• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.39 no.4
• /
• pp.81-89
• /
• 2016

Distributed genetic algorithm (DGA), also known as island model or coarse-grained model, is a kind of parallel genetic algorithm, in which a population is partitioned into several sub-populations and each of them evolves with its own genetic operators to maintain diversity of individuals. It is known that DGA is superior to conventional genetic algorithm with a single population in terms of solution quality and computation time. Several researches have been conducted to evaluate effects of parameters on GAs, but there is no research work yet that deals with structure of DGA. In this study, we tried to evaluate performance of various genetic algorithms (GAs) for the famous symmetric traveling salesman problems. The considered GAs include a conventional serial GA (SGA) with IGX (Improved Greedy Crossover) and several DGAs with various combinations of crossover operators such as OX (Order Crossover), DPX (Distance Preserving Crossover), GX (Greedy Crossover), and IGX. Two distinct immigration policies, conventional noncompetitive policy and newly proposed competitive policy are also considered. To compare performance of GAs clearly, a series of analysis of variance (ANOVA) is conducted for several scenarios. The experimental results and ANOVAs show that DGAs outperform SGA in terms of computation time, while the solution quality is statistically the same. The most effective crossover operators are revealed as IGX and DPX, especially IGX is outstanding to improve solution quality regardless of type of GAs. In the perspective of immigration policy, the proposed competitive policy is slightly superior to the conventional policy when the problem size is large.

• Journal of Korea Multimedia Society
• /
• v.8 no.4
• /
• pp.502-508
• /
• 2005

This paper proposes a dynamic hybrid patching technique that can improve the performance of VOD systems by adopting the advantages of both greedy patching and grace patching to use a VOD server's limited network-I/O bandwidth. The proposed technique uses grace patching to the requests for the videos, arrival intervals of which are smaller than the size of patching window, and uses greedy patching to the rest requests. In addition, proposed patching technique expands the latest particular patching multicast into a regular multicast for a new request. In result, the patching multicast data for the new request can be the data from the beginning to the skew point of the video and the holding time of a dispatched channel can exceedingly decrease. Simulation results confirm that the proposed technique is better than grace patching in terms of defection rate and average service latency.

• KIPS Transactions on Software and Data Engineering
• /
• v.4 no.8
• /
• pp.321-330
• /
• 2015

In journal manuscript submission and review systems, authors can submit their manuscript at any time and editorial members are struggling to find proper reviewers for the submitted manuscripts and assign them to such reviewers. In order to solve this problem, we propose a greedy algorithm and a genetic algorithm to recommend proper reviewers for the submitted manuscripts. The proposed algorithms evaluate reviewers' speciality for the submitted manuscripts by using the submitted manuscripts' keywords and the reviewers expertises. In addition to that, they take the fairness among the reviewers' speciality and the review frequency for consideration. To verify the proposed algorithms, we apply them to the JIPS manuscript submission and review system that the Korea Information Processing Society has operated, and present the results in this paper. By performing the performance evaluation of the proposed algorithms, we finally show that the genetic algorithm outperforms the greedy algorithm in terms of the recommended reviewers' fitness.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.1
• /
• pp.703-712
• /
• 2015

This paper proposes the UIGRP, which can tackle the problem of the network disconnection and packet transmission delay caused by turning vehicles frequently in an urban intersection. The UIGRP was designed as follows. First, it calculates the direction of vehicles using the moving direction of vehicles and the location of a destination. Second, it makes the RSU measure the density of an urban intersection. Third, the TGF Algorithm in the UIGRP decides the data transmission paths by setting as an intermediate node, not only the vehicle that is moving in the direction where a destination node is located, but also the node that has the highest density. The TGF algorithm using a moving direction and density minimizes or removes the occurrence of local maximum problems that the existing Greedy Forwarding algorithm has. Therefore, the simulation result shows that UIGRP decreases the occurrence of local maximum problems by 3 and 1 times, and the packet transmission time by 6.12 and 2.04(ms), and increases the success rate of packet transmission by 15 and 3%, compared to the existing GPSR and GPUR.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.6
• /
• pp.1058-1069
• /
• 2015

In wireless sensor networks, geographic routing is known as an efficient method to transmit the data packet using the location information. Geographic routing relies on two techniques: greedy forwarding and face routing. Face routing helps to recover from greedy routing fail and is based on the planar graph in which does not cross each edge. However, the planarization causes frequently short transmission of data packet because it removes other edges except the shortest one. In other words, since the planarization removes the long edges, face routing could not exploit the efficient removed edges of communication graph. This problem brings about the excessive energy consumption of nodes. In this paper, we propose an energy efficient face routing protocol in wireless sensor networks. This proposed protocol searches the removed edges and transmits them via the edges. Simulation shows that the proposed protocol is more efficient in terms of energy consumption than the previous face routing.

