• Industrial Engineering and Management Systems
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• v.9 no.2
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• pp.70-79
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• 2010

Makespan and cost minimization are two important factors in project investment. This paper considers a multi-mode resource-constrained project scheduling problem with the objective of minimizing costs, subject to a deadline constraint. A number of studies have focused on minimizing makespan or resource availability cost with a specified deadline. This problem assumes a fixed cost for the availability of each renewable resource per period, and the project cost to be minimized is the sum of the variable cost associated with the execution mode of each activity. The presented memetic algorithm (MA) consists of three features: (1) a truncated branch and bound heuristic that serves as effective preprocessing in forming the initial population; (2) a strategy that maintains two populations, which respectively store deadline-feasible and infeasible solutions, enabling the MA to explore quality solutions in a broader resource-feasible space; (3) a repair-and-improvement local search scheme that refines each offspring and updates the two populations. The MA is tested via ProGen generated instances with problem sizes of 18, 20, and 30. The experimental results indicate that the MA performs exceptionally well in both effectiveness and efficiency using the optimal solutions or the current best solutions for the comparison standard.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.103-109
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• 2019

The automotive electronic system should provide a method that can be safely performed by loading a number of application programs having time constraints in several electronic control devices. In this paper, we propose a timing protection mechanism for AUTOSAR, which is a real - time operating system specification for automotive field, in order to observe the deadline of each task when scheduling real - time tasks. We propose a dynamic non-preemption algorithm to guarantee a flexible deadline for fixed priority or dynamic priority tasks, and a location where execution time can be monitored for errors, and suggest ways to implement the AUTOSAR time protection mechanism.

• ETRI Journal
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• v.32 no.3
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• pp.422-429
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• 2010

We present guaranteed dynamic priority assignment schemes for multiple real-time tasks subject to (m, k)-firm deadlines. The proposed schemes have two scheduling objectives: providing a bounded probability of missing (m, k)-firm constraints and maximizing the probability of deadline satisfactions. The second scheduling objective is especially necessary in order to provide the best quality of service as well as to satisfy the minimum requirements expressed by (m, k)-firm deadlines. We analytically establish that the proposed schemes provide a guarantee on the bounded probability of missing (m, k)-firm constraints. Experimental studies validate our analytical results and confirm the effectiveness and superiority of the proposed schemes with regard to their scheduling objectives.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.2952-2971
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• 2016

Outsourcing jobs to a public cloud is a cost-effective way to address the problem of satisfying the peak resource demand when the local cloud has insufficient resources. In this paper, we studied the management of deadline-constrained bag-of-tasks jobs on hybrid clouds. We presented a binary nonlinear programming (BNP) problem to model the hybrid cloud management which minimizes rent cost from the public cloud while completes the jobs within their respective deadlines. To solve this BNP problem in polynomial time, we proposed a heuristic algorithm. The main idea is assigning the task closest to its deadline to current core until the core cannot finish any task within its deadline. When there is no available core, the algorithm adds an available physical machine (PM) with most capacity or rents a new virtual machine (VM) with highest cost-performance ratio. As there may be a workload imbalance between/among cores on a PM/VM after task assigning, we propose a task reassigning algorithm to balance them. Extensive experimental results show that our heuristic algorithm saves 16.2%-76% rent cost and improves 47.3%-182.8% resource utilizations satisfying deadline constraints, compared with first fit decreasing algorithm, and that our task reassigning algorithm improves the makespan of tasks up to 47.6%.

