• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.2A
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• pp.139-148
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• 2011

This paper presents the minimum-cost network selection scheme which determines the transmission instance in the multi-band maritime communication system, so that the shipment-related real-time information can be transmitted within the maximum allowed period. The transmission instances and the corresponding network selection process are modeled by a Markov Decision Process (MDP), for the channel model in the 2-state Markov chain, which can be solved by stochastic dynamic programming. It derives the minimum-cost network selection rule, which can reduce the network cost significantly as compared with the straight-forward scheme with a periodic transmission.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.10
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• pp.807-821
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• 1991

A mulitpath MIN(Multistage Interconnection Network), CSMP(Chained Shuffle Multi-Path) network, is proposed, having fault-tolerance and dynamic reroutability. The number of stages and the number of links between adjacent stagges are the same as in single path MINs, so the overall hardware complexity is considerably reduced in comparison with other multipath MINs. The CSMP networks feature links between switches belonging to the same state, forming loops of switches. The network can tolerate multiple faults, up to (N/4)*(log$_2$N-1), having occured in any stages including the first and the last ones(N:NO. of input). To analyze reliability, terminal reliability (TR) and mean time to failure( MTTE) age given for the networks, and the TR figures are compared to those of other static and dynamic rerouting multipath MINs. Also the MTTE figures are compared. The performance of the proposed network with respect to its bandwidth (BW) and probability of acceptance(PA) is analyzed and is compared to that of other more complex multipath MINs. The cost efficiency analysis of reliability and performance shows that the network is more cost-effective than other previously proposed fault-tolerant multipath MINs.

• Smart Structures and Systems
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• v.11 no.3
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• pp.315-329
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• 2013

The construction of an experimental nonlinear structural model with little cost and unlimited repeatability for vibration control study represents a challenging task, especially for material nonlinearity. This paper reports the design, analysis and vibration control of a nonlinear structural experiment platform with adjustable hinges. In our approach, magnetorheological rotary brakes are substituted for the joints of a frame structure to simulate the nonlinear material behaviors of plastic hinges. For vibration control, a separate magnetorheological damper was employed to provide semi-active damping force to the nonlinear structure. A dynamic neural network was designed as a state observer to enable the feedback based semi-active vibration control. Based on the dynamic neural network observer, an adaptive fuzzy sliding mode based output control was developed for the magnetorheological damper to suppress the vibrations of the structure. The performance of the intelligent control algorithm was studied by subjecting the structure to shake table experiments. Experimental results show that the magnetorheological rotary brake can simulate the nonlinearity of the structural model with good repeatability. Moreover, different nonlinear behaviors can be achieved by controlling the input voltage of magnetorheological rotary damper. Different levels of nonlinearity in the vibration response of the structure can be achieved with the above adaptive fuzzy sliding mode control algorithm using a dynamic neural network observer.

• Journal of Distribution Science
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• v.18 no.3
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• pp.25-36
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• 2020

Purpose: Based on previous researches on social factors of digital item purchase in digital contents distribution platforms such as SNS, we aim to develop the integrated model that accounts for the dynamic and interactive relationship between social structure indicators and digital item purchase. Research design, data and methodology: A PVAR model was used to capture endogenous and dynamic relationships between digital item purchase and network indicators. Results: We find that there exist considerable endogenous and dynamic relationships between digital item purchase and network structure variables. Not only lagged in-degree and out-degree but also in-closeness and out-closeness centrality have significant and positive impacts on digital item purchase. Lagged clustering has a significant and negative effect on digital item purchase. Lagged purchase has a significant and positive impact just on the present in-closeness and out-closeness centrality; but there is no significant effect of lagged purchase on the other two degree variables and clustering coefficient. We also find that both closeness centralities have much higher carryover effect on digital item purchase and that the elasticity of both closeness centralities on the purchase of digital items is even higher than that of other network structure variables. Conclusions: In-closeness and out-closeness are the most influential factors among social structure variables of this study on digital item purchase.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.10
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• pp.130-137
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• 1990

The multipath multistage interconnection network is proposed which has the capability of dynamic rerouting. Construction of the network gets simpler, and the number of stages is reduced to $LOG_{2}$(N), so hardware complexity is reduced. This proposed algorithm makes it possible that destination adresses are used as routing tags, and it is easy to set up the path. Because this proposed network has a dynamic rerouting, backtracking is not necessary to set up another path when conflicts of switch faults are occurred. To estimate a performance, analytic methods are used and it is proved that probability of acceptance is improved in this Multipath MIN.

