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16th Annual International Conference on Combinatorial Optimization and Applications, COCOA 2023

作者： Sun, Zaixing Li, Zhikai Gu, Chonglin Huang, Hejiao Shenzhen518055 China

ISBN: (纸本)9783031496103

Cloud computing has a powerful ability to handle a large number of tasks. Correspondingly, it also consumes a lot of energy. Reducing the energy consumption of cloud service platforms while ensuring the quality of service has become a crucial issue. In this paper, we propose a heuristic energy-saving scheduling algorithm named Real-time Multi-workflow Energy-efficient scheduling (RMES) with the aim to minimize the total energy consumption in container cloud. RMES executes tasks as parallel as possible to enhance the resource utilization of the running machines in cluster, therefore reducing the time of the global process, saving energy as a result. RMES takes advantage of the affinity between containers and machines to meet the resource quantity and performance requirements of containers during scheduling. In order to follow the change of the system state overtime, we introduce the re-scheduling mechanism, which can automatically adjust the scheduling decisions of the tasks that have not yet been executed in the scheduling scheme. The experimental results show that RMES has obvious advantages over other scheduling algorithms in terms of energy consumption and success ratio. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： scheduling algorithms

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AOS mixed channel scheduling strategy 4

AOS mixed channel scheduling strategy

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4th International Conference on Signal Image Processing and Communication, ICSIPC 2024

作者： Guo, Xin Bie, Yuxia Wang, Xiaoyu Wu, Xiping School of Electronics and Information Engineering Shenyang Aerospace University Shenyang China

ISBN: (纸本)9781510682467

In order to improve the efficiency of spatial data transmission and meet different service requirements, this study effectively manages multiple data streams through virtual channel multiplexing. In particular, for asynchronous data streams, this study employs an innovative Zebra Optimization Algorithm for scheduling. The algorithm takes into account key factors such as the priority of each service, the delay tolerance and the urgency of the remaining amount of frame data when deciding the scheduling order of the virtual channel. As verified by simulation experiments, this optimized scheduling strategy for asynchronous channels achieves significant improvement in scheduling efficiency, especially in reducing the average scheduling delay and reducing the frame data residual. © 2024 SPIE.

关键词： scheduling algorithms

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Optimal scheduling of Provincial local Coordinated Based on Source-grid-load-storage Interactions 25

Optimal Scheduling of Provincial local Coordinated Based on ...

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25th IEEE China Conference on System Simulation Technology and its Application, CCSSTA 2024

作者： Zhang, Haixuan Kong, Xiangyu Zhang, Delong Liu, Jiancun Zhou, Xuesong Liu, Mao Tianjin University of Technology Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin China Tianjin University Key Laboratory of Smart Grid Tianjin China

ISBN: (纸本)9798350366600

Considering the characteristics of coordination among source-network-load-storage, a provincial local coordinated scheduling method based on the interaction of sourcenetwork-load-storage is proposed. Firstly, the interaction mechanism of source-grid-load-storage is refined. Secondly, according to the spatial characteristics of the scheduling of provincial local coordinated, a multi-objective optimal scheduling model is established with the objectives of economy and new energy consumption. Thirdly, a genetic algorithm is used to solve the problem. Finally, by analyzing the examples, it is proved that the proposed method can reduce the system cost and improve the utilization rate of new energy. © 2024 IEEE.

关键词： scheduling algorithms

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An Adaptive User scheduling Algorithm for 6G Massive MIMO Systems 26

An Adaptive User Scheduling Algorithm for 6G Massive MIMO Sy...