• Journal of the Korea Computer Industry Society
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• v.4 no.12
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• pp.1053-1068
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• 2003

In this paper, we propose a new scheduling method without timing covert channel of real-time transaction for secure database systems that implement mandatory access control. Our scheduling method use the wait queue based on security level to remove timing covert channel. And it use priority queue that consider transaction type, deadline, and weight. Therefore, the proposed scheduling method prevents timing covert channel because it is kept noninterference between transactions with different security level, and maximizes the sum of the weight of transactions that satisfy its deadline. The simulation results, is a comparison of traditional methods, show that our scheduling method is improved to 30%.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.1
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• pp.9-20
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• 2009

In a real-time system with both hard real-time periodic tasks and soft real-time aperiodic tasks, it is important to guarantee the deadlines of each periodic task as well as obtain fast response time for each aperiodic task. This paper proposes Enhanced Total Bandwidth Server (ETBS) with possibly shorter response time than Total Bandwidth Server (TBS), which is efficient and widely used for servicing aperiodic tasks. For uniprocessor system using Earliest Deadline First (EDF) scheduling algorithm, ETBS assigns an on-line deadline to each aperiodic task considering a surplus slack time which gained for every unit execution time of periodic job. The proposed method can fully utilize the processor while meeting all the deadlines of periodic tasks. We show that the proposed ETBS provides better response time of aperiodic tasks than TBS theoretically, but has the same computational complexity as TBS, O(1). Simulation results show that the response time of aperiodic tasks with ETBS are shorter than one with TBS.

• Journal of Computing Science and Engineering
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• v.2 no.1
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• pp.74-97
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• 2008

A scheduling policy or a schedulability test is defined to be sustainable if any task system determined to be schedulable remains so if it behaves "better" than mandated by its system specifications. We provide a formal definition of sustainability, and subject the concept to systematic analysis in the context of the uniprocessor scheduling of periodic and sporadic task systems. We argue that it is, in general, preferable engineering practice to use sustainable tests if possible, and classify common uniprocessor schedulability tests according to whether they are sustainable or not.

• Journal of KIISE
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• v.43 no.3
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• pp.296-303
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• 2016

Mobile real-time systems with limited system resources and a limited power source need to fully utilize the system resources when the workload is heavy and reduce energy consumption when the workload is light. EDZL (Earliest Deadline until Zero Laxity), a multiprocessor real-time scheduling algorithm, can provide high system utilization, but little work has been done aimed at reducing its energy consumption. This paper tackles the problem of DVFS (Dynamic Voltage/Frequency Scaling) in EDZL scheduling. It proposes a technique to compute a uniform speed on full-chip DVFS platforms and individual speeds of tasks on per-core DVFS platforms. This technique, which is based on the EDZL schedulability test, is a simple but effective one for determining the speeds of tasks offline. We also show through simulation that the proposed technique is useful in reducing energy consumption.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.12
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• pp.277-286
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• 2019

The Unmanned Aerial Vehicle (UAV) is one of the most precious inventions of Internet of things (IOT). UAV faces the necessity to charge battery or replace battery from the charging stations during or between services. We propose scheduling algorithms for drone power charging (SADPC). The basic idea of algorithm is considering both a deadline (for increasing deadline miss ratio) and a charging time (for decreasing waiting time) to decide priority on charging station among drones. Our simulation results show that our power charging algorithm for drones are efficient in terms of the deadline miss ratio as well as the waiting time in general in compare to other conventional algorithms (EDF or SJF). Also, we can choose proper algorithms for battery charge scheduling and charge ready battery allocation according to system parameters and user requirements based on our simulation.

• The KIPS Transactions:PartA
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• v.16A no.6
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• pp.437-442
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• 2009

For multiprocessor systems, Earliest Deadline First (EDF) based on deadline and Least Laxity First (LLF) based on laxity are not suitable for practical environment since EDF has low schedulability and LLF has high context switching overhead. As a combining of EDF and LLF to improve the performance, Earliest Deadline Zero Laxity (EDZL) was proposed. EDZL is basically the same as EDF. But if the laxity of a task becomes zero, its priority is promoted to the highest level. In this paper, we propose Least Laxity Zero Laxity (LLZL) which is based on LLF. But context switching is allowed only if the laxity of a task on rady queue becomes zero. Simulation results show that LLZL has high schedulability approaching to LLF and low context switching overhead similar to EDF. In comparison with EDZL, LLZL has better performance in both of schedulability and context switching overhead.