• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1550-1553
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• 2020

In this paper, we maximize the lifetime of a multi-hop path through a cooperative wireless energy sharing scheme between constituent nodes in a wireless multi-hop communication. Considering a bidirectional multi-hop communication environment, we present an optimization problem to maximize path lifetime by adjusting the amount of energy each node needs to share with its neighboring nodes. On the basis of solidarity property, i.e., the lifetime of the multi-hop path is maximized when the lifetimes of all nodes are the same, we convert the considered optimization problem into a linear programming problem and solve it easily. Simulation result shows that the proposed two-way wireless energy sharing method maximizes the path lifetime of multi-hop communications and approximately doubles the path lifetime compared with the one-way energy sharing method.

• IEMEK Journal of Embedded Systems and Applications
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• v.8 no.6
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• pp.339-345
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• 2013

This paper addresses the system lifetime maximization algorithm in multi-hop sensor network system. A multi-hop sensor network consists of many battery-driven sensor nodes that collaborate with each other to gather, process, and communicate information using wireless communications. As sensor-driven applications become increasingly integrated into our lives, we propose a energy-aware scheme where each sensor node transmits informative data with adaptive data rate to minimize system energy consumption. We show the optimal data rate to maximize the system lifetime in terms of remaining system energy. Furthermore, the proposed algorithm experimentally shows longer system lifetime in comparison with greedy algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10A
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• pp.1023-1033
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• 2007

This study considers a joint congestion control, routing and power control for energy-constrained wireless networks. A mathematical model is introduced which includes maximization of network utility, maximization of network lifetime, and trade-off between network utility and network lifetime. The framework would maximize the overall throughput of the network where the overall throughput depends on the data flow rates which in turn is dependent on the link capacities. The link capacity on the other hand is a function of transmit power levels and link Signal-to-Interference-plus-Noise-Ratio (SINR) which makes the power allocation problem inherently difficult to solve. Using dual decomposition techniques, subgradient method, and logarithmic transformations, a joint algorithm for rate and power allocation problems was formulated. Numerical examples for each optimization problem were also provided.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.12
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• pp.2826-2834
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• 2013

In mobile ad hoc networks (MANET), power-saving technology of mobile nodes is divided into transmit power control (TPC), power-saving mode (PSM), and routing. TPC and PSM are operated in physical layer but the routing is managed in network layer, so the design of a joint algorithm is needed to provide better performance. Therefore, in this paper, we propose a joint power-saving and routing algorithm for maximizing the network lifetime while satisfying the end-to-end data rate in ad hoc networks. The proposed algorithm first applies the TPC or PSM to reduce the power consumption of mobile nodes and then performs the routing by considering the decided node lifetime in order to maximize the path lifetime. Simulation results show that the proposed algorithm maximize the lifetime while satisfying the required rate according to the number of mobile nodes and the level of interference.

• Journal of Korean Society for Quality Management
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• v.36 no.1
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• pp.31-39
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• 2008

This paper proposes a method of estimating the lifetime distribution at use condition for constant stress accelerated life tests when an infant-mortality failure mode as well as wear-out one exists. General limited failure population model is introduced to describe these failure modes. It is assumed that the log lifetime of each failure mode follows a location-scale distribution and a linear relation exists between the location parameter and the stress. An estimation procedure using the expectation and maximization algorithm is proposed. Specific formulas for Weibull distribution are obtained. An illustrative example and the simulation results are given.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.1
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• pp.52-60
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• 2007

Estimating parameters of the lifetime distribution is investigated when field failure data are not completelyreported. To take into account the reality and the accuracy of the estimates in such a case, the failure reportingprobability is incorporated in estimating parameters, Firstly, method of maximum likelihood estimate (MLE) isused to estimate parameters of the lifetime distribution when failure reporting probability is known, Secondly,Expectation and Maximization (EM) algorithm is used to estimate the failure reporting probability and parame-ters of the lifetime distribution simultaneously when failure reporting probability is unknown. For both cases,procedures of estimation are illustrated for single Weibull distribution and mixed Weibull distribution. Simula-tion results show that MLE obtained by the proposed method is more accurate than the conventional MLE.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.5149-5167
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• 2017

