• Journal of Information Processing Systems
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• 제19권4호
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• pp.450-464
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• 2023

To address the problems of large system overhead and low timeliness when dealing with task scheduling in mobile edge cloud computing, a task scheduling and resource management strategy for edge cloud computing based on an improved genetic algorithm was proposed. First, a user task scheduling system model based on edge cloud computing was constructed using the Shannon theorem, including calculation, communication, and network models. In addition, a multi-objective optimization model, including delay and energy consumption, was constructed to minimize the sum of two weights. Finally, the selection, crossover, and mutation operations of the genetic algorithm were improved using the best reservation selection algorithm and normal distribution crossover operator. Furthermore, an improved legacy algorithm was selected to deal with the multi-objective problem and acquire the optimal solution, that is, the best computing task scheduling scheme. The experimental analysis of the proposed strategy based on the MATLAB simulation platform shows that its energy loss does not exceed 50 J, and the time delay is 23.2 ms, which are better than those of other comparison strategies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권8호
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• pp.2736-2750
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• 2022

As demands for the maritime communications increase, a variety of functions and information are required to exchange via elements of maritime systems, which leads communication traffic increases in maritime frequency bands, especially in VHF (Very High Frequency) band. Thus, effective resource management is crucial to the future maritime communication systems not only to the typical terrestrial communication systems. VHF data exchange system (VDES) enables to utilize more flexible configuration according to the communication condition. This paper focuses on the VDES communication system among VDES terminals such as shore stations, ship stations and aids to navigation (AtoN) to address efficient resource allocation. We propose a resource management method considering a MIMO (Multiple Input Multiple Output) technique in VDES, which has been widely used for modern terrestrial wireless networks but not for marine environments by scheduling the essential communication resources. We introduce the general channel model in marine environment and give two metrics, spectral and the energy efficiencies to examine our resource scheduling algorithm. Based on the simulation results and analysis, the proposed method provides a possibility to enhance spectral and energy efficiencies. Additionally, we present a trade-off relationship between spectral and energy efficiencies. Furthermore, we examine the resource efficiencies related to the imperfect channel estimation.

• 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.

• 한국컴퓨터정보학회논문지
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• 제29권9호
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• pp.169-177
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• 2024

IWSN(Industrial Wireless Sensor Network)는 센서, 로봇, 기계 등의 산업 장비들을 무선으로 연결하여 공정 모니터링 및 제어를 통한 산업 자동화 실현을 가능하게 하는 산업 IoT의 핵심 기술로써 실시간, 신뢰성, 에너지 효율 등 현대 산업환경의 엄격한 요구사항을 지원해야 한다. 이를 위해 IWSN에서는 다중 라우팅 경로 설정, 고정적 중복자원 할당 및 비경쟁 기반 스케줄링 등 신뢰적 통신 방식이 사용된다. 그러나 활용되지 않는 무선 자원의 낭비는 한정된 무선 자원의 효율뿐만 아니라 에너지 효율을 저하한다. 본 논문에서는 통신 스케줄링 시 강화학습을 활용하여 사용되지 않는 할당된 무선 자원을 파악하고, 이를 반영한 자원 재할당을 통해 전체 산업 네트워크의 에너지 소모를 절약하는 방안을 제안한다. 실험을 통한 성능평가 결과, 제안 방안은 높은 전송 신뢰성을 유지하면서도 기존 방법에 비해 약 30% 향상된 스케줄링 자원 효율을 보였다. 또한, 불필요한 통신을 줄임으로써 에너지 효율 및 전송지연이 각각 21%, 38% 이상 개선됨을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권5호
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권6호
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• pp.2282-2303
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• 2021