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26th International Conference on Advanced Communications Technology, ICACT 2024

作者： Chataut, Robin Akl, Robert School of Computing and Engineering Quinnipiac University United States University of North Texas Department of Computer Science DentonTX76201 United States

ISBN: (纸本)9791188428120

Massive MIMO (Multiple-Input Multiple-Output) is a promising wireless access technology that has emerged as a solution to the ever-increasing demand for network capacity. Massive MIMO is expected to play a crucial role in the deployment of 5G and upcoming 6G networks, enabling the realization of their full potential capacity. Despite the numerous benefits, user scheduling during downlink communication in Massive MIMO systems is a challenging task due to the large number of antenna terminals. In this paper, we propose a novel scheduling algorithm aimed at improving the area throughput, sum capacity, error performance, and ensuring fairness among all users. The proposed algorithm uses the average channel rate as the scheduling criteria, which is calculated from the channel state information obtained from the users during uplink transmission. To evaluate the performance of our proposed algorithm, we conducted simulations using Matlab. Our results demonstrate that our proposed channel rate-based scheduling algorithm is superior to conventional scheduling algorithms in terms of sumrate, throughput, and bit error performance while also ensuring fairness among all users. The proposed algorithm can address the challenge of user scheduling in Massive MIMO systems and contribute to the efficient deployment of 5G and 6G networks. The ability to improve system capacity, area throughput, and provide fairness in communication is of great importance in meeting the high demands of future wireless networks. Our approach could pave the way for further research in improving the performance of Massive MIMO systems, thereby advancing the potential of 5G and 6G networks. © 2024 Global IT Research Institute - GIRI.

关键词： scheduling algorithms

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Streamlining Load scheduling in Cloud Computing: A Thorough Performance Assessment and Development of Effective Methods for Design

Streamlining Load Scheduling in Cloud Computing: A Thorough ...

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2024 International Conference on Advances in Modern Age Technologies for Health and Engineering Science, AMATHE 2024

作者： Kavitha, M.S. Ramachandra Rao, G. Karthik, S. Sns College Of Technology Department Of Cse Coimbatore India

ISBN: (纸本)9798350371567

In order to satisfy the various cloud applications' quality of service needs, load scheduling in the cloud is a challenging operation that significantly depends on the effective distribution of resources. The intrinsic variability, unpredictable nature, and dispersed nature of cloud systems are the root causes of the issues. Advanced load scheduling methods are required to maximize performance and resource usage because traditional resource allocation mechanisms frequently fail to solve these problems. A variety of approaches, each tailored to address a particular facet of the cloud's resource allocation dilemma, are presented in the literature on load scheduling algorithms. Researchers and practitioners still have a great deal of difficulty when deciding which load scheduling approach is best suited for a given workload. The intrinsic variability of cloud environments' resources is one of the key variables impacting how effective load scheduling algorithms are. A range of resources with unique features and capabilities are included in cloud infrastructures. Network setups, storage choices, and various virtual machine kinds are a few examples. Because of this, load scheduling algorithms have to negotiate this complex environment to distribute resources as efficiently as possible, taking into account variables like processing speed, memory capacity, and network bandwidth. Another issue in cloud settings is the unpredictable nature of workloads. Depending on user activity, application requirements, and outside variables, resource consumption may vary suddenly. For resources to be distributed effectively to meet shifting needs, load scheduling algorithms must be flexible and sensitive to these variations. Its flexibility is essential to sustaining peak performance and avoiding wasteful or excessive use of resources. Another level of complexity to cloud load scheduling is the distribution of resources among geographically dispersed data centers. To improve redundancy, l

关键词： scheduling algorithms

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A Non-Work Conserving Algorithm for Dynamic scheduling of Moldable Gang Tasks on Multicore Systems

A Non-Work Conserving Algorithm for Dynamic Scheduling of Mo...

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2024 International Conference on Electronics, Information, and Communication, ICEIC 2024

作者： Shimizu, Tomoki Nishikawa, Hiroki Kong, Xiangbo Tomiyama, Hiroyuki Graduate School of Science and Engineering Ritsumeikan University Japan Graduate School of Information Science and Technology Osaka University Japan Toyama Prefectural University Faculty of Engineering Japan

ISBN: (纸本)9798350371888

In this paper, we consider a dynamic scheduling algorithm for moldable gang tasks on multicore systems. While previous algorithms have been proposed, they predominantly adhere to work-conserving scheduling algorithms. In this paper, we introduce a non-work conserving dynamic scheduling algorithm aiming to reduce the makespan. Our proposed algorithm employs beam-search to perform non-work conserving scheduling. Through experiments, we demonstrate that under certain conditions, our method improves the makespan by 10% compared to existing methods. Furthermore, we discuss the variance in results based on the characteristics of the input tasks. © 2024 IEEE.

