• Journal of information and communication convergence engineering
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• 제10권3호
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• pp.264-268
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• 2012

Tree-based structures offer assured optimal paths from the data source to the sink. Shortest routes are disregarded since these do not consider the remaining energy level of the nodes. This shortens the lifetime of the whole network. Most tree-based routing protocols, although aware of the nodes' energy, do not consider an energy aware sleep scheduling scheme. We propose an energy-aware sleep scheduling (EASS) scheme that will improve the sleep scheduling scheme of an existing tree-based routing protocol. An energy harvesting structure will be implemented on the wireless sensor network. The depth of sleep of every node will be based on the harvested energy.

• 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.

• Journal of Electrical Engineering and Technology
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• 제11권4호
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• pp.987-992
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• 2016

This study introduces an example environment where wireless devices are mobile, devices use dynamic voltage scaling, devices and tasks are heterogeneous, tasks have deadline, and the computation and communication power is dynamically changed for energy saving. For this type of environment, the efficient system-level energy management and resource management for task completion can be an essential part of the operation and design of such systems. Therefore, the resources are assigned to tasks and the tasks may be scheduled to maximize a goal which is to minimize energy usage while trying to complete as many tasks as possible by their deadlines. This paper also introduces mobility of nodes and variable transmission power for communication which complicates the resource management/task scheduling problem further.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2011년도 춘계학술발표대회
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• pp.92-96
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• 2011

Nowadays, the researches study high rate and real-time query applications seem to be real-time query scheduling protocols and energy aware real time query protocols. Also the WSNs should provide the quality of data in real time query applications that is more and more popular for wireless sensor networks (WSNs). Thus we propose the quality of data function to merge into energy efficiency called energy join quality aware realtime query scheduling (EJQRTQ). Our work calculate the energy ratio that considers interference of queries, and then compute the expected quality of query and allocate slots to real-time preemptive query scheduler.

• ETRI Journal
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• 제44권5호
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• pp.746-758
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• 2022

This paper focuses on a mobile edge-computing-enabled heterogeneous network. A battery level-aware task-scheduling framework is proposed to improve the energy efficiency and prolong the operating hours of battery-powered mobile devices. The formulated optimization problem is a typical mixed-integer nonlinear programming problem. To solve this nondeterministic polynomial (NP)-hard problem, a decomposition-based task-scheduling algorithm is proposed. Using an alternating optimization technology, the original problem is divided into three subproblems. In the outer loop, task offloading decisions are yielded using a pruning search algorithm for the task offloading subproblem. In the inner loop, closed-form solutions for computational resource allocation subproblems are derived using the Lagrangian multiplier method. Then, it is proven that the transmitted power-allocation subproblem is a unimodal problem; this subproblem is solved using a gradient-based bisection search algorithm. The simulation results demonstrate that the proposed framework achieves better energy efficiency than other frameworks. Additionally, the impact of the battery level-aware scheme on the operating hours of battery-powered mobile devices is also investigated.

• 대한전자공학회논문지SD
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• 제46권7호
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• pp.22-28
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• 2009

멀티프로세서가 임베디드 시스템에서 널리 쓰임에 따라 지원되는 전력 최소화 기법을 이용하여 태스크를 수행하기 위해 필요한 에너지의 소모량을 줄여야 할 필요성이 대두된다. 본 논문은 동적 전압 스케일링 및 전력 셧다운을 이용하여 에너지 소모를 최소화 하는 태스크 스케줄링 알고리즘을 멀티프로세서 환경을 위해 제안하였다. 제안된 알고리즘에서는 전력 셧다운시의 에너지 및 타이밍 오버헤드를 고려하여 반복적으로 태스크 할당 및 태스크 순서화를 수행한다. 제안된 반복적인 태스크 스케줄링을 통해 전체 에너지 소모를 줄이는 가장 좋은 해를 얻을 수 있었다. 전체 에너지 소모는 리니어 프로그래밍 모델 및 전력 셧다운의 임계 시간을 고려하여 계산되었다. 실제 어플리케이션으로부터 추출된 표준 태스크 그래프에 기반을 둔 실험 결과를 통해 하드웨어 자원 및 시간제한에 따른 에너지 소모 관계를 분석하였다. 실험 결과를 볼 때 제안된 알고리즘은 기존의 우선권 기반의 태스크 스케줄링에 대해서 의미 있는 성능 향상을 얻을 수 있었다.

