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A scheduling algorithm for Multi-Tenants Instance-Intensive Workflows

APPLIED MATHEMATICS & INFORMATION SCIENCES 2013年第1Part L期7卷 99-105页

作者： Cui, Lizhen Zhang, Tiantian Xu, Guangquan Yuan, Dong Shandong Univ Sch Comp Sci & Technol Jinan 250101 Peoples R China Shandong Prov Key Lab Software Engn Jinan Shandong Peoples R China Tianjin Univ Sch Comp Sci & Technol Tianjin 300072 Peoples R China Swinburne Univ Technol Fac Informat & Commun Technol Melbourne Vic Australia

As a key service model in cloud computing, SaaS applications are becoming increasingly popular. Multi-tenancy is a key characteristics of SaaS applications. Business processes play a key role in SaaS applications because of the composability and reusability of software services. This paper focuses on multi-tenants instance-intensive workflows system, in which workflows have a large number of instances belonging to multiple tenants in a SaaS environment, and further proposes a scheduling algorithm for multi-tenants workflow instances. This algorithm improves the quality of service (QoS) for tenants and saves the execution cost of workflows. The simulation results demonstrate that the proposed algorithm guarantees the workflow execution conforming to the deadline set by tenants, and reduces the mean execution time for tenants in high priority whilst saves the execution cost for service providers.

关键词： Multi-tenants Instance-intensive workflow scheduling algorithm

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A NEW scheduling algorithm TO PROVIDE PROPORTIONAL QOS IN OPTICAL BURST SWITCHING NETWORKS

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Journal of Electronics(China) 2006年第5期23卷 656-660页

作者： Tan Wei Zhang Zhizhong Luo Yunhan Wang Sheng Li Lemin Key Lab of Opt. Fiber Trans. and Commun. Networks UESTC Chengdu 610054 China Dept of Commun Engineering Chongqing Univ of Posts and Telecommun. Chongqing 400065 China

A new scheduling algorithm, which aims to provide proportional and controllable QoS (Quality of Service) in terms of burst loss probability for OBS (Optical Burst Switching) networks, is proposed on the ba- sis of a survey of QoS schemes in current OBS networks. With simulations, performance analysis and com- parisons are carried out in detail. The results show that, in the proposed scheme, burst loss probabilities are proportional to the given factors and the control of QoS performance can be achieved with better performance. This scheme will be beneficial to the OBS network management and the tariff policy making.

关键词： Optical Burst Switching (OBS) Proportional Quality of Service (QoS) scheduling algorithm

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Towards Sustainable Energy-Efficient Communities Based on a scheduling algorithm

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SENSORS 2019年第18期19卷 3973-3973页

作者： Cruz, Carlos Palomar, Esther Bravo, Ignacio Gardel, Alfredo Univ Alcala Dept Elect Madrid 28871 Spain

The Internet of Things (IoT) and Demand Response (DR) combined have transformed the way Information and Communication Technologies (ICT) contribute to saving energy and reducing costs, while also giving consumers more control over their energy footprint. Unlike current price and incentive based DR strategies, we propose a DR model that promotes consumers reaching coordinated behaviour towards more sustainable (and green) communities. A cooperative DR system is designed not only to bolster energy efficiency management at both home and district levels, but also to integrate the renewable energy resource information into the community's energy management. Initially conceived in a centralised way, a data collector called the aggregator will handle the operation scheduling requirements given the consumers' time preferences and the available electricity supply from renewables. Evaluation on the algorithm implementation shows feasible computational cost (CC) in different scenarios of households, communities and consumer behaviour. Number of appliances and timeframe flexibility have the greatest impact on the reallocation cost. A discussion on the communication, security and hardware platforms is included prior to future pilot deployment.

关键词： cooperative smart community scheduling algorithm consumer preferences renewables

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Phase space load balancing priority scheduling algorithm for cloud computing clusters

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AUTOMATIKA 2023年第4期64卷 1215-1224页

作者： Zheng, Zhou Wuxi Vocat Inst Arts & Technol Informat Ctr Wuxi Yixing Peoples R China Wuxi Vocat Inst Arts & Technol Informat Ctr Wuxi 214206 Yixing Peoples R China

Due to the development of new technologies such as the Internet and cloud computing, high requirements have been placed on the storage and management of big data. At the same time, new applications in the cloud computing environment also pose new requirements for cloud storage systems, such as strong scalability and high concurrency. Currently, the existing nosql database system is based on cloud computing virtual resources, supporting dynamic addition and deletion of virtual nodes. Based on the study of phase space reconstruction, the necessity of considering traffic flow as a chaotic time series is analyzed. In addition, offline data migration methods based on load balancing are also studied. Firstly, a data migration model is proposed through analysis, and the factors that affect migration performance are analyzed. Based on this, optimization objectives for migration are proposed. Then, the system design of data migration is presented, and optimization research is conducted from two aspects around the migration optimization objectives: optimizing from the data source layer, and proposing the LBS method to convert data sources into distributed data sources, ensuring the balanced distribution of data and meeting the scalability requirements of the system. This paper applies cloud computing technology and phase space reconstruction to load balancing scheduling algorithms to promote their development.

