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Learning scheduling Policies for Co-Located Workloads in Cloud Datacenters

IEEE TRANSACTIONS ON CLOUD COMPUTING 2023年第4期11卷 3725-3736页

作者： Li, Jialun Xiao, Danyang Yao, Jieqian Long, Yujie Wu, Weigang Sun Yat Sen Univ Sch Comp Sci & Engn Guangzhou 510275 Peoples R China

Co-location, which deploys long running applications and batch-processing applications in the same computing cluster, has become a promising way to improve resource utility for large cloud datacenters. However, co-location brings huge challenges to task scheduling because different types of workloads may affect each other. Existing works on task scheduling rarely focus on the scenario of co-location. This article presents Co-ScheRRL, a scheduling algorithm delicately designed for co-located workloads. Co-ScheRRL consists of two major mechanisms: i) a self-attention encoding mechanism which encodes and represents states of the computing cluster as a set of embedding feature vectors;ii) a deep reinforcement learning (DRL) relational reasoning mechanism which calculates and compares different scheduling actions under different co-located workloads pattern via DRL feedback reward signals based on these feature vectors. Our two mechanisms can tackle complicatedly and dynamically varying behaviors of co-located workloads. With the help of these two mechanisms, Co-ScheRRL is able to construct high-quality scheduling policies. Trace-driven simulation demonstrates that Co-ScheRRL outperforms existing scheduling algorithms in terms of makespan by more than 38.4% and throughput by more than 166.7%.

关键词： scheduling Task analysis Optimal scheduling scheduling algorithms Cognition Cloud computing Runtime Cloud datacenter co-location resource management task scheduling deep reinforcement learning

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Optimal Broadcast scheduling Algorithm for a Multi-AUV Acoustic Communication Network

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IEEE-ACM TRANSACTIONS ON NETWORKING 2023年第5期31卷 2058-2069页

作者： Qiu, Tianyou Li, Yiping Feng, Xisheng Univ Sci & Technol China Sch Informat Sci & Technol Hefei 230026 Anhui Peoples R China Chinese Acad Sci Shenyang Inst Automat State Key Lab Robot Shenyang 110016 Peoples R China Chinese Acad Sci Inst Robot & Intelligent Mfg Shenyang 110169 Peoples R China Chinese Acad Sci Shenyang Inst Automat Inst Robot & Intelli gent Mfg State Key Lab Robot Shenyang 110169 Peoples R China Key Lab Marine Robot Shenyang 110169 Liaoning Peoples R China

In systems of multiple autonomous underwater vehicles (AUVs), to achieve cooperative operation and cluster intelligence, information is often disseminated via broadcasting. However, due to the long propagation delay and slow transmission rate of underwater acoustic communication, traditional broadcast scheduling algorithms require a long broadcast period to avoid signal collision. To improve the channel utilization rate as much as possible and improve the update rate for broadcast information, we propose an optimal broadcast scheduling algorithm. This algorithm uses the location information of AUVs to adjust the broadcast sequence and broadcast schedule, to achieve the shortest possible collision-free broadcast period in the broadcast network for the current node distribution. Simulation experiments show that this algorithm can achieve a broadcast period much shorter than that of traditional TDMA and higher channel utilization without signal collision. In addition, the simulations prove the feasibility of applying the algorithm in an actual MAC protocol.

关键词： Protocols scheduling algorithms Media Access Protocol Time division multiple access Schedules Underwater acoustics Robots Multi-AUV acoustic communication network broadcast scheduling algorithm TDMA protocol

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Near-Optimal scheduling for Crowdsourced Transit System With Skip-Stop Tactic

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2023年第11期35卷 11668-11680页

作者： Li, Hanlin Wu, Xiaowei Hou, U. Leong Kou, Kun Pang Univ Macau State Key Lab Internet Things Smart City Taipa Macao Peoples R China Univ Macau Ctr Data Sci Taipa Macao Peoples R China Univ Macau Dept Civil & Environm Engn Taipa Macao Peoples R China

Efficient bus scheduling is a crucial component for the improvement of public transit services. Without systematic optimization and efficient shift arrangement, the bus scheduling system may suffer from poor vehicle loading rate or crowd onboard, resulting in wasted energy and passenger dissatisfaction. In this paper, we consider a crowdsourced bus service system (on a fixed route) that receives user requests as input and computes the scheduling of buses with flexible departure time and skip-stop to minimize the travel time of users. We first show that the general problem of computing the optimal scheduling is NP-hard. On the other hand, for the case when skip-stop is not adopted, we propose the Optimized Departure Time (ODT) algorithm that computes optimal scheduling. Our algorithm is built on an innovative reduction of the problem to some variants of the k-clustering problem and an efficient application of dynamic programming. On top of ODT, we further improve the effectiveness of the solution by utilizing the power of skip-stop tactic, named ODTS. Our experimental results demonstrate that ODT and ODTS dramatically outperform existing algorithms for the bus scheduling problem in terms of effectiveness and efficiency. Moreover, the solutions given by ODTS are very close to the optimum.

