• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1284-1294
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• 2010

The ZigBee is one of the most important technologies for composing USN. It is one of the IEEE 802.15.4 standards to support personal area networks. It uses a hierarchical routing or an on-demand route discovery strategy as an address allocation method. A hierarchical routing doesn't use a routing table but only uses a child node or a parent node as an intermediate node for data delivery. Therefore, the ZigBee network's topology greatly affects the overall network performance. In this paper, we propose a more trustworthy algorithm than only using the depth and widely variable LQI during network formation, and moreover we propose an algorithm to measure network's trustworthiness. We simulate our algorithm using the NS-2 and implement our network using the MG2400 ZigBee module for verifying performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2140-2156
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• 2023

The Wireless Sensor Network (WSN), is constructed out of teeny-tiny sensor nodes that are very low-cost, have a low impact on the environment in terms of the amount of power they consume, and are able to successfully transmit data to the base station. The primary challenges that are presented by WSN are those that are posed by the distance between nodes, the amount of energy that is consumed, and the delay in time. The sensor node's source of power supply is a battery, and this particular battery is not capable of being recharged. In this scenario, the amount of energy that is consumed rises in direct proportion to the distance that separates the nodes. Here, we present a Hybrid Firefly Glow-Worm Swarm Optimization (HF-GSO) guided routing strategy for preserving WSNs' low power footprint. An efficient fitness function based on firefly optimization is used to select the Cluster Head (CH) in this procedure. It aids in minimising power consumption and the occurrence of dead sensor nodes. After a cluster head (CH) has been chosen, the Glow-Worm Swarm Optimization (GSO) algorithm is used to figure out the best path for sending data to the sink node. Power consumption, throughput, packet delivery ratio, and network lifetime are just some of the metrics measured and compared between the proposed method and methods that are conceptually similar to those already in use. Simulation results showed that the proposed method significantly reduced energy consumption compared to the state-of-the-art methods, while simultaneously increasing the number of functioning sensor nodes by 2.4%. Proposed method produces superior outcomes compared to alternative optimization-based methods.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.3
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• pp.48-54
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• 2010

S plastic injection molding factory located at Namdong Industrial Complex in Incheon produces plastic parts for semiconductor, vacuum cleaners, office furniture, etc. It produces the parts to customers' order and delivers them directly to customers at due dates using the trucks of freight company. In recent years, it has been suffered from the excessive production cost, high lost sales rate, rigid response to customers' order, and high delivery cost, which affect negatively on its profit. This paper introduces a case study on the profit increase through a newly proposed production and distribution method which applies a make-to-stock and multi-visit delivery strategy at S plastic injection molding factory. The proposed method is evaluated by comparing with the current method with respect to sales profit using the historical data of customer demand. It is confirmed through the computational experiments that the proposed production and distribution method yields almost double increase in profit resulted from the increased production, reduced lost sales, reduced production cost, and reduced delivery cost.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.1
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• pp.20-28
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• 1999

In this paper, we propose a new datagram delivery strategy at the home agent to improve the end-to-end performance by reducing retransmission overheads during handover. Changed routing might be able to cause packet disordering and this in turn could cause unnecessary retransmission at the fixed host and finally results in performance degradation. In our proposal, the home agent begins to buffer received datagrams instead of transmitting them after receiving a registration request message from the foreign agent and then transmits them again after for a certain time. Simulation results show that our proposal may successfully solve this problem at little cost.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4678-4702
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• 2018

Traffic Matrix estimation has always caught attention from researchers for better network management and future planning. With the advent of high traffic loads due to Cloud Computing platforms and Software Defined Networking based tunable routing and traffic management algorithms on the Internet, it is more necessary as ever to be able to predict current and future traffic volumes on the network. For large networks such origin-destination traffic prediction problem takes the form of a large under- constrained and under-determined system of equations with a dynamic measurement matrix. Previously, the researchers had relied on the assumption that the measurement (routing) matrix is stationary due to which the schemes are not suitable for modern software defined networks. In this work, we present our Compressed Sensing with Dynamic Model Estimation (CS-DME) architecture suitable for modern software defined networks. Our main contributions are: (1) we formulate an approach in which measurement matrix in the compressed sensing scheme can be accurately and dynamically estimated through a reformulation of the problem based on traffic demands. (2) We show that the problem formulation using a dynamic measurement matrix based on instantaneous traffic demands may be used instead of a stationary binary routing matrix which is more suitable to modern Software Defined Networks that are constantly evolving in terms of routing by inspection of its Eigen Spectrum using two real world datasets. (3) We also show that linking this compressed measurement matrix dynamically with the measured parameters can lead to acceptable estimation of Origin Destination (OD) Traffic flows with marginally poor results with other state-of-art schemes relying on fixed measurement matrices. (4) Furthermore, using this compressed reformulated problem, a new strategy for selection of vantage points for most efficient traffic matrix estimation is also presented through a secondary compression technique based on subset of link measurements. Experimental evaluation of proposed technique using real world datasets Abilene and GEANT shows that the technique is practical to be used in modern software defined networks. Further, the performance of the scheme is compared with recent state of the art techniques proposed in research literature.

