• Journal of Communications and Networks
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• v.16 no.3
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• pp.293-300
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• 2014

As energy harvesting communication systems emerge, there is a need for transmission schemes that dynamically adapt to the energy harvesting process. In this paper, after exhibiting a finite-horizon online throughput-maximizing scheduling problem formulation and the structure of its optimal solution within a dynamic programming formulation, a low complexity online scheduling policy is proposed. The policy exploits the existence of thresholds for choosing rate and power levels as a function of stored energy, harvest state and time until the end of the horizon. The policy, which is based on computing an expected threshold, performs close to optimal on a wide range of example energy harvest patterns. Moreover, it achieves higher throughput values for a given delay, than throughput-optimal online policies developed based on infinite-horizon formulations in recent literature. The solution is extended to include ergodic time-varying (fading) channels, and a corresponding low complexity policy is proposed and evaluated for this case as well.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2003-2021
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• 2020

Today's computer systems are widely integrated with CPU and GPU to achieve considerable performance, but energy consumption of such system directly affects operational cost, maintainability and environmental problem, which has been aroused wide concern by researchers, computer architects, and developers. To cope with energy problem, we propose a task-scheduling framework to reduce energy under performance constraint by rationally allocating the tasks across the CPU and GPU. The framework first collects the estimated energy consumption of programs and performance information. Next, we use above information to formalize the scheduling problem as the 0-1 knapsack problem. Then, we elaborate our experiment on typical platform to verify proposed scheduling framework. The experimental results show that our proposed algorithm saves 14.97% energy compared with that of the time-oriented policy and yields 37.23% performance improvement than that of energy-oriented scheme on average.

• Management Science and Financial Engineering
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• v.20 no.2
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• pp.33-37
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• 2014

A flow shop scheduling problem involves scheduling jobs on multiple machines in series in order to optimize a given criterion. The flow time of a job is the amount of time the job spent before its completion and the stretch of the job is the ratio of its flow time to its processing time. In this paper, a hybrid genetic algorithm (HGA) approach is proposed for minimizing the total stretch in flow shop scheduling. HGA adopts the idea of seed selection and development in order to reduce the chance of premature convergence that may cause the loss of search power. The performance of HGA is compared with that of genetic algorithms (GAs).

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.73-76
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• 2001

High-level synthesis generates a structural design that implements the given behavior and satisfies design constraints for area, performance, power consumption, packaging, testing and other criteria. Thus, high-level synthesis generates that register-transfer(RT) level structure from algorithm level description. High-level synthesis consist of compiling, partitioning, scheduling. In this paper, we proposed the efficient scheduling algorithm that find the number of the functional unit and scheduling into the minimum control step with silicon area resource constrained.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4429-4445
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• 2019

As low-power and low-rate WSNs are being widely used for industrial applications, the scheduling of such applications becomes a critical issue to guarantee meeting the stringent requirements of determinism and tight latencies. This paper studies the link scheduling problem for real-time industrial applications in time-slotted channel hopping (TSCH) networks. We propose a heuristic algorithm for centralized link scheduling referred to as path-collision aware least laxity first (PC-LLF) algorithm, which dynamically prioritizes the packets based on the laxity time to the end-to-end deadlines and the amount of collisions that messages might deal with along their designated paths to the destination device. We propose schedulability analysis of real-time applications scheduled under our prioritization approach over TSCH networks, based on the literature on real-time schedulability analysis of multiprocessors and distributed systems. We show that our methodology provides an improved schedulability condition with respect to the existing approaches. Performance evaluation studies quantify to quantify the performance of our proposed approach under a variety of scenarios.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.5
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• pp.1-17
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• 1997

With the increasing performance and density of VLSI scircuits as well as the popularity of portable devices such as personal digital assitance, power consumption has emerged as an important issue in the design of electronic systems. Low power design techniqeus have been pursued at all design levels. However, it is more effective to attempt to reduce power dissipation at higher levels of abstraction which allow wider view. In this paper, we propose a simultaneous scheduling and binding scheme which increases the correlation between cosecutive inputs to an operation so that the switched capacitance of execution units is reduced in datapath-dominated circuits. The proposed method is implemented and integrated into the scheduling and assignment part of HYPER synthesis environment. Compared with original HYPER synthesis system, average power saving of 23.0% in execution units and 14.2% in the whole circuits, ar eobtained for a set of benchmark examples.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.257-263
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• 2002

Test scheduling of SoC becomes more important because it is one of the prime methods to minimize the testing time under limited power consumption of SoCs. In this paper, a heuristic algorithm, in which test resources are selected for groups and arranged based on the size of product of power dissipation and test time together with total power consumption in core-based SoCs is proposed. We select test resource groups which has maximum power consumption but does not exceed the constrained power consumption and make the testing time slot of resources in the test resource group to be aligned at the initial position to minimize the idle test time of test resources.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.1
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• pp.59-64
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• 2020

Scheduling of electric vehicles and optimizing for charging waiting time have been critical. Meanwhile, it is challengeable to exploit the fluctuating data from electric vehicles in real-time. We introduce an optimal routing algorithm and a simulator with electric vehicles obeying the Poisson distribution of the observed information about time, space and energy-demand. Electric vehicle routing is updated in every cycle even it is already set. Also, we suggest an electric vehicle routing algorithm for minimizing total trip time, considering a threshold of the waiting time. Total trip time and charging waiting time are decreased 34.3% and 86.4% respectively, compared to the previous algorithm. It can be applied to the information service of charging stations and utilized as a reservation service.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.312-317
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• 1998

Reliable maintenance scheduling of main equipments is a crucial problem in thermal power stations in order to skirt overall losses of power generation resulted from severe failures of the equipments. A reasonable method was proposed to determine the maintenance scheduling of whole pump system in thermal power stations in order to reduce the maintenance cost by keeping the present avail-ability of the pump system throughout the operation. The dimensional reduction method was used to solve problems encountered due to few data which involved many operational factors in failure rate of pumps. The problem of bandlimited nature of data with time was solved by extrapolating future failures from presently available actual data with an aid of Weibull distribution. The results of the analysis identified the most suitable maintenance intervals of each pump type accordingly and hence reduce the cost of unnecessary maintenance with an acceptable range in the overall system availability.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.127_128
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• 2009

A new technique using a search method which is based on fuzzy multi-criteria function is proposed for GMS(generator maintenance scheduling) in order to consider multi-objective function. Not only minimization of probabilistic production cost but also maximization of system reliability level are considered for fuzzy multi-criteria function. To obtain an optimal solution for generator maintenance scheduling under fuzzy environment, fuzzy multi-criteria relaxation method(fuzzy search method) is used. The practicality and effectiveness of the proposed approach are demonstrated by simulation studies for a real size power system model in Korea in 2010.