• 한국산업정보학회논문지
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• 제16권1호
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• pp.1-8
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• 2011

효율적인 전력관리는 모바일 휴대용 제품 시장에서 중요한 경쟁력 중의 하나이다. 본 논문은 전력을 미리 예측하는 방법으로 실행중인 응용프로그램의 sleep 상태를 이용하는 Energy-Aware Scheduling policy(EASY)를 제안한다. 기존 대기 모드에서 전력소모를 줄이는 방법과의 차이점은 응용프로그램들이 얼마나 오랫동안 스케쥴러에서 sleep 상태에 있었는지를 검사하여 각 응용프로그램들의 동작 상태를 결정한다. EASY 기법은 측정된 sleep 시간을 기준으로 현재의 작업량에 맞는 적정한 CPU 클럭 주파수를 정하고, 다음 작업량의 적정한 CPU 클럭 주파수를 예측함으로서 동작 상태에서 전력 소모를 줄일 수 있다. 실험 결과 기존의 대기모드를 이용한 전력관리 기법과 비교하여 평균적으로 10-30%의 전력소모를 줄임으로써 제안된 기법의 우수성을 입증한다.

• 한국통신학회논문지
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• 제31권9A호
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• pp.884-891
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• 2006

무선 센서 네트워크에서의 센서 노드는 배터리로 동작하기 때문에 에너지에 대한 제약이 있다. 따라서 무선 센서 노드를 위한 효율적인 전력 관리 기법과 스케줄링 기법 설계가 중요한데, 본 논문에서는 운영체제 레벨의 소비 에너지를 줄이기 위한 알고리즘을 제안한다. 효율적인 배터리 사용을 위해 상황에 따라 필요한 컴포넌트에만 전원을 인가함으로써 센서노드의 에너지 소비를 줄일 수 있다. 본 논문에서는 제안한 알고리즘을 시뮬레이션 한 결과 기존의 duty 사이클과 비교하여 최대 56%의 에너지가 절약되었음을 알 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권11호
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• pp.5465-5480
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• 2018

Energy-efficient task scheduling on multi-core server is a fundamental issue in green cloud computing. Multi-core processors are widely used in mobile devices, personal computers, and servers. Existing energy efficient task scheduling methods chiefly focus on reducing the energy consumption of the processor itself, and assume that the cores of the processor are controlled independently. However, the cores of some processors in the market are divided into several voltage islands, in each of which the cores must operate on the same status, and the cost of the server includes not only energy cost of the processor but also the energy of other components of the server and the cost of user waiting time. In this paper, we propose a cost-aware scheduling algorithm ICAS for computation intensive tasks on multi-core server. Tasks are first allocated to cores, and optimal frequency of each core is computed, and the frequency of each voltage island is finally determined. The experiments' results show the cost of ICAS is much lower than the existing method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권12호
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• pp.5800-5818
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• 2018

Interference may occur when several co-located wireless body area networks (WBANs) share the same channel simultaneously, which is compressed by resource scheduling generally. In this paper, a QoS-aware Adaptive Coloring (QAC) scheduling algorithm is proposed, which contains two components: interference sets determination and time slots assignment. The highlight of QAC is to determine the interference graph based on the relay scheme and adapted to the network QoS by multi-coloring approach. However, the frequent resource assignment brings in extra energy consumption and packet loss. Thus we come up with a launch condition for the QAC scheduling algorithm, that is if the interference duration is longer than a threshold predetermined, time slots rescheduling is activated. Furthermore, based on the relative distance and moving speed between WBANs, a prediction model for interference duration is proposed. The simulation results show that compared with the state-of-the-art approaches, the QAC scheduling algorithm has better performance in terms of network capacity, average delay and resource utility.