• Korean Journal of Cognitive Science
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• v.2 no.2
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• pp.205-220
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• 1990

Material substance may exist in two different modes of reality:real as physcal objects that comprise material cause and formal cause, and real as function networks that comprise efficient cause and functional cause.Functional networks are real as a mode of material substance because their efficient cause is energy consuming.Neural functional network, in this sense, are different from neural networks.In the same way, mental functional networks are real, for they are energy consuming and they function as a network.Mental functional networks, in turn, may divide into non-lingustic functional networks and linguistic functional networks.And further distinctions among the different levels of mental functional networks will be specified, and hence their reality confirmed more specifically as the research in cognitive science advances.

• 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 Internet Computing and Services
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• v.8 no.5
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• pp.133-140
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• 2007

Currently, as the requirement for high quality Internet access from anywhere at anytime is consistently increasing, the interconnection of pure ad hoc networks to fixed IP networks becomes increasingly important. Such integrated network, referred to as hybrid ad hoc networks, can be extended to many applications, including Sensor Networks, Home Networks, Telematics, and so on. We focus on some data communication problems of hybrid ad hoc networks, such as broadcasting and routing. In particular. power failure of mobile terminals is the most important factor since it affects the overall network lifetime. We propose an energy-efficient routing protocol based on clustering for hybrid ad hoc networks. By applying the index-based data broadcasting and selective tuning methods, the infra system performs the major operations related to clustering and routing on behalf of ad hoc nodes. The proposed scheme reduces power consumption as well as the cost of path discovery and maintenance, and the delay required to configure the route.

• Journal of Korea Multimedia Society
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• v.18 no.4
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• pp.492-498
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• 2015

In general, data packets from sensor nodes are transferred to the sink node in a wireless sensor networks. So many data packets are gathered around the sink node, resulting in significant packet collision and delay. In this paper, we propose an efficient packet transmission mechanism for multi-hop wireless sensor networks. The proposed mechanism is composed of two modes. One mode works between sink node and 1-hop nodes from sink. In this mode, data packets are transmitted in predefined time slots to reduce collisions. The other mode works between other nodes except sink node. In this mode, duplicated packets from neighbor nodes can be detected and dropped using some control signals. Our numerical analysis and simulation results show that our mechanism outperforms X-MAC and RI-MAC in terms of energy consumption and transmission delay.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.6
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• pp.1357-1378
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• 2013

Energy constraint of wireless sensor networks makes energy saving and prolonging the network lifetime become the most important goals of routing protocols. In this paper, we propose an Energy Efficient Chain-based Routing Protocol (EECRP) for wireless sensor networks to minimize energy consumption and transmission delay. EECRP organizes sensor nodes into a set of horizontal chains and a vertical chain. Chain heads are elected based on the residual energy of nodes and distance from the header of upper level. In each horizontal chain, sensor nodes transmit their data to their own chain head based on chain routing mechanism. EECRP also adopts a chain-based data transmission mechanism for sending data packets from the chain heads to the base station. The simulation results show that EECRP outperforms LEACH, PEGASIS and ECCP in terms of network lifetime, energy consumption, number of data messages received at the base station, transmission delay and especially energy${\times}$delay metric.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.2946-2962
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• 2017

An improved energy-efficient compressed network coding method is proposed for the data communication in the wireless sensor networks (WSNs). In the method, the compressed sensing and network coding are jointly used to improve the energy efficiency, and the two-hop neighbor information is employed to choose the next hop to further reduce the number of the transmissions. Moreover, a new packet format is designed to facilitate the intermediate node selection. To theoretically verify the efficiency of the proposed method, the expressions for the number of the transmissions and receptions are derived. Simulation results show that, the proposed method has higher energy efficiency compared with the available schemes, and it only requires a few packets to reconstruct measurements with reasonable quality.

• Journal of Communications and Networks
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• v.17 no.1
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• pp.34-39
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• 2015

In opportunistic networks, it is difficult to predict when a node encounters others and how long it keeps in contact with another. Nodes continually attempt to explore neighbor nodes in the vicinity to transmit data. In battery-operated devices, this persistent exploration consumes a great deal of energy. In this paper, we propose an optimal energy-efficient neighbor discovery scheme (OPEED) that guarantees neighbor discovery within a delay bound. Through performance evaluation, we show that the OPEED scheme consumes 33%-83% less energy than other schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.626-648
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• 2011

Energy consumption of wireless access networks is in permanent increase, which necessitates development of more energy-efficient network management approaches. Such management schemes must result with adaptation of network energy consumption in accordance with daily variations in user activity. In this paper, we consider possible energy savings of wireless local area networks (WLANs) through development of a few integer linear programming (ILP) models. Effectiveness of ILP models providing energy-efficient management of network resources have been tested on several WLAN instances of different sizes. To cope with the problem of high computational time characteristic for some ILP models, we further develop several heuristic algorithms that are based on greedy methods and local search. Although heuristics obtains somewhat higher results of energy consumption in comparison with the ones of corresponding ILP models, heuristic algorithms ensures minimization of network energy consumption in an amount of time that is acceptable for practical implementations. This confirms that network management algorithms will play a significant role in practical realization of future energy-efficient network management systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.5
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• pp.326-328
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• 2014

In this paper we propose an efficient algorithm for LSA(Link State Advertisements) flooding. Link state routing protocols have been widely adopted in wired networks. When link state change occurs, a LSA is flooded into the whole network. The overhead of LSA flooding may be a big problem in wireless networks because their link states can be changed frequently. We propose an efficient flooding method that optimizes the flooding processes in wireless networks.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.254-260
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• 2017

Data packets from sensor nodes scattered over measuring fields are generally forwarding to the sink node, which may be connected to the wired networks, in a wireless sensor network. So many data packets are gathered near the sink node, resulting in significant data packet collisions and severe transmission latency. In an event detection application such as object tracking and military, bursty data is generated when an event occurs. So many data packet should be transmitted in a limited time to the sink node. In this paper, we present a delay efficient and bursty traffic friendly MAC protocol called DEBF-MAC protocol for wireless sensor networks. The DEBF-MAC uses a slot-reserved mechanism and sleep period control method to send multiple data packets efficiently in an operational cycle time. Our simulation results show that DEBF-MAC outperforms DW-MAC and SR-MAC in terms of energy consumption and transmission delay.