• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3544-3564
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• 2022

With the development of the NB-IoT (Narrow band Internet of Things) and smart cities, coupled with the emergence of smart smoke sensors, new requirements and issues have been introduced to study on the deployment of sensors in large spaces. Previous research mainly focuses on the optimization of wireless sensors in some monitoring environments, including three-dimensional terrain or underwater space. There are relatively few studies on the optimization deployment problem of smart smoke sensors, and leaving large spaces with obstacles such as libraries out of consideration. This paper mainly studies the deployment issue of smart smoke sensors in large spaces by considering the fire probability of fire areas and the obstacles in a monitoring area. To cope with the problems of coverage blind areas and coverage redundancy when sensors are deployed randomly in large spaces, we proposed an optimized deployment strategy of smart smoke sensors based on the PSO (Particle Swarm Optimization) algorithm. The deployment problem is transformed into a multi-objective optimization problem with many constraints of fire probability and barriers, while minimizing the deployment cost and maximizing the coverage accuracy. In this regard, we describe the structure model in large space and a coverage model firstly, then a mathematical model containing two objective functions is established. Finally, a deployment strategy based on PSO algorithm is designed, and the performance of the deployment strategy is verified by a number of simulation experiments. The obtained experimental and numerical results demonstrates that our proposed strategy can obtain better performance than uniform deployment strategies in terms of all the objectives concerned, further demonstrates the effectiveness of our strategy. Additionally, the strategy we proposed also provides theoretical guidance and a practical basis for fire emergency management and other departments to better deploy smart smoke sensors in a large space.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3030-3049
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• 2023

With the development and wide application of hybrid network computing modes like cloud computing, edge computing and fog computing, the customer service requests and the collaborative optimization of various computing resources face huge challenges. Considering the characteristics of network environment resources, the optimized deployment of service resources is a feasible solution. So, in this paper, the optimal goals for deploying service resources are customer experience and service cost. The focus is on the system impact of deploying services on load, fault tolerance, service cost, and quality of service (QoS). Therefore, the alternate node filtering algorithm (ANF) and the adjustment factor of cost matrix are proposed in this paper to enhance the system service performance without changing the minimum total service cost, and corresponding theoretical proof has been provided. In addition, for improving the fault tolerance of system, the alternate node preference factor and algorithm (ANP) are presented, which can effectively reduce the probability of data copy loss, based on which an improved cost-efficient replica deployment strategy named ICERD is given. Finally, by simulating the random occurrence of cloud node failures in the experiments and comparing the ICERD strategy with representative strategies, it has been validated that the ICERD strategy proposed in this paper not only effectively reduces customer access latency, meets customers' QoS requests, and improves system service quality, but also maintains the load balancing of the entire system, reduces service cost, enhances system fault tolerance, which further confirm the effectiveness and reliability of the ICERD strategy.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.6
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• pp.877-885
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• 2018

The anti-submarine helicopter is the most effective weapon system in anti-submarine warfare. Recently changes in the introduction of the anti-submarine warfare sonar system are expected to operate multi-static sonar equipment of the anti-submarine helicopter. Therefore, it is required to study the operational concept of multi-static of anti-submarine helicopter. This paper studies on the optimal search of multi-static based on anti-submarine helicopter considering Furthest On Circles(FOC). First, the deployment of the sensors of the anti-submarine helicopter is optimized using genetic algorithms. Then, the optimized model is extended to consider FOC. Finally, the proposed model is verified by comparing pattern-deployment the search method in Korean Navy.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.91-97
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• 1997

The objective of a traffic management system is to promote safe driving, low pollution, short travel time, and optimized traffic flow by naturally distributing the flow of traffic through the use of suitable telecommunications media. Such traffic management systems will be improved by integrating dynamic traffic data and two-way communication media because cars can work as sensors. The purpose of this paper is to help organizations trying to select the correct telecommunications media for minimal-cost investment options without loss of functionality. The wireless communications for an intelligent transportation system (ITS) are introduced in this paper. We describe which kind of telecommunication media are suitable. FM broadcast type media or cellular phone can be recommended to provide real time traffic and roadway conditions in the first stage of ITS, because existing broadcast base station or cellular network facilities can be used. It is expected that cellular radio network or satellites are used for communication. Finally, the strategy and deployment plan of an ITS are described based on selections of telecommunication media in Korea.

• The KIPS Transactions:PartA
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• v.10A no.5
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• pp.519-528
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• 2003

Container terminals need decisions in the course of daily-24 hour and 365 day - operations, and all these decisions are inter-related. The ultimate goal of Decision Support System is to minimize ship loading/unloading time, resources used to handle the workload, and congestion on the roads inside the terminal. It is also to make the best possible use of the storage space available. Therefore, the necessity of decision support tools are emphasized to enhance the operational efficiency of container shipping terminals more, because of limits and complexity of these decisions. So, in thia paper, we draw evaluation items for Decision Support Systems and suggest optimization strategy of evaluation items which have the greatest influence on Decision Support system, that is, yard stacking allocation, RTGC deployment among blocks, and YT allocation to QCs. We also estimate the efficiency of Decision Support System design by simulation using G2 language, comparing ship loading/unloading time.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.2
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• pp.228-231
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• 2015

In power system research fields, one of current key issues is the construction and commercialization of micro grid site which is called green island, carbon zero island, energy independent island, building micro grid, etc. and various affiliated technologies have been being vigorously developed to realize. In addition, various researches about electric vehicles (EVs) are in progress and it is expected to penetrate rapidly with the next a few years. Some new load models should be developed integrating with electric vehicle loads because the EVs' deployment could cause the change of load composition rate on power system planning and operations. EVs are also resources for micro grid as well as distributed generation and demand response so that various supply and demand side resources should be considered for micro grid researches. In this paper, the load composition rate of residential sectors is prospected considering the deployment of EVs and the resource configuration of micro grid is optimized based on net present cost. In the optimization, the load patten of case studies includes EV's charging characteristics and various cases are simulated comparing micro grid environment and normal condition. HOMER is used to compare various cases and economic effects.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.6
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• pp.864-871
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• 2015

Recently, one of the main research on the power distribution system is the microgrid. The microgrid is a combination of power sources and loads, which is controllable and has separable connection. The main objective of microgrid is the deployment of the renewable clean energy and the enhancement of load-side reliability. The modern power sources and loads have DC I/O interfaces, which is the major advantage of DC microgrid compared to the conventional AC grid. The components in the microgrid have diverse features, so there is need of proper coordination control. For achieving economic feature, the active power of renewable energy resources is regarded as major control parameter and the whole operation modes of DC microgrid are defined, and the proper operations of each component are described. From the inherent characteristics of DC, there are two control variables: voltage and active power. Through analysis of operation modes, it is possible to determine exact control objectives and optimized voltage & power control strategy in each mode. Because of consideration of whole operation modes, regardless of the number and capacity of components, this coordination control method can be used without modification. This paper defines operation mode of DC microgrid with several DC sources and suggests economic and efficient coordinated control methods. Simulation with PSCAD proves effectiveness.