• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권11호
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• pp.3523-3543
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• 2022

Autonomous vehicles are gradually being regarded as the mainstream trend of future development of the automobile industry. Autonomous driving networks generate many intensive and delay-sensitive computing tasks. The storage space, computing power, and battery capacity of autonomous vehicle terminals cannot meet the resource requirements of the tasks. In this paper, we focus on the task scheduling problem of autonomous driving in software-defined edge networks. By analyzing the intensive and delay-sensitive computing tasks of autonomous vehicles, we propose an emotion model that is related to task urgency and changes with execution time and propose an optimal base station (BS) task scheduling (OBSTS) algorithm. Task sentiment is an important factor that changes with the length of time that computing tasks with different urgency levels remain in the queue. The algorithm uses task sentiment as a performance indicator to measure task scheduling. Experimental results show that the OBSTS algorithm can more effectively meet the intensive and delay-sensitive requirements of vehicle terminals for network resources and improve user service experience.

• Journal of Computing Science and Engineering
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• 제7권1호
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• pp.30-43
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• 2013

Multicore and multiprocessor systems with dynamic voltage scaling architectures are being used as one of the solutions to satisfy the growing needs of high performance applications with low power constraints. An important aspect that has propelled this solution is effective task/application scheduling and mapping algorithms for multiprocessor systems. This work proposes an energy aware, offline, probability-based unified scheduling and mapping algorithm for multiprocessor systems, to minimize the number of processors used, maximize the utilization of the processors, and optimize the energy consumption of the multiprocessor system. The proposed algorithm is implemented, simulated and evaluated with synthetic task graphs, and compared with classical scheduling algorithms for the number of processors required, utilization of processors, and energy consumed by the processors for execution of the application task graphs.

• 한국콘텐츠학회논문지
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• 제9권12호
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• pp.52-63
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• 2009

본 논문에서는 유니폼 멀티프로세서 환경에서 단순 주기성 태스크 시스템을 성공적으로 스케줄 할 수 있는 알고리즘을 제안한다. 멀티프로세서 환경에서 주기성 태스크를 스케줄하기 위한 파티션드(partitioned) 스케줄링 알고리즘은 bin-packing 문제와 같은 문제로써 해결하는 게 불가능하다고 알려져 있다. 본 논문에서는 "task-splitting"기법을 이용하여 단순 주기성 태스크 시스템을 다른 단순 주기성 태스크 시스템으로 변환하는 글로벌(global) 스케줄링 알고리즘을 제시하고, 변환과정을 거친 단순 주기성 태스크 시스템은 유니폼 멀티프로세서에서 파티션드 스케줄링 알고리즘에 의해 성공적으로 스케줄 된다. 그리고 유니폼 멀티프로세서 환경에서 제안한 알고리즘이 이론적으로 최대 이용률 범위(utilization bound)까지 성공적으로 스케줄 할 수 있음을 증명한다.

• 한국정보처리학회논문지
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• 제7권10호
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• pp.3055-3063
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• 2000

본 논문에서는 공유 메모리 다중 프로세서 시스템에서 태스크 중복을 기반으로 하는 휴리스틱 스케줄링 알고리즘을 제안한다. 제안된 알고리즘에서는 공유 메모리에서 통신할 때 발생되는 충돌을 방지하기 위하여 네트웍 통신 자원을 우선 할당하고, 스케줄링 길이를 단축하고 병렬처리 시간을 줄이기 위한 중복 태스크를 선택할 때 휴리스틱을 사용한다. 제안된 알고리즘은 태스크 그래프를 입력으로 받아 다중 프로세서로 스케줄링하며, 시스템에서 사용 가능한 프로세서의 수에 맞도록 태스크를 스케줄링 할 수 있다. 시뮬레이션에서는 제안된 알고리즘을 실제 응용프로그램의 태스크 그래프에 적용하였으며, 프로세서 수의 변화에 따른 스케줄링 길이를 비교하여 제안된 알고리즘의 성능이 우수함을 보여주었다.

• 한국멀티미디어학회논문지
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• 제9권1호
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• pp.119-126
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• 2006

멀티 프로세서 시스템에서 스케쥴링은 매우 중요한 부분이지만, 최적의 해를 구하는 것이 복잡하여 최근 다양한 휴리스틱 방법들에 의한 스케쥴링 알고리즘들이 제안되고 있다. 본 논문에서는 유전 알고리즘을 이용한 새로운 스케쥴링 알고리즘을 제시한다. 또한, 해를 구하는 과정에서 시뮬레이티드 어닐링 (simulated annealing)의 확률을 이용하여 유전 알고리즘의 성능을 개선시킨다. 제시된 알고리즘은 태스크들의 최종 수행 완료 시간 (makespan)을 최소화하는 것을 목표로 한다. 모의 실험을 통하여 제시된 알고리즘이 다른 알고리즘보다 최종 수행 완료 시간이 작음을 확인할 수 있었다.

