• IEMEK Journal of Embedded Systems and Applications
• /
• v.19 no.2
• /
• pp.107-114
• /
• 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 the Korea Institute of Information and Communication Engineering
• /
• v.22 no.4
• /
• pp.676-682
• /
• 2018

In wireless sensor networks, we propose an optimization algorithm in order to minimize the consumed energy of nodes for maritime search and rescue. In the marine environment, search and rescue operations are mainly performed on the surveillance side and passively on the rescued side. A self-configurable wireless sensor network can build a system that can send rescue signals in the operations. A simulated annealing algorithm is proposed to minimize the consumed energy of nodes in the networks with many nodes. As the density of nodes becomes higher, the algorithmic computation will increase highly. To search the good result in a proper execution time, the proposed algorithm proposes a new neighborhood generating operation and improves the efficiency of the algorithm. The proposed algorithm was evaluated in terms of the consumed energy of the nodes and algorithm execution time, and the proposed algorithm performed better than other optimization algorithms in the performance results.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.1B
• /
• pp.15-30
• /
• 2000

The important considerations in the design of fiber-optic networks are reliability and survivability preparing against a failure. The SDH(Synchronous Digital Hierarchy), the international standard of optical transmission, offers several network reconfiguration methods that enable network to be automatically restored from failure. One of the methods is the SHR(Self Healing Ring), which is a ring topology system. Most network providers have constructed their backbone networks with SHR architecture since it can provide survivability economically. The network architecture has eventually evolved into a multi-ring network comprised of interconnected rings. This paper addresses multi-ring network design problems is to minimize ring-construction cost. This problem can be formulated with MIP(mixed integer programming) model. However, it is difficult to solve the model within reasonable computing time on a large scale network because the model is NP-complete. Furthermore, in practice we should consider the problem of routing demands on rings to minimize total cost. This routing problem involves multiplex bundling at the intermediate nodes. A family of heuristic algorithms is presented for this problem. These algorithms include gateway selection and routing of inter-ring demands as well as load balancing on single rings. The developed heuristic algorithms are applied to some network provider's regional and long-distance transmission networks. We show an example of ring design and compare it with another ring topology design. Finally, we analysis the effect bundling.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.7
• /
• pp.1585-1609
• /
• 2013

Over recent years, enormous amounts of research in wireless sensor networks (WSNs) have been conducted, due to its multifarious applications such as in environmental monitoring, object tracking, disaster management, manufacturing, monitoring and control. In some of WSN applications dependent the energy-efficient and link reliability are demanded. Hence, this paper presents a routing protocol that considers these two criteria. We propose a new mechanism called Reliable Routing Scheme for Energy-Balanced (RRSEB) to reduce the packets dropped during the data communications. It is based on Swarm Intelligence (SI) using the Ant Colony Optimization (ACO) method. The RRSEB is a self-adaptive method to ensure the high routing reliability in WSNs, if the failures occur due to the movement of the sensor nodes or sensor node's energy depletion. This is done by introducing a new method to create alternative paths together with the data routing obtained during the path discovery stage. The goal of this operation is to update and offer new routing information in order to construct the multiple paths resulting in an increased reliability of the sensor network. From the simulation, we have seen that the proposed method shows better results in terms of packet delivery ratio and energy efficiency.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.7 no.4
• /
• pp.74-81
• /
• 1997

This paper proposes an evolutionary learning algorithm to discipline the projection neural nctworks (PNNs) with special type of hidden nodes which can activate radial basis functions as well as sigmoid functions. The proposed algorithm not only trains the parameters and the connection weights hut also c~ptimizes the network structure. Through the structure optimization, the number of hidden node:; necessary to represent a given target function is determined and the role of each hidden node is decided whether it activates a radial basis function or a sigmoid function. To apply the algorithm, PNN is realized by a self-organizing genotype representation with a linked list data structure. Simulations show that the algorithm can build the PNN with less hidden nodes than thc existing learning algorithm using error hack propagation(EE3P) and network growing strategy.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.2
• /
• pp.542-558
• /
• 2016

