• The KIPS Transactions:PartD
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• v.13D no.2 s.105
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• pp.191-198
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• 2006

Many enterprises have introduced workflow to enhance work efficiency and support effective work processes in their various work environments. Recently, Business Process Management(BPM), an extension of workflow, is spotlighted in enterprise software markets Although woklflow plays an important role in Business Process Managements, researches in workflow are mostly concentrated on temporal constraints which finds exact execution sequences for complicated jobs. On that reason, majority of workflow scheduling has concentrated on modeling of various resources which should be handled and the interest for workflow scheduling under constraints related to resources is rather unsatisfactory In this paper we presents the Transformation Template based on Concurrent Transaction Logic(CTR) which is suitable for scheduling workflows with resource allocation constraints, and the logical framework. The Transformation Template consists of a Workflow Transformation Template and a Constraint Transaction Template. Especially the Transformation Template can be conveniently used to logically represent new workflows under the existing resource allocation constraints.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3876-3895
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• 2014

Recently, Heterogeneous Network (HetNet) with Coordinated Multi-Point (CoMP) scheme is introduced into Long Term Evolution-Advanced (LTE-A) systems to improve digital services for User Equipments (UEs), especially for cell-edge UEs. However, Radio Resource Management (RRM), including Resource Block (RB) scheduling and Power Allocation (PA), in this scenario becomes challenging, due to the intercell cooperation. In this paper, we investigate the RRM problem for downlink transmission of HetNet system with Joint Processing (JP) CoMP (both joint transmission and dynamic cell selection schemes), aiming at maximizing weighted sum data rate under the constraints of both transmission power and backhaul capacity. First, joint RB scheduling and PA problem is formulated as a constrained Mixed Integer Programming (MIP) which is NP-hard. To simplify the formulation problem, we decompose it into two problems of RB scheduling and PA. For RB scheduling, we propose an algorithm with less computational complexity to achieve a suboptimal solution. Then, according to the obtained scheduling results, we present an iterative Karush-Kuhn-Tucker (KKT) method to solve the PA problem. Extensive simulations are conducted to verify the effectiveness and efficiency of the proposed algorithms. Two kinds of JP CoMP schemes are compared with a non-CoMP greedy scheme (max capacity scheme). Simulation results prove that the CoMP schemes with the proposed RRM algorithms dramatically enhance data rate of cell-edge UEs, thereby improving UEs' fairness of data rate. Also, it is shown that the proposed PA algorithms can decrease power consumption of transmission antennas without loss of transmission performance.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2010.05a
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• pp.131-133
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• 2010

As linear scheduling method has been used since 1929, Empire State Building linear schedule, it is being applied in various fields such as construction and manufacturing. When addressing concurrent critical path occurring on linear schedule of construction, the empirical researches stress the resource management which should be applied for optimizing work flow, flexible work productivity and continuos resource allocation. However, work relationships has been usually overlooked for making the linear schedule from existing network schedule. Therefore, this research analyze the previous researches related to linear scheduling model and then propose the method that can be applied for adopting the relationships of network schedule to the linear schedule.

• Korean Journal of Construction Engineering and Management
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• v.8 no.6
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• pp.235-245
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• 2007

This research study presents the development and application of an Elitist Genetic Algorithm (Elitist GA) for solving the resource-constrained project scheduling problem, which is one of the most challenging problems in construction engineering. Main features of the developed algorithm are that the elitist roulette selection operator is developed to preserve the best individual solution for the next generation so as to obtain the improved solution, and that parallel schedule generation scheme is used to generate a feasible solution to the problem. The experimental results on standard problem sets indicate that the proposed algorithm not only produces reasonably good solutions to the problems over the heuristic method and other GA, but also can find the optimal and/or near optimal solutions for the large-sized problems with multiple resources within a reasonable amount of time that will be applicable to the construction industry. This paper will help researchers and/or practitioners in the construction project scheduling software area with alternative means to find the optimal schedules by utilizing the advantages of the Elitist GA.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1728-1731
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• 2002

Scheduling is assigning each operation in a control/data flow graph(CDFG) to a specific control step. It directly influences the performance of the hardware synthesized. In this paper, we propose an efficient resource-constrained scheduling algorithm assuming that only available silicon area is given. We performed the experiment to evaluate its performance. The results show that our algorithm find the solution with shorter scheduling length compared to the existing methods.