Reducing energy consumption in a wireless video sensor network (WVSN) is a crucial problem because of the high video data volume and severe energy constraints of battery-powered WVSN nodes. In this paper, we present an adaptive dynamic resizing approach for a SRAM communication buffer in a WVSN node in order to reduce the energy consumption and thereby, to maximize the lifetime of the WVSN nodes. To reduce the power consumption of the communication part, which is typically the most energy-consuming component in the WVSN nodes, the radio needs to remain turned off during the data buffer-filling period as well as idle period. As the radio ON/OFF transition incurs extra energy consumption, we need to reduce the ON/OFF transition frequency, which requires a large-sized buffer. However, a large-sized SRAM buffer results in more energy consumption because SRAM power consumption is proportional to the memory size. We can dynamically adjust any active buffer memory size by utilizing a power-gating technique to reflect the optimal control on the buffer size. This paper aims at finding the optimal buffer size, based on the trade-off between the respective energy consumption ratios of the communication buffer and the radio part, respectively. We derive a formula showing the relationship between control variables, including active buffer size and total energy consumption, to mathematically determine the optimal buffer size for any given conditions to minimize total energy consumption. Simulation results show that the overall energy reduction, using our approach, is up to 40.48% (26.96% on average) compared to the conventional wireless communication scheme. In addition, the lifetime of the WVSN node has been extended by 22.17% on average, compared to the existing approaches.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.678-685
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• 2005

Estimating parameters of the lifetime distribution is investigated when field failure data are not completely reported. To take into account the reality and the accuracy of the estimates in such a case, the failure reporting probability is incorporated in estimating parameters. Firstly, method of maximum likelihood estimate(MLE) is used to estimate parameters of the lifetime distribution when failure reporting probability is known. Secondly, Expectation and Maximization(EM) algorithm is used to estimate the failure reporting probability and parameters of the lifetime distribution simultaneously when failure reporting probability is unknown. For both case, procedures of estimation are illustrated for single Weibull distribution and mixed Weibull distribution. Simulation results show that MLE obtained by the proposed method is more accurate than the conventional MLE.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.3
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• pp.31-39
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• 2012

In this paper, we propose an energy-aware source routing protocol for maximizing a network lifetime in mobile ad hoc network environments. The proposed routing protocol is based on the source routing and chooses a path that maximize the path lifetime, by considering both transmit/receive power consumption and residual battery power in the mobile nodes from the perspective of source-destination end-to-end. This paper proposes a new routing cost and designs a new routing protocol for minimizing the control packet overhead occurred during the route discovery. Simulation results show that the proposed scheme has similar performances to the conventional routing schemes in terms of the number of transmission hops, transmission rate and total energy consumption, but achieves the performance improvement of 20 percent with respect to the lifetime.

• Journal of the Korea Society of Computer and Information
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• v.15 no.6
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• pp.65-72
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• 2010

In ad-hoc network, the technique to efficiently consume the limited amounts of energy is an important issue since the wireless terminal node is operated on batteries as their energy resource. In order to extend the system lifetime, through a balanced energy consumption, we must delay the situation in which a particular terminal node's energy is depleted and results in system disconnection. Also, the link, which has low reliability due to the mobility of the node, should be avoided considering the key element when setting up the route. The proposed CMLR method in this paper enables to increase the efficiency of energy consumption with a new cost function considering the residue energy of node, error rate of link, and transmission energy consumption. This method is extending the network lifetime and increasing the energy efficiency by compromising the value between the minimization of the transmission energy consumption and maximization of the node's lifetime. Through the simulations the proposed CMLR algorithm was verified by showing better performance over the conventional methods in terms of network lifetime and path efficiency.