorithm that gathers attributes of sensor node to evaluate probability to be cluster head.

• The KIPS Transactions:PartC
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• v.17C no.3
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• pp.291-298
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• 2010

In wireless sensor networks, energy is the most important consideration because the lifetime of the sensor node is limited by battery. The clustering is the one of methods used to manage network energy consumption efficiently and LEACH(Low-Energy Adaptive Clustering Hierarchy) is one of the most famous clustering algorithms. LEACH utilizes randomized rotation of cluster-head to evenly distribute the energy load among the sensor nodes in the network. The random selection method of cluster-head does not guarantee the number of cluster-heads produced in each round to be equal to expected optimal value. And, the cluster head in a high-density cluster has an overload condition. In this paper, we proposed both a token based cluster-head selection algorithm for guarantee the number of cluster-heads and a cluster selection algorithm for uniform-density cluster. Through simulation, it is shown that the proposed algorithm improve the network lifetime about 9.3% better than LEACH.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.176-179
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• 2022

In this paper, we consider a sectorized wireless powered sensor network (WPSN), wherein sensor nodes are clustered based on sectors and transmit data to the cluster head (CH) using energy harvested from a hybrid access point. We construct a system model for this sectorized WPSN and find optimal coordinates of CH that maximize the achievable transmission rate of sensing data. To obtain the optimal CH with low overhead, we perform an asymptotic geometric analysis (GA). Simulation results show that the proposed GA-based CH selection method is close to the optimal performance exhibited by exhaustive search with a low feedback overhead.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2469-2490
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• 2019

A low-energy adaptive clustering hierarchy (LEACH) protocol is a low-power adaptive cluster routing protocol which was proposed by MIT's Chandrakasan for sensor networks. In the LEACH protocol, the selection mode of cluster-head nodes is a random selection of cycles, which may result in uneven distribution of nodal energy and reduce the lifetime of the entire network. Hence, we propose a new selection method to enhance the lifetime of network, in this selection function, the energy consumed between nodes in the clusters and the power consumed by the transfer between the cluster head and the base station are considered at the same time. Meanwhile, the improved FTBA algorithm integrating the curve strategy is proposed to enhance local and global search capabilities. Then we combine the improved BA with LEACH, and use the intelligent algorithm to select the cluster head. Experiment results show that the improved BA has stronger optimization ability than other optimization algorithms, which the method we proposed (FTBA-TC-LEACH) is superior than the LEACH and LEACH with standard BA (SBA-LEACH). The FTBA-TC-LEACH can obviously reduce network energy consumption and enhance the lifetime of wireless sensor networks (WSNs).

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.185-194
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• 2020

Designing of a hierarchical clustering algorithm is one of the numerous approaches to minimize the energy consumption of the Wireless Sensor Networks (WSNs). In this paper, a homogeneous and randomly deployed sensor nodes is considered. These sensors are energy constrained elements. The nominal selection of the Cluster Head (CH) which falls under the clustering part of the network protocol is studied and compared to Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. CHs in this proposed process is the function of total remaining energy of each node as well as total average energy of the whole arrangement. The algorithm considers initial energy, optimum value of cluster heads to elect the next group of cluster heads for the network as well as residual energy. Total remaining energy of each node is compared to total average energy of the system and if the result is positive, these nodes are eligible to become CH in the very next round. Analysis and numerical simulations quantify the efficiency and Average Energy Ratio (AER) of the proposed system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.620-623
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• 2014

Network topology for communication between vehicles are quickly changing because vehicles have a special movement pattern, especially character which is quickly changed by velocity and situation of road. Because of these feature, it is not easy to apply reliable routing on VANET(Vehicular Ad-hoc Network). Clustering method is one of the alternatives which are suggested for overcoming weakness of routing algorithm. Clustering is the way to communicate and manage vehicles by binding them around cluster head. Therefore choosing certain cluster head among vehicles has a decisive effect on decreasing overhead in relevant clustering and determining stability and efficiency of the network. This paper introduces new cluster head selection algorithm using RSU(Road Side Unit) different from existing algorithms. We suggest a more stable and efficient algorithm which decides a priority of cluster head by calculating vehicles' velocity and distance through RSU than existing algorithms.