• 인터넷정보학회논문지
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• 제12권6호
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• pp.1-17
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• 2011

분산 이기종 컴퓨팅 시스템의 성능은 입력 그래프인 방향성 비순환 그래프DAG)를 스케줄링 하는 알고리즘의 성능에 따라 좌우된다. 그러나 분산 이기종 컴퓨팅 시스템에서의 태스크 스케줄링은 NP-complete 문제로 휴리스틱 방법으로 접근해야한다. 태스크 스케줄링 알고리즘은 우선순위 결정 단계와 프로세서 할당 단계로 구성되며, 많은 연구들이 두 단계를 함께 고려하고 있다. 본 논문에서는 태스크 우선순위 결정 단계에 초점을 맞추어 태스크 복제 기반 프로세서 할당 방법에 최적화된 태스크 우선순위 결정 알고리즘인 WPD 알고리즘을 제안한다. 제안하는 WPD 알고리즘의 성능 분석을 위해 태스크 복제 기반 프로세서 할당 방법을 사용하는 기존의 태스크 스케줄링 알고리즘인 HMPID, HCPFD, HCT 알고리즘의 프로세서 할당 단계에 본 논문에서 제안하는 WPD 알고리즘을 결합하여 성능을 비교하였다. 그 결과 본 논문에서 제안하는 WPD 알고리즘이 기존 태스크 우선순위 결정 방법에 비해 태스크 복제를 더욱 효율적으로 사용하여 HCPFD 알고리즘보다 9.58%, HCT 알고리즘보다 1.31% 성능 향상이 있는 것을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권11호
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• pp.3638-3657
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• 2022

In urban vehicular edge computing (VEC) environments, one edge server always serves many task requests in its coverage which results in the resource-constrained problem. To resolve the problem and improve system utilization, we first design a general hierarchical resource management framework based on typical VEC network structures. Following the framework, a specific interacting protocol is also designed for our decision algorithm. Secondly, a greedy bidding-based multi-hop task scheduling decision algorithm is proposed to realize effective task scheduling in resource-constrained VEC environments. In this algorithm, the goal of maximizing system utility is modeled as an optimization problem with the constraints of task deadlines and available computing resources. Then, an auction mechanism named greedy bidding is used to match task requests to edge servers in the case of multiple hops to maximize the system utility. Simulation results show that our proposal can maximize the number of tasks served in resource constrained VEC networks and improve the system utility.

• 한국자동차공학회논문집
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• 제24권2호
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• pp.127-136
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• 2016

The camera based object detection systems should satisfy the recognition performance as well as real-time constraints. Particularly, in safety-critical systems such as Autonomous Emergency Braking (AEB), the real-time constraints significantly affects the system performance. Recently, multi-core processors and system-on-chip technologies are widely used to accelerate the object detection algorithm by distributing computational loads. However, due to the advanced hardware, the complexity of system architecture is increased even though additional hardwares improve the real-time performance. The increased complexity also cause difficulty in migration of existing algorithms and development of new algorithms. In this paper, to improve real-time performance and design complexity, a task scheduling strategy is proposed for visual object tracking systems. The real-time performance of the vision algorithm is increased by applying pipelining to task scheduling in a multi-core processor. Finally, the proposed task scheduling algorithm is applied to crosswalk detection and tracking system to prove the effectiveness of the proposed strategy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권8호
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• pp.3516-3541
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• 2018

Task scheduling is one of the most challenging aspects of cloud computing nowadays, and it plays an important role in improving overall performance in, and services from, the cloud, such as response time, cost, makespan, and throughput. A recent cloud task-scheduling algorithm based on the symbiotic organisms search (SOS) algorithm not only has fewer specific parameters, but also incurs time complexity. SOS is a newly developed metaheuristic optimization technique for solving numerical optimization problems. In this paper, the basic SOS algorithm is reduced, and chaotic local search (CLS) is integrated into the reduced SOS to improve the convergence rate. Simulated annealing (SA) is also added to help the SOS algorithm avoid being trapped in a local minimum. The performance of the proposed SA-CLS-SOS algorithm is evaluated by extensive simulation using the Matlab framework, and is compared with SOS, SA-SOS, and CLS-SOS algorithms. Simulation results show that the improved hybrid SOS performs better than SOS, SA-SOS, and CLS-SOS in terms of convergence speed and makespan.

• 한국멀티미디어학회논문지
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• 제10권12호
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• pp.1741-1751
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• 2007

The imprecise computation technique ensures that all time-critical tasks produce their results before their deadlines by trading off the quality of the results for the computation time requirements of the tasks. In the imprecise computation, most scheduling problems of satisfying both 0/1 constraints and timing constraints, while the total error is minimized, are NP-complete when the optional tasks have arbitrary processing times. In the previous studies, the reasonable strategies of scheduling tasks with the 0/1 constraints on uniprocessors and multiprocessors for minimizing the total error are proposed. But, these algorithms are all off-line algorithms. Then, in the on-line scheduling, NORA(No Off-line tasks and on-line tasks Ready upon Arrival) algorithm can find a schedule with the minimum total error. In NORA algorithm, EDF(Earliest Deadline First) strategy is adopted in the scheduling of optional tasks. On the other hand, for the task system with 0/1 constraints, NORA algorithm may not suitable any more for minimizing total error of the imprecise tasks. Therefore, in this paper, an on-line algorithm is proposed to minimize total error for the imprecise real-time task system with 0/1 constraints. This algorithm is suitable for the imprecise on-line system with 0/1 constraints. Next, to evaluate performance of this algorithm, a series of experiments are done. As a consequence of the performance comparison, it has been concluded that IOSMTE(Imprecise On-line Scheduling to Minimize Total Error) algorithm proposed in this paper outperforms LOF(Longest Optional First) strategy and SOF(Shortest Optional First) strategy for the most cases.