• Journal of Communications and Networks
• /
• v.11 no.6
• /
• pp.589-598
• /
• 2009

In wireless sensor networks, a node that reports information gathered from adjacent assets should relay packets appropriately so that its location context is kept private, and thereby helping ensure the security of the assets that are being monitored. Unfortunately, existing routing methods that counter the local eavesdropping-based tracing deal with a single asset, and most of them suffer from the packet-delivery latency as they prefer to take a separate path of many hops for each packet being sent. In this paper, we propose a routing method, greedy perimeter stateless routing-based source-location privacy with crew size w (GSLP-w), that enhances location privacy of the packet-originating node (i.e., active source) in the presence of multiple assets. GSLP-w is a hybrid method, in which the next-hop node is chosen in one of four modes, namely greedy, random, perimeter, and retreat modes. Random forwarding brings the path diversity, while greedy forwarding refrains from taking an excessively long path and leads to convergence to the destination. Perimeter routing makes detours that avoid the nodes near assets so that they cannot be located by an adversary tracing up the route path. We study the performance of GSLP-w with respect to crew size w (the number of packets being sent per path) and the number of sources. GSLP-w is compared with phantom routing-single path (PR-SP), which is a notable routing method for source-location privacy and our simulation results show that improvements from the point of the ratio of safety period and delivery latency become significant as the number of source nodes increases.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.21 no.5
• /
• pp.921-928
• /
• 2017

Unlike wired networks, broadcasting in wireless networks can transmit data to several nodes at a time in a single transmission. The omnidirectional broadcasting of node in wireless networks simultaneously reaches all neighboring nodes. In this paper, we propose a greedy algorithm to solve the minimum power broadcasting problem that minimizes the total transmission power when broadcasting in wireless networks. The proposed algorithm uses a neighborhood list which is a set of nodes that can transmit messages within the maximum transmission range of each node, and among the transmitting nodes that have received the data, the node having the largest number of the neighboring nodes firstly transmits the data to neighboring node. The performance of the proposed algorithm was evaluated by computer simulation, and was compared with existing algorithms in terms of total transmission power and broadcasting frequency for broadcasting to all nodes. Experiment results show that the proposed algorithm outperforms the conventional algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.3B
• /
• pp.453-461
• /
• 2010

A critical issue in wireless sensor networks is an energy-efficiency since the sensor batteries have limited energy power and, in most cases, are not rechargeable. The most practical manner relate to this issue is to use a node wake-up scheduling protocol that some sensor nodes stay active to provide sensing service, while the others are inactive for conserving their energy. Especially, CTC (Connected Target Coverage) problem has been considered as a representative energy-efficiency problem considering connectivity as well as target coverage. In this paper, we propose a new energy consumption model considering multiple-targets and create a new problem, CMTC (Connected Multiple-Target Coverage) problem, of which objective is to maximize the network lifetime based on the energy consumption model. Also, we present SPT (Shortest Path based on Targets)-Greedy algorithm to solve the problem. Our simulation results show that SPT-Greedy algorithm performs much better than previous algorithm in terms of the network lifetime.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.40 no.4
• /
• pp.137-146
• /
• 2017

For the competitive business environment under purchase dependence, this paper proposes a new approximate calculation of order fill rate which is a probability of satisfying a customer order immediately using the existing inventory. Purchase dependence is different to demand dependence. Purchase dependence treats the purchase behavior of customers, while demand dependence considers demand correlation between items, between regions, or over time. Purchase dependence can be observed in such areas as marketing, manufacturing systems, and distribution systems. Traditional computational methods have a difficulty of the curse of dimensionality for the large cases, when deriving the stationary joint distribution which is utilized to calculate the order fill rate. In order to escape the curse of dimensionality and protect the solution from diverging for the large cases, we develop a greedy iterative search algorithm based on the Gauss-Seidel method. We show that the greedy iterative search algorithm is a dependable algorithm to derive the stationary joint distribution of on-hand inventories in the retailer system by conducting a comparison analysis of a greedy iterative search algorithm with the simulation. In addition, we present some managerial insights such as : (1) The upper bound of order fill rate can be calculated by the one-item pure system, while the lower bound can be provided by the pure system that consists of all items; (2) As the degree of purchase dependence declines while other conditions remain same, it is observed that the difference between the lower and upper bounds reduces, the order fill rate increases, and the order fill rate gets closer to the upper bound.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.05a
• /
• pp.641-644
• /
• 2016

Unlike wired networks, broadcasting in wireless networks can transmit data at once to several nodes with a single transmission. For omnidirectional broadcast to a node in wireless networks, all adjacent nodes receive the data at the same time. In this paper, we propose a greedy algorithm to solve the minimum power broadcasting problem of minimizing the total transmit power on broadcasting in wireless networks. We apply two matrices to the proposed algorithm: one is a distance matrix that represents the distance between each node, the other is an adjacency matrix having the number of adjacency nodes. Among the nodes that receive the data, a node that has the greatest number of the adjacent node transmits data to neighbor preferential. We compare the performance of the proposed algorithm with random method through computer simulation in terms of transmitting power of nodes. Experiment results show that the proposed algorithm outperforms better than the random method.