To solve the problems of heavy computing load and system transmission pressure in energy internet (EI), we establish a three-tier cloud-edge integrated EI network based on a cloud-edge collaborative computing to achieve the tradeoff between energy consumption and the system delay. A joint optimization problem for resource allocation and task offloading in the threetier cloud-edge integrated EI network is formulated to minimize the total system cost under the constraints of the task scheduling binary variables of each sensor node, the maximum uplink transmit power of each sensor node, the limited computation capability of the sensor node and the maximum computation resource of each edge server, which is a Mixed Integer Non-linear Programming (MINLP) problem. To solve the problem, we propose a joint task offloading and resource allocation algorithm (JTOARA), which is decomposed into three subproblems including the uplink transmission power allocation sub-problem, the computation resource allocation sub-problem, and the offloading scheme selection subproblem. Then, the power allocation of each sensor node is achieved by bisection search algorithm, which has a fast convergence. While the computation resource allocation is derived by line optimization method and convex optimization theory. Finally, to achieve the optimal task offloading, we propose a cloud-edge collaborative computation offloading schemes based on game theory and prove the existence of Nash Equilibrium. The simulation results demonstrate that our proposed algorithm can improve output performance as comparing with the conventional algorithms, and its performance is close to the that of the enumerative algorithm.

• 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.

• Journal of Electrical Engineering and Technology
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• 제12권5호
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• pp.1709-1718
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• 2017

This paper presents a hybrid stochastic deterministic multi-timescale scheduling (SDMS) approach for generation scheduling of a power grid. SDMS considers flexible resource options including conventional generation flexibility in a chance-constrained day-ahead scheduling optimization (DASO). The prime objective of the DASO is the minimization of the daily production cost in power systems with high penetration scenarios of variable generation. Furthermore, energy storage is scheduled in an hourly-ahead deterministic real-time scheduling optimization (RTSO). DASO simulation results are used as the base starting-point values in the hour-ahead online rolling RTSO with a 15-minute time interval. RTSO considers energy storage as another source of grid flexibility, to balance out the deviation between predicted and actual net load demand values. Numerical simulations, on the IEEE RTS test system with high wind penetration levels, indicate the effectiveness of the proposed SDMS framework for managing the grid flexibility to meet the net load demand, in both day-ahead and real-time timescales. Results also highlight the adequacy of the framework to adjust the scheduling, in real-time, to cope with large prediction errors of wind forecasting.

• Journal of Information Processing Systems
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• 제11권2호
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• pp.295-309
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• 2015

Beacon scheduling is considered to be one of the most significant challenges for energy-efficient Low-Rate Wireless Personal Area Network (LR-WPAN) multi-hop networks. The emerging new standard, IEEE802.15.4e, contains a distributed beacon scheduling functionality that utilizes a specific bitmap and multi-superframe structure. However, this new standard does not provide a critical recipe for superframe duration (SD) allocation in beacon scheduling. Therefore, in this paper, we first introduce three different SD allocation approaches, LSB first, MSB first, and random. Via experiments we show that IEEE802.15.4e DSME beacon scheduling performs differently for different SD allocation schemes. Based on our experimental results we propose an adaptive SD allocation (ASDA) algorithm. It utilizes a single indicator, a distributed neighboring slot incrementer (DNSI). The experimental results demonstrate that the ASDA has a superior performance over other methods from the viewpoint of resource efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권2호
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• pp.559-573
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• 2016

In this paper, we investigate the problem of achieving proportional fairness in hierarchical wireless sensor networks. Combining clustering formulation and scheduling, we maximize total bandwidth utility for proportional fairness while controlling the power consumption to a minimum value. This problem is decomposed into two sub-problems and solved in two stages, which are Clustering Formulation Stage and Scheduling Stage, respectively. The above algorithm, called CSPF_PC, runs in a network formulation sequence. In the Clustering Formulation Stage, we let the sensor nodes join to the cluster head nodes by adjusting transmit power in a greedy strategy; in the Scheduling Stage, the proportional fairness is achieved by scheduling the time-slot resource. Simulation results verify the superior performance of our algorithm over the compared algorithms on fairness index.