• Journal of Korean Institute of Industrial Engineers
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• v.13 no.2
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• pp.35-46
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• 1987

To minimize makespan for preemptive sequence dependent job scheduling with parallel identical processors, fundamental results, as the basis of new algorithm to be presented, such as McNauton's algorithm for independent jobs, Hu's characterization for dependent jobs, and Muntz-Coffman's algorithm, were first introduced. Then a huristic procedure was presented applying those concepts of zoning of assembly line balancing and of resource leveling on CPM network scheduling with two or more of parallel machines in general. New procedure has eliminated presumative machine assignment using ${\rho}$, rate of resource capability (${\rho}$ < 1), for practical scheduling.

• Journal of information and communication convergence engineering
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• v.16 no.4
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• pp.264-270
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• 2018

In our research study, we aim at optimizing multiple load in cloud, effective resource allocation and lesser response time for the job assigned. Using Hadoop on datacenter is the best and most efficient analytical service for any corporates. To provide effective and reliable performance analytical computing interface to the client, various cloud service providers host Hadoop clusters. The previous works done by many scholars were aimed at execution of workflows on Hadoop platform which also minimizes the cost of virtual machines and other computing resources. Earlier stochastic hill climbing technique was applied for single parameter and now we are working to optimize multiple parameters in the cloud data centers with proposed heuristic hill climbing. As many users try to priorities their job simultaneously in the cluster, resource optimized workflow scheduling technique should be very reliable to complete the task assigned before the deadlines and also to optimize the usage of the resources in cloud.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4349-4371
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• 2019

Moldable parallel tasks are widely used in different areas, such as weather forecast, biocomputing, mechanical calculation, and so on. Considering the deadline and the speedup, scheduling moldable parallel tasks becomes a difficulty. Past work majorly focuses on the LA (List Algorithms) or OMA (Optimizing the Middle Algorithms). Different from prior work, our work normalizes execution time and makes all tasks have the same scope in normalized execution time: [0,1], and then according to the normalized execution time, a method is used to search for the reference execution time without considering the deadline of tasks. According to the reference execution time, we get an initial scheduling result based on AFCFS (Adaptive First Comes First Served) policy. Finally, a heuristic approach is used to improve the performance of the initial scheduling result. We call our method HSRET (a Heuristic Scheduling method based on Reference Execution Time). Comparisons to other methods show that HSRET has good performance in AWT (Average Waiting Time), AET (Average Execution Time), and PUT (Percentages of Unfinished Tasks).

• Journal of Information Processing Systems
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• v.11 no.2
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• pp.295-309
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• 2015

Beacon scheduling is considered to be one of the most significant challenges for energy-efficient Low-Rate Wireless Personal Area Network (LR-WPAN) multi-hop networks. The emerging new standard, IEEE802.15.4e, contains a distributed beacon scheduling functionality that utilizes a specific bitmap and multi-superframe structure. However, this new standard does not provide a critical recipe for superframe duration (SD) allocation in beacon scheduling. Therefore, in this paper, we first introduce three different SD allocation approaches, LSB first, MSB first, and random. Via experiments we show that IEEE802.15.4e DSME beacon scheduling performs differently for different SD allocation schemes. Based on our experimental results we propose an adaptive SD allocation (ASDA) algorithm. It utilizes a single indicator, a distributed neighboring slot incrementer (DNSI). The experimental results demonstrate that the ASDA has a superior performance over other methods from the viewpoint of resource efficiency.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.1
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• pp.89-100
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• 2016

Given the unpredictability of the space environment, satellite communications are manually performed by exchanging telecommands and telemetry. Ground support for orbiting satellites is given only during limited periods of ground antenna visibility, which can result in conflicts when multiple satellites are present. This problem can be regarded as a scheduling problem of allocating antenna support (task) to limited visibility (resource). To mitigate unforeseen errors and costs associated with manual scheduling and mission planning, we propose a novel method based on a genetic algorithm to solve the ground support problem of multiple satellites and antennae with visibility conflicts. Numerous scheduling parameters, including user priority, emergency, profit, contact interval, support time, remaining resource, are considered to provide maximum benefit to users and real applications. The modeling and formulae are developed in accordance with the characteristics of satellite communication. To validate the proposed algorithm, 20 satellites and 3 ground antennae in the Korean peninsula are assumed and modeled using the satellite tool kit (STK). The proposed algorithm is applied to two operation modes: (i) telemetry, tracking, and command and (ii) payload. The results of the present study show near-optimal scheduling in both operation modes and demonstrate the applicability of the proposed algorithm to actual mission control systems.