• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.1
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• pp.1-8
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• 2016

We proposed a load unbalancing scheduling method for energy-efficient multi-core embedded systems considering DVFS (Dynamic Voltage/Frequency Scaling) power consumption and task characteristics. It is a new kind of scheduler which combines load balancing and load unbalancing technique. The purpose of the method is to effectively utilize energy without much effect in performance. In this paper, we conduct experiments on energy consumption and performance using the previous load balancing and unbalancing techniques and our proposed technique. The proposed technique reduced energy consumption more than 13.7% when compared to other algorithms. As a result, the proposed technique shows low energy consumption without much decline in the performance and is adequate for energy-efficient multi-core embedded systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.949-966
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• 2013

Recently, Wireless Body Area Network (WBAN) has promise to revolutionize human daily life. The need for multiple sensors and constant monitoring lead these systems to be energy hungry and expensive with short operating lifetimes. In this paper, we offer a review of existing work of WBAN and focus on energy-aware management in it. We emphasize that nodes computation, wireless communication, topology deployment and energy scavenging are main domains for making a long-lived WBAN. We study the popular power management technique Dynamic Voltage and Frequency Scaling (DVFS) and identify the impact of slack time in Dynamic Power Management (DPM), and finally propose an enhanced dynamic power management method to schedule scaled jobs at slack time with the goal of saving energy and keeping system reliability. Theoretical and experimental evaluations exhibit the effectiveness and efficiency of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.117-135
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• 2016

Performance enhancement is one of the most important issues in high performance distributed computing systems. In such computing systems, online users submit their jobs anytime and anywhere to a set of dynamic resources. Jobs arrival and processes execution times are stochastic. The performance of a distributed computing system can be improved by using an effective load balancing strategy to redistribute the user tasks among computing resources for efficient utilization. This paper presents a multi-class load balancing strategy that balances different classes of user tasks on multiple heterogeneous computing nodes to minimize the per-class mean response time. For a wide range of system parameters, the performance of the proposed multi-class load balancing strategy is compared with that of the random distribution load balancing, and uniform distribution load balancing strategies using simulation. The results show that, the proposed strategy outperforms the other two studied strategies in terms of average task response time, and average computing nodes utilization.

• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1678-1685
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• 1999

In most of the existing real-time schedulers producing the total value as large as possible, the service times for all schedulable tasks are computed at each time a new task arrives. If all scheduled tasks would be executed completely before a new task arrives, the schedule may produce the greatest total value. But this is not always true in real situations. In many cases, (a) new tasks arrive(s) before all the scheduled tasks are executed completely. In this paper, we propose a unique scheduling algorithm for real-time tasks. The proposed algorithm determines the service times only for some tasks with earlier deadlines while the existing algorithms determine the service times for all tasks. This partial computation decreases the average scheduling complexity ramatically, even though, in the worst case, the complexity of the proposed algorithm becomes O(N2), which is equal to that of a previous algorithm that has been known as a less complicated one.

• Journal of Korea Multimedia Society
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• v.7 no.7
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• pp.886-895
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• 2004

In this paper, we propose the dynamic allocation scheme of the CPU bandwidth to efficiently integrate and schedule these tasks in the same system, where multimedia tasks and hard real-time tasks can coexist simultaneously. Hard real-time tasks are guaranteed based on worst case execution times, whereas multimedia tasks modeled as soft real-time tasks are served based on mean parameters. This paper describes a server-based allocation scheme for assigning the CPU resource to two types of tasks. Especially for MPEG video streams, we show how to dynamically control the fraction of the CPU bandwidth allocated to each multimedia task. The primary purpose of the proposed method is to minimize the mean tardiness of multimedia tasks while satisfying the timing constraints of hard real-time tasks present in the system. We showed through simulations that the tardiness experienced by multimedia tasks under the proposed allocation scheme is much smaller than that experienced by using other scheme.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.11
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• pp.549-560
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• 2001

Cluster system provides attractive scalability in terms of compution power and memory size. With the advances in high speed computer network technology, cluster systems are becoming increasingly competitive compared to expensive MPPs (massively parallel processors). Load balancing is very important issue since an inappropriate scheduling of tasks cannot exploit the true potential of the system and can offset the gain from parallelization. In parallel processing program, it is difficult to predict the load of each task before running the program. Furthermore, tasks are interdependent each other in many ways. The dynamic load balancing algorithm, which evaluates each processor's load in runtime, partitions each task into the appropriate granularity and assigns them to processors in proportion to their performance in cluster systems. However, if the communication cost between processing nodes is expensive, it is not efficient for all nodes to attend load balancing process. In this paper, we restrict a processor that attend load balancing by the communication cost and the deviation of its load from the average. We simulate various models of the cluster system with parameters such as communication cost, node number, and range of workload value to compare existing load balancing methods with the proposed dynamic algorithms.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.4
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• pp.18-29
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• 2019

A dynamic adaptive streaming server consumes high processor power because it handles a large amount of transcoding operations at a time. For this purpose, multi-processor architecture is mandatory for which effective transcoding task distribution strategies are essential. In this paper, we present the design and implementation details of the transcoding workload distribution schemes at a 2-tier (frontend node and backend node) transcoding server. For this, we implemented four schemes: 1) allocation of transcoding tasks to appropriate back-end nodes, 2) task scheduling in the back-end node and 3) the communication between front-end and back-end nodes. Experiments were conducted to compare the estimated and the actual power consumption in a real testbed to verify the efficacy of the system. It also proved that the system can reduce the load on each node to optimize the power and time used for transcoding.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1B
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• pp.17-21
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• 2007

In this paper, we propose new on-line processor management algorithms that manage heterogeneous multimedia services while maximizing energy efficiency. These online management mechanisms are combined in an integrated scheme for higher system performance and energy efficiency. The most important feature of our proposed scheme is its adaptability, flexibility and responsiveness to current network conditions. Simulation results clearly indicate the superior performance of our proposed scheme to strike the appropriate performance balance between contradictory requirements.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.591-592
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• 2008

본 논문은 배터리를 이용하는 시스템의 사용시간을 극대화하기 위하여 두 가지 해결책을 제시한다. 첫 번째, 우리는 멀티 프로세서 시스템에서 Dynamic Voltage Scaling(DVS)을 이용하여 에너지 소모를 최소화시킨다. 다른 어프로치와의 큰 차이점은 테스크의 실행 시간을 deadline까지 확장시켜 에너지 소모를 최소화할 뿐만 아니라 테스크의 실행 사이클 수가 감소할것을 고려하여 테스크를 나누어 다른 동작 주파수를 적용 시키고 이를 수학적 방법으로 도출한다. 두 번째, 배터리의 discharge 특성인 capacity rate effect와 recovery effect를 고려하여 프로세서들의 에너지 소모 프로파일을 재구성함으로서 배터리 라이프타임을 최적화시킨다.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.559-564
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• 2013

In this paper a new hybrid forecast method composed of wavelet transform and neural network is proposed to forecast the wind speed more accurately. In the field of wind energy research, accurate forecast of wind speed is a challenging task. This will influence the power system scheduling and the dynamic control of wind turbine. The wind data used here is measured at 15 minute time intervals. The performance is evaluated based on the metrics, namely, mean square error, mean absolute error, sum squared error of the proposed model and compared with the back propagation model. Simulation studies are carried out and it is reported that the proposed model outperforms the compared model based on the metrics used and conclusions were drawn appropriately.