Vehicular Ad Hoc Networks (VANETs) are self-configuring networks where the nodes are vehicles equipped with wireless communication technologies. In such networks, limitation of signal coverage and fast topology changes impose difficulties to the proper functioning of the routing protocols. Traditional Mobile Ad Hoc Networks (MANET) routing protocols lose their performance, when communicating between vehicles, compromising information exchange. Obviously, most applications critically rely on routing protocols. Thus, in this work, we propose a methodology for investigating the performance of well-established protocols for MANETs in the VANET arena and, at the same time, we introduce a routing protocol, called Genetic Network Protocol (G-NET). It is based in part on Dynamic Source Routing Protocol (DSR) and on the use of Genetic Algorithms (GAs) for maintenance and route optimization. As G-NET update routes periodically, this work investigates its performance compared to DSR and Ad Hoc on demand Distance Vector (AODV). For more realistic simulation of vehicle movement in urban environments, an analysis was performed by using the VanetMobiSim mobility generator and the Network Simulator (NS-3). Experiments were conducted with different number of vehicles and the results show that, despite the increased routing overhead with respect to DSR, G-NET is better than AODV and provides comparable data delivery rate to the other protocols in the analyzed scenarios.

• ETRI Journal
• /
• v.39 no.6
• /
• pp.794-802
• /
• 2017

In this paper, a wireless powered communication network (WPCN) consisting of a hybrid access point (H-AP) and multiple user equipment (UE), all of which operate in full-duplex (FD), is described. We first propose a transceiver structure that enables FD operation of each UE to simultaneously receive energy in the downlink (DL) and transmit information in the uplink (UL). We then provide an energy usage model in the proposed UE transceiver that accounts for the energy leakage from the transmit chain to the receive chain. It is shown that the throughput of an FD WPCN using the proposed FD UE (FD-WPCN-FD) can be maximized by optimal allocation of the UL transmission time to the UE by solving a convex optimization problem. Simulation results reveal that the use of the proposed FD UE efficiently improves the throughput of a WPCN with a practical self-interference cancellation capability at the H-AP. Compared to the WPCN with FD H-AP and half-duplex (HD) UE, FD-WPCN-FD achieved an 18% throughput gain. In addition, the throughput of FD-WPCN-FD was shown to be 25% greater than that of WPCN in which an H-AP and UE operated in HD.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.1018-1021
• /
• 2009

Wireless Sensor Network collects a data from the specific area and the control is composed of small sensor nodes. Like this sensors to after that is established at the beginning are operated with the battery, the operational duration until several years must be continued from several months and will be able to apply the resources which is restricted in efficiently there must be. In this paper RHC (rounting history cache) applies in Directed Diffusion which apply a data central concept a reliability and an efficiency in data transfer course set. RHC algorithms which proposes each sensor node updated RHC of oneself with periodic and because storing the optimization course the course and, every event occurrence hour they reset the energy is wasted the fact that a reliability with minimization of duplication message improved.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.8 no.5
• /
• pp.61-71
• /
• 1998

Genetic Algorithm(GA) is a method of approaching optimization problems by modeling and simulating the biological evolution. GA needs large time-consuming, so ti had better do on a parallel computer architecture. Our proposed system has a VLSI-oriented interconnection network, which is constructed from a viewpoint of fractal geometry, so that self-similarity is considered in its configuration. The approach to Parallel Genetic Algorithm(PGA) on our proposed system is explained, and then, we construct the classifier system such that the set of samples is classified into weveral classes based on the features of each sample. In the process of designing the classifier system, We have applied PGA to the Traveling Salesman Problem and classified the sample set in the Euclidean space into several categories with a measure of the distance.

• Proceedings of the KIEE Conference
• /
• 1998.07b
• /
• pp.681-683
• /
• 1998

Fuzzy Inference System is to trans late and be concrete with human expert in to mathematical equation. It is easy to be applied for Nonlinear System and the know ledge can be applied at that. With using the rule according to the Knowledge, when it is realized simulations must be required repeatedly and small vibration is generated in steady state, too. In this paper, we applied the system to the methodology of optimization with self-learn ing by us ing ANFIS(Adaptive Network-based Fuzzy Inference System) which makes use of back-propagation and least square method at a first order Sugeno Fuzzy System. In order to show the effect of Algorithm, we demonstrated it by us ing Rotary Inverted Pendulum.