• Journal of KIISE:Computer Systems and Theory
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• v.34 no.10
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• pp.493-501
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• 2007

The imprecise real-time system provides flexibility in scheduling time-critical tasks. Most scheduling problems of satisfying both 0/1 constraint and timing constraints, while the total error is minimized, are NP-complete when the optional tasks have arbitrary processing times. Liu suggested a reasonable strategy of scheduling tasks with the 0/1 constraint on uniprocessors for minimizing the total error. Song et at suggested a reasonable strategy of scheduling tasks with the 0/1 constraint on multiprocessors for minimizing the total error. But, these algorithms are all off-line algorithms. In the online scheduling, the NORA algorithm can find a schedule with the minimum total error for the imprecise online task system. In NORA algorithm, EDF strategy is adopted in the optional scheduling. On the other hand, for the task system with 0/1 constraint, EDF_Scheduling may not be optimal in the sense that the total error is minimized. Furthermore, when the optional tasks are scheduled in the ascending order of their required processing times, NORA algorithm which EDF strategy is adopted may not produce minimum total error. Therefore, in this paper, an online algorithm is proposed to minimize total error for the imprecise task system with 0/1 constraint. Then, to compare the performance between the proposed algorithm and NORA algorithm, a series of experiments are performed. As a conseqence of the performance comparison between two algorithms, it has been concluded that the proposed algorithm can produce similar total error to NORA algorithm when the optional tasks are scheduled in the random order of their required processing times but, the proposed algorithm can produce less total error than NORA algorithm especially when the optional tasks are scheduled in the ascending order of their required processing times.

• The Journal of Engineering Research
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• v.2 no.1
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• pp.73-82
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• 1997

In this paper, we examine design trends in the development of distributed real-time system. Many real-time systems developed over the last ten years share common characteristics including use of communications, imprecise computations, the object-oriented paradigm, multiprocessor node hardware, dynamic time-driven scheduling and the inclusion of fault tolerance mechanisms. By examining the major design decisions made in previous systems, the best attributes of these systems can be coalesced together to form the "ideal" real-time system. This paper examines such a system and the advantages and disadvantages of the design decisions involved.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.6B
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• pp.1032-1041
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• 1999

This paper proposes on-line scheduling algorithms that reduce the largest weighted error incurred by preemptive imprecise tasks running on a single processor system. The first one is a two-level algorithm. The top-level scheduling, which is executed whenever a new task arrives, determines the processing times to be allotted to tasks in such a way to minimize maximum weighted error as well as to minimize total error. The lower-level algorithm actually allocates the processor to the tasks. The second algorithm extends the on-line algorithm studied by Shih and Liu[4] by formalizing the top-level algorithm mathematically. The numerical simulation shows that the proposed algorithm outperforms the previous works in the sense that it greatly reduces the largest weighted error.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.225-237
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• 2016

In conventional transportation problem (TP), all the parameters are always certain. But, many of the real life situations in industry or organization, the parameters (supply, demand and cost) of the TP are not precise which are imprecise in nature in different factors like the market condition, variations in rates of diesel, traffic jams, weather in hilly areas, capacity of men and machine, long power cut, labourer's over time work, unexpected failures in machine, seasonal changes and many more. To counter these problems, depending on the nature of the parameters, the TP is classified into two categories namely type-2 and type-4 fuzzy transportation problems (FTPs) under uncertain environment and formulates the problem and utilizes the trapezoidal fuzzy number (TrFN) to solve the TP. The existing ranking procedure of Liou and Wang (1992) is used to transform the type-2 and type-4 FTPs into a crisp one so that the conventional method may be applied to solve the TP. Moreover, the solution procedure differs from TP to type-2 and type-4 FTPs in allocation step only. Therefore a simple and efficient method denoted by PSK (P. Senthil Kumar) method is proposed to obtain an optimal solution in terms of TrFNs. From this fuzzy solution, the decision maker (DM) can decide the level of acceptance for the transportation cost or profit. Thus, the major applications of fuzzy set theory are widely used in areas such as inventory control, communication network, aggregate planning, employment scheduling, and personnel assignment and so on.