• Journal of IKEEE
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• v.23 no.1
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• pp.280-288
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• 2019

In the CR-enabled MANET, routing paths can be easily destroyed due to node mobility and channel unavailability (due to the emergence of the PU of a channel), resulting in significant overhead to maintain/recover the routing path. In this paper, network caching is actively used for route maintenance, taking into account the properties of the CR. In the proposed scheme, even if a node detects that a path becomes unavailable, it does not generate control messages to establish an alternative path. Instead, the node stores the packets in its local cache and 1) waits for a certain amount of time for the PU to disappear; 2) waits for a little longer while overhearing messages from other flow; 3) after that, the node applies local route recovery process or delay tolerant forwarding strategy. According to the simulation study using the OPNET simulator, it is shown that the proposed scheme successfully reduces the amount of control messages for path recovery and the service latency for the time-sensitive traffic by 13.8% and 45.4%, respectively, compared to the existing scheme. Nevertheless, the delivery ratio of the time-insensitive traffic is improved 14.5% in the proposed scheme.

• Journal of IKEEE
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• v.13 no.1
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• pp.71-76
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• 2009

As one of the most important requirements for wireless sensor networks, prolonging network lifetime can be realized by minimizing energy consumption in cluster heads as well as sensor nodes. While most of the previous researches have focused on the energy of sensor nodes, we devote our attention to cluster heads because they are most dominant source of power consumption in the cluster-based sensor networks. Therefore, we seek to minimize energy consumption by minimizing the maximum(MINMAX) energy dissipation at each cluster heads. This work requires energy-efficient clustering of the sensor nodes while satisfying given energy constraints. In this paper, we present a constraint satisfaction modeling of cluster-based routing in a heterogeneous sensor networks because mixed integer programming cannot provide solutions to this MINMAX problem. Computational experiments show that substantial energy savings can be obtained with the MINMAX algorithm in comparison with a minimum total energy(MTE) strategy.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.1033-1035
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• 2005

일반적으로 기존의 Ad-hoc 무선 네트워크 환경에서의 라우팅 정책은 가장 빠르게 데이터를 전송할 수 있는 경로를 찾는 것이 목적이었다. 그러나 한정된 전력을 가진 노드로 구성한 네트워크에서 각 노드의 잔여전력량을 무시하고 라우팅 경로를 설정하면 수명을 다한 특정 노드로 인해 네트워크의 성능이 저하되는 문제점이 발생한다. 따라서 본 논문에서는 각 노드의 생존시간을 최대한 보장할 수 있도록 라우팅 경로를 선택하여 네트워크의 성능 저하를 최소화하는 라우팅 정책을 제안한다. 이 정책은 기존의 테이블 기반 라우팅 정책에 두 가지 metric을 더하여 잔여 전력이 많은 노드를 포함하는 경로를 설정할 수 있게 해 준다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.4
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• pp.138-145
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• 2013

A sweep-based heuristic using common area is developed for multi-vehicle VRPs under time various and unsymmetric forward and backward vehicle moving speed. One depot and 2 delivery vehicle are assumed in this research to make the problem solving strategy simple. A common area is held to make adjustment of possible unbalance of between two vehicle delivery completion times. The 4 time zone heuristic is used to solve for efficient delivery route for each vehicle. The current size of common area needs to be studied for better results, but the suggested problem solving procedures can be expanded for any number of vehicles.

• Korean Journal of Computational Design and Engineering
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• v.18 no.2
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• pp.129-137
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• 2013

This paper proposed the scheduling method for tire mixing processes using the genetic algorithm. The characteristics of tire mixing process have the manufacturing routing, operation machine and operation time by compound types. Therefore, the production scheduling has to consider characteristics of the tire mixing process. For the reflection of the characteristics, we reviewed tire mixing processes. Also, this paper introduces the genetic algorithm using the crossover and elitist preserving selection strategy. Fitness is measured by the makespan. The proposed genetic algorithm has been implemented and tested with two examples. Experimental results showed that the proposed algorithm is superior to conventional heuristic algorithm.