• Journal of Intelligence and Information Systems
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• v.12 no.4
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• pp.39-51
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• 2006

This study addresses how to plan purchasing and leasing of containers to satisfy the demand on containers. The problem can be further decomposed into the long-term planning and the short-term scheduling. The long-term plan specifies the composition of owned containers, long-term leasing containers, and short-term containers. The short-term plan considers the seasonality of demand and determines the time of leasing and the amount of the short-term and the long-term leasing containers. The length of the planning horizon is 10-20 years for the long-term planning, while it is one year for the short-term planning. The time unit is one year for the long-term planning, while it is one month for the short-term planning. This study discusses how to estimate the demand of containers and proposes deterministic models for scheduling purchasing and leasing of containers.

• Environmental and Resource Economics Review
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• v.11 no.3
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• pp.447-463
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• 2002

The heat demand prediction is an essential issue in management of district heating system. Without an accurate prediction through the lead-time period, it might be impossible to make a rational decision on many issues such as heat production scheduling and heat exchange among the plants which are very critical for the district heating company. The heat demand varies with the temperature as well as the time nonlinearly. And the parametric specification of the heat demand model would cause a misspecification bias in prediction. A nonparametric model for the short-term heat demand prediction has been developed as an alternative to avoiding the misspecification error and tested with the actual data. The prediction errors are reasonably small enough to use the model to predict a few hour ahead heat demand.

• Journal of Energy Engineering
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• v.7 no.1
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• pp.89-95
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• 1998

Maintenance scheduling of generators plays an important role in evaluating supply reliability of power systems. Since generators must be maintained and inspected, the generation planner must schedule planned outages during the year. Several factors entering into this scheduling analysis include: seasonal load-demand profile, amount of maintenance, size of the units, elapsed time from last maintenance, and availability of maintenance crew. This paper proposes a new maintenance scheduling algorithm for the alternatives of long-term generation expansion planning by using LOLP levelization method which is known as an effective method for the generator's maintenance scheduling. To get the best supply reliability of power systems, we change the maintenance period to levelize the reliability over all period. The proposed algorithm is applied to a real size power system and the better reliability results are obtained.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.1
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• pp.88-95
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• 2004

The previous disk scheduling schemes for best-effort applications do not guarantee the real-time requirement of multimedia objects and the real-time disk scheduling schemes do not satisfy throughput of multimedia server. So, this paper propose a two-step disk scheduling scheme to satisfy the requirement of best-effort as well as soft real-time applications. This scheme is based on the round robin algorithm that imposes different weights on the best-effort task and the real-time one. The experiment results on the Linux kernel have shown that both best-effort tasks and real-time tasks could get fair service.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4311-4330
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• 2015

Cloud computing has become a new paradigm by enabling on-demand provisioning of applications, platforms or computing resources for clients. Workflow scheduling has always been treated as one of the most challenging problems in clouds. Commercial clouds have been widely used in scientific research, such as biology, astronomy and weather forecasting. Certainly, it is very important for a cloud service provider to pursue the profits for the commercial essence of clouds. This is also significantly important for the case of providing services to workflow tasks. In this paper, we address the issues of workflow scheduling in commercial clouds. This work takes the communication into account, which has always been ignored. And then, a topology-based workflow-scheduling algorithm named Resource Auction Algorithm (REAL) is proposed in the objective of getting more profits. The algorithm gives a good performance on searching for the optimum schedule for a sample workflow. Also, we find that there exists a certain resource amount, which gets the most profits to help us get more enthusiasm for further developing the research. Experimental results demonstrate that the analysis of the strategies for most profits is reasonable, and REAL gives a good performance on efficiently getting an optimized scheme with low computing complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5243-5263
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• 2017

Data center networks provide critical bandwidth for the continuous growth of cloud computing, multimedia storage, data analysis and other businesses. The problem of low link bandwidth utilization in data center network is gradually addressed in more hot fields. However, the current scheduling strategies applied in data center network do not adapt to the real-time dynamic change of the traffic in the network. Thus, they fail to distribute resources due to the lack of intelligent management. In this paper, we present an improved adaptive traffic scheduling strategy utilizing the simulated annealing genetic algorithm (SAGA). Inspired by the idea of software defined network, when a flow arrives, our strategy changes the bandwidth demand dynamically to filter out the flow. Then, SAGA distributes the path for the flow by considering the scheduling of the different pods as well as the same pod. It is implemented through software defined network technology. Simulation results show that the bisection bandwidth of our strategy is higher than state-of-the-art mechanisms.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.8
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• pp.312-321
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• 2018