关键词： Cloud computing phase space load balance scheduling algorithm

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Improved FIFO scheduling algorithm Based on Fuzzy Clustering in Cloud Computing

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INFORMATION 2017年第1期8卷 25页

作者： Li, Jian Ma, Tinghuai Tang, Meili Shen, Wenhai Jin, Yuanfeng Nanjing Univ Informat Sci & Technol Sch Comp Software Nanjing 210044 Jiangsu Peoples R China Nanjing Univ Informat Sci & Technol Engn Ctr Network Monitoring CICAEET Nanjing 210044 Jiangsu Peoples R China Natl Meteorol Informat Ctr Beijing 100080 Peoples R China YanBian Univ Dept Math Yanji 133002 Peoples R China

In cloud computing, some large tasks may occupy too many resources and some small tasks may wait for a long time based on First-In-First-Out (FIFO) scheduling algorithm. To reduce tasks' waiting time, we propose a task scheduling algorithm based on fuzzy clustering algorithms. We construct a task model, resource model, and analyze tasks' preference, then classify resources with fuzzy clustering algorithms. Based on the parameters of cloud tasks, the algorithm will calculate resource expectation and assign tasks to different resource clusters, so the complexity of resource selection will be decreased. As a result, the algorithm will reduce tasks' waiting time and improve the resource utilization. The experiment results show that the proposed algorithm shortens the execution time of tasks and increases the resource utilization.

关键词： cloud computing fuzzy clustering algorithms FIFO scheduling algorithm resource clustering

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An Improved scheduling algorithm for Data Transmission in Ultrasonic Phased Arrays with Multi-Group Ultrasonic Sensors

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SENSORS 2017年第10期17卷 2355页

作者： Tang, Wenming Liu, Guixiong Li, Yuzhong Tan, Daji South China Univ Technol Sch Mech & Automot Engn Guangzhou 510641 Guangdong Peoples R China Guangzhou Doppler Elect Technol Co Ltd Guangzhou 510663 Guangdong Peoples R China

High data transmission efficiency is a key requirement for an ultrasonic phased array with multi-group ultrasonic sensors. Here, a novel FIFOs scheduling algorithm was proposed and the data transmission efficiency with hardware technology was improved. This algorithm includes FIFOs as caches for the ultrasonic scanning data obtained from the sensors with the output data in a bandwidth-sharing way, on the basis of which an optimal length ratio of all the FIFOs is achieved, allowing the reading operations to be switched among all the FIFOs without time slot waiting. Therefore, this algorithm enhances the utilization ratio of the reading bandwidth resources so as to obtain higher efficiency than the traditional scheduling algorithms. The reliability and validity of the algorithm are substantiated after its implementation in the field programmable gate array (FPGA) technology, and the bandwidth utilization ratio and the real-time performance of the ultrasonic phased array are enhanced.

关键词： ultrasonic phased array scheduling algorithm FIFOs multi-group sensors FPGA bandwidth utilization

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Improved scheduling algorithm for Synchronous Data Flow Graphs on a Homogeneous Multi-Core Systems

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algorithmS 2022年第2期15卷 56页

作者： Wang, Lei Wang, Chenguang Wang, Huabing Univ Elect Sci & Technol China Res Inst Elect Sci & Technol Chengdu 611731 Peoples R China State Key Lab Complex Elect Environm Effects Elec Luoyang 471000 Peoples R China

In order to accelerate the execution of streaming applications on multi-core systems, this article studies the scheduling problem of synchronous data flow graphs (SDFG) on homogeneous multi-core systems. To describe the data flow computation process, we propose the SDAG (Super DAG) computation model based on the DAG model combined with data-driven thoughts. Further, we analyze the current common SDFG scheduling algorithms and propose an improved SDFG scheduling algorithm, LSEFT (level-shortest-first-earliest-finish time). The LSEFT algorithm uses an inverse traversal algorithm to calculate the priority of tasks in the task-selection phase;the shortest-job-priority earliest-finish-time policy is used in the processor selection phase to replace the original long job priority policy. In the experimental part, we designed an SDFG random generator and generated 958 SDFGs with the help of the random generator as test cases to verify the scheduling algorithm. The experimental results show that our improved algorithm performs well for different numbers of processor cores, especially for 8 cores, where the speedup of our improved algorithm improves by 10.17% on average.

