• Journal of the Institute of Convergence Signal Processing
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• v.3 no.2
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• pp.89-95
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• 2002

Global routing is to assign each net to routing regions to accomplish the required interconnections. The most popular algorithms for global routing inlcude maze routing algorithm, line-probe algorithm, shortest path based algorithm, and Steiner tree based algorithm. In this paper we propose weighted network heuristic(WNH) as a minimal Steiner tree search method in a routing graph and a genetic algorithm based on WNH for the global routing. We compare the genetic algorithm(GA) with simulated annealing(SA) by analyzing the results of each implementation.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.3
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• pp.63-69
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• 2002

Detailed routing is a problem assigning each net to a track after global routing. The most popular algorithms for detailed routing include left-edge algorithm, dogleg algorithm, and greedy channel routing algorithm. In this paper we propose a genetic algorithm searching solution space for the detailed routing problem. We compare the performance of proposed genetic algorithm(GA) for detailed routing with that of greedy channel routing algorithm by analyzing the results of each implementation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1846-1850
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• 2005

This paper presents a constrained-based routing (CBR) algorithm called, Dynamic Possible Path per Link (D-PPL) routing algorithm, for MultiProtocol Label Switching (MPLS) networks. In MPLS on-line routing, future traffics are unknown and network resource is limited. Therefore many routing algorithms such as Minimum Hop Algorithm (MHA), Widest Shortest Path (WSP), Dynamic Link Weight (DLW), Minimum Interference Routing Algorithm (MIRA), Profiled-Based Routing (PBR), Possible Path per Link (PPL) and Residual bandwidth integrated - Possible Path per Link (R-PPL) are proposed in order to improve network throughput and reduce rejection probability. MIRA is the first algorithm that introduces interference level avoidance between source-destination node pairs by integrating topology information or address of source-destination node pairs into the routing calculation. From its results, MIRA improves lower rejection probability performance. Nevertheless, MIRA suffer from its high routing complexity which could be considered as NP-Complete problem. In PBR, complexity of on-line routing is reduced comparing to those of MIRA, because link weights are off-line calculated by statistical profile of history traffics. However, because of dynamic of traffic nature, PBR maybe unsuitable for MPLS on-line routing. Also, both PPL and R-PPL routing algorithm we formerly proposed, are algorithms that achieve reduction of interference level among source-destination node pairs, rejection probability and routing complexity. Again, those previously proposed algorithms do not take into account the dynamic nature of traffic load. In fact, future traffics are unknown, but, amount of previous traffic over link can be measured. Therefore, this is the motivation of our proposed algorithm, the D-PPL. The D-PPL algorithm is improved based on the R-PPL routing algorithm by integrating traffic-per-link parameters. The parameters are periodically updated and are dynamically changed depended on current incoming traffic. The D-PPL tries to reserve residual bandwidth to service future request by avoid routing through those high traffic-per-link parameters. We have developed extensive MATLAB simulator to evaluate performance of the D-PPL. From simulation results, the D-PPL improves performance of MPLS on-line routing in terms of rejection probability and total throughput.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.289-291
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• 2005

Even though a lot of routing algorithms have been proposed, an omnipotent algorithm of routing technique, which has optimal efficiency, does not exist. Therefore, A routing algorithm in a sensor network is an application oriented; the best effective routing algorithm depends on which application it is used to. In this paper, the routing algorithm is proposed for the purpose of monitoring a movement of Assets in office. This Paper proposes a new multi-hop routing algorithm, that is, RSS(Received Signal Strength) value which was used in a localization of sensor network is applied to routing algorithm.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1733-1740
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• 2007

In this paper, we propose a wireless location-based routing algorithm which uses the location information of its neighbor nodes and a destination node. At first, the proposed routing algorithm forwards a packet to the X direction by selecting a closest node to its destination as a next hop in terms of the X coordinate until the packet reaches closely to the packet's destination. Then the packet is forwarded to the Y direction by selecting a closest node to its destination in terms of the Y coordinate. We use a back off mechanism in case that a next hop cannot be found using the proposed routing algorithm, which resolves loops while forwarding. The experimental results show that the proposed routing algorithm performs well like the existing routing algorithms Ad hoc On-demand Distance Vector and Greedy Perimeter Stateless Routing. It is expected to use the proposed routing algorithm in the digital battlefield of military environments and survival games of commercial environments.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.4
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• pp.81-86
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• 2003