关键词： scheduling algorithms

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Efficient Microservice Deployment in the Edge-Cloud Networks With Policy-Gradient Reinforcement Learning

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IEEE ACCESS 2024年 12卷 133110-133124页

作者： Afachao, Kevin Abu-Mahfouz, Adnan M. Hanke Jr, Gerhard P. Univ Pretoria Dept Elect Elect & Comp Engn ZA-0028 Pretoria South Africa CSIR ZA-0083 Pretoria South Africa City Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China

The rise of user-centric design demands ubiquitous access to infrastructure and applications, facilitated by the Edge-Cloud network and microservices. However, efficiently managing resource allocation while orchestrating microservice placement in such dynamic environments presents a significant challenge. These challenges stem from the limited resources of edge devices, the need for low latency responses, and the potential for performance degradation due to service failures or inefficient deployments. This paper addresses the challenge of microservice placement in Edge-Cloud environments by proposing a novel Reinforcement Learning algorithm called Bi-Generic Advantage Actor-Critic for Microservice Placement Policy. This algorithm's ability to learn and adapt to the dynamic environment makes it well-suited for optimizing resource allocation and service placement decisions within the Edge-Cloud. We compare this algorithm against three baseline algorithms through simulations on a real-world dataset, evaluating performance metrics such as execution time, network usage, average migration delay, and energy consumption. The results demonstrate the superiority of the proposed method, with an 8% reduction in execution time, translating to faster response times for users. Additionally, it achieves a 4% decrease in network usage and a 2% decrease in energy consumption compared to the best-performing baseline. This research contributes by reproducing the Edge-Cloud environment, applying the novel Bi-Generic Advantage Actor-Critic technique, and demonstrating significant improvements over the state-of-the-art baseline algorithms in microservice placement and resource management within Edge-Cloud environments.

关键词： Edge computing microservices network optimization online placement scheduling algorithms reinforcement learning Edge computing microservices network optimization online placement scheduling algorithms reinforcement learning

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MP-ORAM: A Novel ORAM Design for Multicore Processor Systems

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IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING 2024年第4期21卷 3719-3733页

作者： Hussain, Sajid Guo, Hui Li, Tuo Parameswaran, Sri UNSW Sydney Sch Comp Sci & Engn Sydney NSW 2052 Australia MUST Dept Comp Syst Engn Mirpur 10250 Pakistan Univ Sydney Sch Elect & Comp Engn Sydney NSW 2050 Australia Inst Comp Technol CAS State Key Lab Processors Beijing 100190 Peoples R China Zhongguancun Lab Beijing 100081 Peoples R China

Security becomes increasingly critical in today's ubiquitous computing. One vulnerable part of a computing system is the bus between the processor chip and the external off-chip memory, where data transferred on the bus can be snooped. To protect data confidentiality, encryption is commonly used. However, encryption alone is not sufficient since the adversary can still find out useful information using the memory address trace. Oblivious RAM (ORAM) is a strong security measure to prevent such information leak. ORAM hides a true memory access in a round of random (dummy) accesses to the memory such that the data and addresses transferred over the memory buses look oblivious to the adversary. However, the existing ORAM designs often incur a hefty performance overhead, which greatly slows down the processor execution, especially for the multicore processor system where the potentially high memory access frequency from the multiple cores could make the impact of the performance overhead even more critical. To address this issue, we, for the first time, propose to process multiple memory access requests in a single round of dummy memory accesses. As such, we develop a novel ORAM design, called MP-ORAM, that targets the multicore system and is able to simultaneously handle a dynamic number of memory access requests to mitigate the performance overhead without compromising the obliviousness of the off-chip memory access trace. We have built a prototype for MP-ORAM and successfully integrated it into a RISCV-based multicore processor system. The whole system has also been implemented on a Xilinx Ultrascale+ ZCU102 FPGA board, with which we can effectively evaluate the performance of our design. Our evaluation, based on the SPLASH-2 benchmark suit, shows that MP-ORAM improves performance by 51-157% while only consuming up to 22% extra FPGA resources as compared to the baseline design. Furthermore, from the NIST randomness tests on the memory access traces generated by MP-ORA

