• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.5
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• pp.40-52
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• 2010

A mobile ad hoc network is instant and heuristic, and it is also vulnerable and volatile. Since topology and route changes are frequent, no single routing protocol designed for a conventional network performs well. Some protocols suffer from significant performance degradation when the number of nodes increases, or when nodes become highly mobile. In this paper we investigate a way to adaptively select a routing protocol that fits to the real-time network conditions. The first phase of our study is to analyze the performances of two classes of routing protocols under various network scenarios. The second phase consists of constructing a routing protocol selection reference. All nodes continue to monitor the status of neighbor nodes and control packets exchanged. Then, the aggregated information is periodically compared against the protocol selection reference. The selected routing protocol is maintained throughout the network until the network property changes substantially. The performance of the proposed algorithm is verified by a set of computer simulations using the OPNET modeler. The experimental results show that selectively changing routing protocol adaptive to the network conditions greatly improves the efficacy of bandwidth utilization.

• 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).

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1113-1128
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• 2020

Ad hoc networks play an important role in mobile communications, and the performance of nodes has a significant impact on the choice of communication links. To ensure efficient and secure data forwarding and delivery, an intelligent routing protocol (IAODV) based on learning method is constructed. Five attributes of node energy, rate, credit value, computing power and transmission distance are taken as the basis of segmentation. By learning the selected samples and calculating the information gain of each attribute, the decision tree of routing node is constructed, and the rules of routing node selection are determined. IAODV algorithm realizes the adaptive evaluation and classification of network nodes, so as to determine the optimal transmission path from the source node to the destination node. The simulation results verify the feasibility, effectiveness and security of IAODV.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.2
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• pp.107-114
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• 2024

Mobile ad hoc networks represent self-configuring networks of mobile devices that communicate without relying on a fixed infrastructure. However, traditional routing protocols in such networks encounter challenges in selecting efficient and reliable routes due to dynamic nature of these networks caused by unpredictable mobility of nodes. This often results in a failure to meet the low-delay and low-energy consumption requirements crucial for such networks. In order to overcome such challenges, our paper introduces a novel multi-objective and adaptive routing scheme based on the Q-learning reinforcement learning algorithm. The proposed routing scheme dynamically adjusts itself based on measured network states, such as traffic congestion and mobility. The proposed approach utilizes Q-learning to select routes in a decentralized manner, considering factors like energy consumption, load balancing, and the selection of stable links. We present a formulation of the multi-objective optimization problem and discuss adaptive adjustments of the Q-learning parameters to handle the dynamic nature of the network. To speed up the learning process, our scheme incorporates informative shaped rewards, providing additional guidance to the learning agents for better solutions. Implemented on the widely-used AODV routing protocol, our proposed approaches demonstrate better performance in terms of energy efficiency and improved message delivery delay, even in highly dynamic network environments, when compared to the traditional AODV. These findings show the potential of leveraging reinforcement learning for efficient routing in ad hoc networks, making the way for future advancements in the field of mobile ad hoc networking.

• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.1-6
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• 2024

Energy efficiency in wireless sensor networks (WSNs) is a critical issue because batteries are used for operation and communication. In terms of scalability, energy efficiency, data integration, and resilience, WSN-cluster-based routing algorithms often outperform routing algorithms without clustering. Low-energy adaptive clustering hierarchy (LEACH) is a cluster-based routing protocol with a high transmission efficiency to the base station. In this paper, we propose an energy consumption model for LEACH and compare it with the existing LEACH, advanced LEACH (ALEACH), and power-efficient gathering in sensor information systems (PEGASIS) algorithms in terms of network lifetime. The energy consumption model comprises energy-sensitive cluster formation and a cluster head selection technique. The setup and steady-state phases of the proposed model are discussed based on the cluster head selection. The simulation results demonstrated that a low-energy-consumption network was introduced, modeled, and validated for LEACH.

• Proceedings of the IEEK Conference
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• summer
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• pp.330-333
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• 2004

Microsensor nodes is energy limited in sensor networks. If nodes had been stop in working, sensor network can't acquire sensing data in that area as well as routing path though the sensor can't be available. So, it's important to maximize the life of network in sensor network. In this paper, we look at communication protocol, which is modified by LEACH(Low-Energy Adaptive Clustering Hierarchy). We extend LEACH's stochastic cluster-head selection algorithm by a Position-based Selection (PB-Leach). This method is that the sink divides the topology into several areas and cluster head is only one in an area. PB-Leach can prevent that the variance of the number of Cluster-Head is large and Cluster-Heads are concentrated in specific area. Simulation results show that PB-Leach performs better than leach by about 100 to $250\%.$

• International Journal of Advanced Culture Technology
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• v.4 no.2
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• pp.19-26
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• 2016

The most important factor in the wireless sensor network is the use of effective energy and increase in lifetime of the individual nodes in order to operate the wireless network more efficiently. For this purpose, various routing protocols have been developed. The LEACH such a protocol, well known among typical cluster routing protocols. However, when a cluster head is selected, the energy consumption may not be equal because it does not take into account the energy of the nodes. In this paper, we seek to improve the cluster head selection method according to residual energy of each sensor node. This method then adaptively applies the LEACH algorithm and the cluster head section algorithm with consideration of node energy in accordance with the energy of the whole sensor field. Through the simulation, it was found that this proposed algorithm was effective.

• 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.

• The KIPS Transactions:PartC
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• v.18C no.3
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• pp.167-178
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• 2011

As the growth of ubiquitous services, various types of ad hoc networks have emerged. In particular, wireless sensor networks (WSN) and mobile ad hoc networks (MANET) are widely known ad hoc networks, but there are also other kinds of wireless ad hoc networks in which the characteristics of the aforementioned two network types are mixed together. This paper proposes a variant of the Low Energy Adaptive Cluster Hierarchy (LEACH) routing protocol modified to be suitable in such a combined network environment. That is, the proposed routing protocol provides node detection and route discovery/maintenance in a network with a large number of mobile sensor nodes, while preserving node mobility, network connectivity, and energy efficiency. The proposed routing protocol is implemented with a multi-hop multi-path algorithm, a topology reconfiguration technique using node movement estimation and vibration sensors, and an efficient path selection and data transmission technique for a great many moving nodes. In the experiments, the performance of the proposed protocol is demonstrated by comparing it to the conventional LEACH protocol.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.3
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• pp.29-38
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• 2006

Recent advances in wireless communication technology promotes many researches related to sensor network and brings several proposals to fit into various types of sensor network communication. The research direction for sensor network is divided into the method to maximize an energy efficiency and security researches that has not been remarkable so far. To maximize an energy efficiency, the methods to support data aggregation and cluster-head selection algorithm are proposed. To strengthen the security, the methods to support encryption techniques and manage a secret key that is applicable to sensor network are proposed, In. However, the combined method to satisfy both energy efficiency and security is in the shell. This paper is devoted to design the protocol that combines an efficient clustering protocol with key management algorithm that is fit into various types of sensor network communication. This protocol may be applied to sensor network systems that deal with sensitive data.