Current growth of VLSI design depends critically on the research and development of automatic layout tool. Automatic layout is composed of placement assigning a specific shape to a block and arranging the block on the layout surface and routing finding the interconnection of all the nets. Algorithms performing placement and routing impact on performance and area of VLSI design. Switchbox routing is a problem interconnecting each terminals on all four sides of the region, unlike channel routing. In this paper we propose a genetic algorithm searching solution space for switchbox routing problem. We compare the performance of proposed genetic algorithm(GA) for switchbox routing with that of other switchbox routing algorithm by analyzing the results of each implementation. Consequently experimental results show that out proposed algorithm reduce routing length and number of the via over the other switchbox routing algorithms.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.7
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• pp.535-539
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• 2007

We study an degree of alternativeness and a survivability of alternate routing algorithm in mobile ad-hoc tactical communication networks. The common channel signaling scheme is used and flood search routing algorithm is used for analysis. We also study a connectivity performance for flood search routing, restricted flooding and hybrid routing. From the results we expect low blocking probabilities with alternate routing and the conventional flood search routing shows better connectivity performance which results in high survivability.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.12
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• pp.2329-2336
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• 2010

Hierarchical tree routing is a inefficient routing method of transmitting data in a wireless sensor network. Zigbee routing which is made to improve inefficiency of the hierarchical tree routing only fulfills the tree routing when a destination node don't exists in neighbor nodes of a router. We suggest a TFSR algorithm that is improved more than the zigbee routing. The TFSR algorithm generates a family set included a parent node and child nodes and over of a destination node, and uses this information. According to simulation results, the TFSR algorithm reduce routing costs over 30 percent in comparison with the hierarchical tree routing and the zigbee routing.

• Journal of the Korea Society of Computer and Information
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• v.21 no.4
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• pp.17-24
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• 2016

In this paper, we propose a AH LSU(Advanced Hybrid QoS Routing Link State Update) Algorithm that improves the performance of Hybrid LSU(Hybrid QoS Link State State Update) Algorithm with statistical information of flow holding time in network. AH LSU algorithm has had both advantages of LSU message control in periodic QoS routing LSU algorithm and QoS routing performance in adaptive LSU algorithm. It has the mechanism that calculate LSU message transmission priority using the flow of statistical request bandwidth and available bandwidth and include MLMR(Meaningless LSU Message Removal) mechanism. MLMR mechanism can remove the meaningless LSU message generating repeatedly in short time. We have evaluated the performance of the MLMR mechanism, the proposed algorithm and the existing algorithms on MCI simulation network. We use the performance metric as the QoS routing blocking rate and the mean update rate per link, it thus appears that we have verified the performance of this algorithm.

• ETRI Journal
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• v.44 no.5
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• pp.733-745
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• 2022

In software-defined wireless networking (SDWN), the optimal routing technique is one of the effective solutions to improve its performance. This routing technique is done by many different methods, with the most common using integer linear programming problem (ILP), building optimal routing metrics. These methods often only focus on one routing objective, such as minimizing the packet blocking probability, minimizing end-to-end delay (EED), and maximizing network throughput. It is difficult to consider multiple objectives concurrently in a routing algorithm. In this paper, we investigate the application of machine learning to control routing in the SDWN. An intelligent routing algorithm is then proposed based on the machine learning to improve the network performance. The proposed algorithm can optimize multiple routing objectives. Our idea is to combine supervised learning (SL) and reinforcement learning (RL) methods to discover new routes. The SL is used to predict the performance metrics of the links, including EED quality of transmission (QoT), and packet blocking probability (PBP). The routing is done by the RL method. We use the Q-value in the fundamental equation of the RL to store the PBP, which is used for the aim of route selection. Concurrently, the learning rate coefficient is flexibly changed to determine the constraints of routing during learning. These constraints include QoT and EED. Our performance evaluations based on OMNeT++ have shown that the proposed algorithm has significantly improved the network performance in terms of the QoT, EED, packet delivery ratio, and network throughput compared with other well-known routing algorithms.