关键词： Random access memory Multicore processing Hardware Process control Field programmable gate arrays Threat modeling scheduling algorithms ORAM memory data protection secure processor system multicore processor side-channel attacks

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Assessing the Value of Proactive Microgrid scheduling

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IEEE ACCESS 2022年 10卷 51062-51078页

作者： Spiegel, Michael H. Strasser, Thomas, I AIT Austrian Inst Technol Elect Energy Syst Ctr Energy A-1210 Vienna Austria TU Wien Inst Mech & Mechatron Fac Mech & Ind Engn A-1060 Vienna Austria

Microgrids and multi-microgrids are commonly installed to fulfill rising flexibility needs and to boost the system resilience by advanced fault mitigation capabilities. On top of a complex control architecture, proactive resilient scheduling optimizes the operation of such grids in advance. Although several scheduling algorithms include measures to limit the effects of faults, the impact of proactive scheduling on the system resilience is not widely assessed. This work presents an advanced simulation-based assessment method that includes an extended power flow formulation to consider low-level control and device capabilities even in islanded mode. A case study assesses resilience gains and costs of proactive scheduling based on multiple algorithms and an extensive set of operating conditions. It turned out that even on a suitable test grid that is specifically designed to challenge scheduling algorithms, a large share of the faults can already be handled by low-level controls without the need of considering them in scheduling. However, the remaining share of unhandled faults can be well influenced by advanced proactive scheduling algorithms and an appropriate resilience constraint formulation. Given the evaluation results, it can be supported that in less critical applications, scheduling focuses on economic aspects only without considering fault mitigation. Nevertheless, a detailed assessment is needed to justify the algorithmic choice and to improve the quality of resilient algorithms. The presented method adds a tool that can efficiently assess the value of proactive scheduling based on extensive simulations.

关键词： Microgrids scheduling algorithms Frequency control Optimal scheduling Load flow Job shop scheduling Costs Energy management power flow microgrids microgrid scheduling power system resilience proactive resilient scheduling

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A Dynamic Prioritization-based Collaborative Task scheduling Algorithm for Cloud-side-end of Distribution Networks 4

A Dynamic Prioritization-based Collaborative Task Scheduling...

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4th International Conference on Smart Grid and Energy Internet, SGEI 2024

作者： Wu, Zhengrong Li, Hua Yang, Yuxuan Liu, Yunhua Yin, Furong CHINA SOUTHERN POWER GRID Guangdong Guangzhou512000 China Co. Ltd China Southern Power Grid. Guangdong Guangzhou512000 China

ISBN: (纸本)9798350368314

Affected by resource configuration and task request characteristics, the rationality of distribution network task scheduling is directly related to its operating status. For this reason, a research on cloud-edge collaborative task scheduling algorithm for distribution network based on dynamic priority is proposed. On the basis of using a unified semantic data model to solve the problem of information interaction obstacles, through information modeling, a consistent model framework is provided for core information such as terminal device identification and operating status;after taking into account the inherent static priority of the task (reflecting the basic importance of tasks), it incorporates the consideration of the task's tolerance of deadlines, completes the dynamic priority division of tasks, and efficiently utilizes the limited computing resources of the object layer in the model while meeting the timeliness requirements of each task as much as possible. principles to perform task scheduling. In the test results, the load deviation is basically stable within 0.15, with the maximum value only 0.16;the ratio of cost to output is always lower than 0.84. Compared with the control group, it has significant advantages in stability and balance respectively. ©2024 IEEE.

关键词： scheduling algorithms

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