关键词： homogeneous synchronous data flow graph computational model multi-core systems scheduling algorithm

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A scheduling algorithm for Optimizing Electric Vehicle Charging Infrastructure in Parking Lots

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INTERNATIONAL JOURNAL OF ENGINEERING 2024年第11期37卷 2239-2255页

作者： Firouzjah, K. Gorgani Bandpey, M. Fattahi Ghasemi, J. Univ Mazandaran Dept Elect Engn Babolsar Iran

Sufficient public parking lots (PLs) are essential for developing of sustainable cities. Different factors such as location, accessibility, safety, and environmental effects must be considered to ensure PLs stability. New technologies such as intelligent parking systems, electric vehicle (EV) charging stations (CSs), and green infrastructure make PLs more sustainable and efficient. In addition to providing parking spaces for ordinary cars (OCs), PLs provide charging services for EVs. After completing charging, EVs can be transferred to another place in the PL to provide charging service for more EVs. This problem is a motivation to present an optimization process for park scheduling in this paper. The proposed process is based on minimizing the number of required chargers. The considered constraints in the optimal scheduling process include providing the requested charging service and parking space for all EVs and OCs. The required parking space is determined based on the available databases and the simultaneous presence of vehicles in the PL. Statistical simulations produce different scenarios of vehicles in PL. The findings demonstrate that the suggested approach enhances the utilization of EV charging infrastructure in PLs. It can address the issue of random parking in public places and determine the parking routine.

关键词： Electric Vehicle scheduling algorithm Public Parking Lots Charging Infrastructure

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An Optimized scheduling algorithm on a Cloud Workflow Using a Discrete Particle Swarm

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CYBERNETICS AND INFORMATION TECHNOLOGIES 2014年第1期14卷 25-39页

作者： Cao, Jianfang Chen, Junjie Zhao, Qingshan Xinzhou Teachers Univ Dept Comp Sci & Technol Xinzhou City 034000 Peoples R China Taiyuan Univ Technol Coll Comp & Software Taiyuan 030024 Peoples R China

In order to solve the problems of security threats on workflow scheduling in cloud computing environments, the security of tasks and virtual machine resources are quantified using a cloud model, and the users' satisfaction degree with the security of tasks assigned to the virtual resources is measured through the similarity of the security cloud. On this basis, combined with security, completion time and cost constraints, an optimized cloud workflow scheduling algorithm is proposed using a discrete particle swarm. The particle in the particle swarm indicates a different cloud workflow scheduling scheme. The particle changes its velocity and position using the evolution equation of the standard particle swarm algorithm, which ensures that it is a feasible solution through the feasible solution adjustment strategies. The simulation experiment results show that the algorithm has better comprehensive performance with respect to the security utility, completion time, cost and load balance compared to other similar algorithms.

关键词： scheduling algorithm cloud workflow discrete particle swarm evolution equation

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A scheduling algorithm for Appliance Energy Consumption Optimization in a Dynamic Pricing Environment

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WORLD ELECTRIC VEHICLE JOURNAL 2024年第1期15卷 1页

作者： Touhs, Hamza Temouden, Anas Khallaayoun, Ahmed Chraibi, Mhammed El Hafdaoui, Hamza Al Akhawayn Univ Sch Sci & Engn Ifrane 53000 Morocco Sidi Mohamed Ben Abdellah Univ Natl Sch Appl Sci Fes 30000 Morocco

This research delves into the intricate landscape of energy scheduling and optimization within microgrid and residential contexts, addressing pivotal aspects such as real-time scheduling systems, challenges in dynamic pricing, and an array of optimization strategies. This paper introduces a cutting-edge scheduling algorithm, harnessing the power of artificial neural networks driven by Long Short-Term Memory Networks, and highlights its exceptional performance, boasting a significantly lower Mean Absolute Error of 5.32 compared to conventional models. This heightened predictive accuracy translates into tangible improvements in both energy efficiency and cost savings. This study underscores the delicate balance between user satisfaction, cost reduction, and efficient scheduling for sustainable energy consumption, showcasing a remarkable 38% enhancement in optimized schedules. Further granularity revealed substantial gains in energy efficiency and cost reduction across different scheduling intensities: 11.11% in light schedules, 20.09% in medium schedules, and an impressive 38.85% in heavy schedules. However, this research does not shy away from highlighting challenges related to data quality, computational demands, and generalizability. Future research trajectories encompass the development of adaptive models tailored to diverse data qualities, enhancements in scalability for and adaptability to various microgrid configurations, the integration of real-time data, the accommodation of user preferences, the exploration of energy storage and renewables, and an imperative focus on enhancing algorithm transparency.

关键词： scheduling algorithm predictive modeling energy cost reduction dynamic pricing time series forecasting

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