• Journal of Communications and Networks
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• v.9 no.4
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• pp.499-510
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• 2007

Shortest path tree(SPT) construction is essential in high performance routing in an interior network using link state protocols. When some links have new state values, SPTs may be rebuilt, but the total rebuilding of the SPT in a static way for a large computer network is not only computationally expensive, unnecessary modifications can cause routing table instability. This paper presents a new update algorithm, dynamic shortest path tree(DSPT) that is computationally economical and that maintains the unmodified nodes mostly from an old SPT to a new SPT. The proposed algorithm reduces redundancy using a dynamic update approach where an edge becomes the significant edge when it is extracted from a built edge list Q. The average number of significant edges are identified through probability analysis based on an arbitrary tree structure. An update derived from significant edges is more efficient because the DSPT algorithm neglect most other redundant edges that do not participate in the construction of a new SPT. Our complexity analysis and experimental results show that DSPT is faster than other known methods. It can also be extended to solve the SPT updating problem in a graph with negative weight edges.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.991-992
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• 2006

Multiprocessor system is efficient and high performance architecture to overcome a limitation of single core SoC. In this paper, we propose a multiprocessor SoC (MPSoC) architecture which provides the low complexity and the high performance. The dynamic routing scheme has a serious problem in which the complexity of routing increases exponentially. We solve this problem by making a cluster with several PEs (Processing Element). In inter-cluster network, we use deterministic routing scheme and in intra-cluster network, we use dynamic routing scheme. In order to control the hierarchical network, we propose efficient router architecture by using smart crossbar switch. We modeled 2-D mesh topology and used simulator based on C/C++. The results of this routing scheme show that our approach has less complexity and improved throughput as compared with the pure deterministic routing architecture and the pure dynamic routing architecture.

• The KIPS Transactions:PartC
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• v.10C no.4
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• pp.441-446
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• 2003

Earlier efforts on optical access concentrated on the design of PONs for the collection and distribution portion of the access network. The PON architecture is very simple but it requires a MAC protocol for control of upstream traffic. The MAC protocol must support QoS (Quality of Service) administration function by various traffic class, efficient dynamic bandwidth assignment function, CDV (Ceil Delay Variation) minimization function etc. This paper proposes a dynamic bandwidth assignment algorithm of the MAC protocol for a broadband access network using an Ethernet Passive Optical Network supporting various traffic class. We compare our proposed with MDRR algorithm using simulation, and confirmed that our proposed Request-Counter algorithm produces shorter average cell delay.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.119-125
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• 2006

Distributed Systems can be defined as set of computing resources connected by computer network. One of the most significant techniques in optimization problem domains is parallel genetic algorithms, which are based on distributed systems. Since the status of dynamic network environments such as Internet and mobile computing. can be changed continually, it must not be efficient on the dynamic environments to solve an optimization problem using previous parallel genetic algorithms themselves. In this paper, we propose the effective technique, in which the parallel genetic algorithm can be used efficiently on the dynamic network environments.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.2
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• pp.132-140
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• 2002

A momentum backpropagation neural network is prepared to carry out real-time dynamics simulations of a passenger car. A full-car model of fifteen degrees of freedom was constructed for vehicle dynamics analysis. Human body dynamics analysis was performed for a male driver(50 percentile Korean adult) restrained by a three point seatbelt system. The trained data using the neural network were obtained using a dynamic solver, ADAMS . The neural network were formed based on the dynamics of the simulator. The optimized hidden layer was obtained by selecting the optimal number of hidden layers. The driving scenario including bump passing and lane changing has been used for the estimation of the proposed neural network. A comparison between the trained data and neural network outputs is found to be satisfactory to show the applicability of the suggested approach.