The Korean DR market proposes suppression of peak demand under reliability crisis caused a natural disaster or unexpected power plant accidents as well as saving power plant construction costs and expanding amount of reserve as utility's perspective. End-user is notified a DR event signal DR execution before one hour, and executes DR based on requested amount of load reduction. This paper proposes a DR energy management algorithm that can be scheduled the optimal operations of chiller system and ESS in the next day considering the TOU tariff and DR scheme. In this DR algorithm is divided into two scheduling's; day-ahead operation scheduling with temperature forecasting error and operation rescheduling on DR operation. In day-ahead operation scheduling, the operations of DR resources are scheduled based on the finite number of ambient temperature scenarios, which have been generated based on the historical ambient temperature data. As well as, the uncertainties in DR event including requested amount of load reduction and specified DR duration are also considered as scenarios. Also, operation rescheduling on DR operation day is proposed to ensure thermal comfort and the benefit of a COB owner. The proposed method minimizes the expected energy cost by a mixed integer linear programming (MILP).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.5
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• pp.1037-1050
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• 2000

A goal of a BISDN network is to provided integrated transport for a wide range of applications such as teleconferencing, Video On Demand etc. There require multipoint communications in addition to conventional point-to-point connections. Therefore multicast capabilities are very essential in multimedia communications. In this paper, we propose a new multicast cell scheduling method on the Parallel Multicast Packet Switch with Ring network: PMRN which are based on separated HOL. In this method, we place two different HOLs, one for unicast cells and the other for multicast cells. Then using non-FIFO scheduling, we can schedule both unicast cells and multicast cells which are available at the time in the input buffer. The simulation result shows that this method reduces the delay in the input buffer and increases the efficiency of both point-to-point network and ring network and finally enhances the bandwidth of the overall packet switch. A goal of a BISDN network is to provided integrated transport for a wide range of applications such as teleconferencing, Video On Demand etc. There require multipoint communications in addition to conventional point-to-point connections. Therefore multicast capabilities are very essential in multimedia communications. In this paper, we propose a new multicast cell scheduling method on the Parallel Multicast Packet Switch with Ring network: PMRN which are based on separated HOL. In this method, we place two different HOLs, one for unicast cells and the other for multicast cells. Then using non-FIFO scheduling, we can schedule both unicast cells and multicast cells which are available at the time in the input buffer. The simulation result shows that this method reduces the delay in the input buffer and increases the efficiency of both point-to-point network and ring network and finally enhances the bandwidth of the overall packet switch.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.287-307
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• 2018

There are two targets to schedule parallel jobs in the Cloud: (1) scheduling the jobs as many as possible, and (2) reducing the average execution time of the jobs. Most of previous work mainly focuses on the computing speed of resources without considering other attributes, such as bandwidth, memory and so on. Especially, past work does not consider the supply-demand condition from those attributes. Resources have different attributes, considering those attributes together makes the scheduling problem more difficult. This is the problem that we try to solve in this paper. First of all, we propose a new parallel job scheduling method based on a classification method of resources from different attributes, and then a scheduling method-CPLMT (Cloud parallel scheduling based on the lists of multiple attributes) is proposed for the parallel tasks. The classification method categories resources into different kinds according to the number of resources that satisfy the job from different attributes of the resource, such as the speed of the resource, memory and so on. Different kinds have different priorities in the scheduling. For the job that belongs to the same kinds, we propose CPLMT to schedule those jobs. Comparisons between our method, FIFO (First in first out), ASJS (Adaptive Scoring Job Scheduling), Fair and CMMS (Cloud-Minmin) are executed under different environments. The simulation results show that our proposed CPLMT not only reduces the number of unfinished jobs, but also reduces the average execution time.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.123-126
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• 1998

Generally, in a VOD(video on Demand) system, batching technique is oten used to improve throughput. Since subscribers to VOD servives tend to withdraw their requests as the latency becomes large, an optimal scheduling scheme should consider not only batching size but also withdrawal rae, service latency and fairness between different programs. In this paper, we propose a new scheduling scheme, which shows improvement in fairness and reduction in withdrawal rate and service latency compared with other well known schemes. When there are 2 or more streams are available in the VOD server, proposed scheme apply different program selection policies to each streams. Using this approach effectiveness of stream usage can be improved.