关键词： Schedules Optimal scheduling Costs Heuristic algorithms scheduling algorithms QR codes Mobile applications Near-optimal scheduling skip-stop

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HATS: HetTask scheduling

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IEEE TRANSACTIONS ON CLOUD COMPUTING 2023年第2期11卷 2071-2083页

作者： Koohi, Sina Zangbari Hamid, Nor Asilah Wati Abdul Othman, Mohamed Ibragimov, Gafurjan Univ Putra Malaysia Fac Comp Sci & Informat Technol Dept Commun Technol & Network Seri Kembangan 43400 Selangor Malaysia Univ Putra Malaysia Inst Math Res Lab Computat Sci & Math Phys Seri Kembangan 43400 Selangor Malaysia Univ Putra Malaysia Dept Math Fac Sci Seri Kembangan 43400 Selangor Malaysia

To handle task execution, modern supercomputers employ thousands (or millions) of processors. In such supercomputers, task scheduling has a meaningful impression on system performance. To improve efficiency, task scheduling algorithms aim to decrease the volume of communication and the number of message exchanges. These efforts, however, result in other bottlenecks, such as high-link congestion. In addition, the heterogeneity of processors and networks is another major challenge for schedulers. This paper presents a new algorithm for scheduling called Heterogeneity-Aware Task scheduling (HATS). The proposed algorithm adopts an updated multi-level hyper-graph partitioning approach. It describes a new method of aggregation in the coarsening step that helps to accurately coarsen the hyper-graph of the task model. The Raccoon Optimization algorithm is then used in the initial partitioning phase, and in the un-coarsening phase, a novel refinement procedure optimises the initial partitions. The experiments on this approach showed that, compared to the other well-known algorithms, the proposed method offers better schedules with lower communication volume and imbalance ratio in a shorter time.

关键词： Task analysis Partitioning algorithms Topology Program processors Supercomputers scheduling scheduling algorithms Heterogeneous multilevel partitioning optimization parallel application task scheduling

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Flow Ordering Problem for Time-Triggered Traffic in the scheduling of Time-Sensitive Networking

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IEEE COMMUNICATIONS LETTERS 2023年第5期27卷 1367-1371页

作者： Chen, Zhuoxing Lu, Yiqin Wang, Haihan Qin, Jiancheng Wang, Meng South China Univ Technol SCUT Sch Elect & Informat Engn Guangzhou 510640 Peoples R China

Time-Sensitive Networking (TSN) can ensure deterministic communications for time-critical traffic, which plays a crucial role in various real-time scenarios. In this letter, we propose and study a neglected problem in TSN, named flow ordering problem, which provides a new perspective on improving the scheduling of large-scale TSN. Specifically, we formulate the flow ordering problem, look into its theoretical basis, and prove this problem is NP-hard. Furthermore, we propose a hybrid search algorithm to provide an optimized scheduling order. Simulation results verify the significant impact of the flow ordering problem on TSN scheduling and the effectiveness of our algorithm.

关键词： Job shop scheduling scheduling algorithms Metaheuristics Genetic algorithms Costs Schedules Mathematical models Deterministic communications time-sensitive networking (TSN) scheduling NP-hard

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An IFWA-BSA Based Approach for Task scheduling in Cloud Computing

Journal of ICT Standardization

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Journal of ICT Standardization 2023年第1期11卷 45-66页

作者： Li, Xiaoxia School of Artificial Intelligence and Big Data Zibo Vocational Institute Shandong Zibo255000 China

Establishing an efficient cloud computing task scheduling model is the object of many scholars' research. In view of the low scheduling efficiency in cloud computing task scheduling, we propose a cloud computing task scheduling algorithm based on the fusion of the Fireworks Algorithm and Bird Swarm Algorithm (IFWA-BSA). Firstly, we describe the cloud computing task scheduling model based on time and cost constraint functions, secondly, we use chaotic backward learning and Coasean distribution for optimization in FWA initialization;we set thresholds for the radius of core fireworks and non-core fireworks for optimization;we filter the IFWA individuals after each iteration by BSA algorithm, and finally, we use the IFWA-BSA algorithm is used in cloud computing task scheduling model to solve the optimal solution. In the simulation experiments, IFWA-BSA has obvious advantages over ACO, PSO and FWA in the comparison of execution time and consumption cost indexes, which reduces the scheduling time and cost of cloud computing. © 2023 River Publishers.

关键词： scheduling algorithms

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Application of hybrid genetic algorithm in large traffic scheduling in SDN architecture

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International Journal of Wireless and Mobile Computing 2023年第3-4期24卷 341-351页

作者： Feng, Yuhan School of Information Engineering Xinyang Agriculture and Forestry University Henan Province Xinyang China

The scale of data centres and network traffic at the core of modern information service infrastructure is increasing. At present, there are many problems in network traffic management under the new architecture, such as too many large flow conflicts and low flexibility. A large flow scheduling mechanism for SDN architecture based on hybrid genetic algorithm is proposed. Based on the analysis of data centre network topology and architecture module, this paper focuses on HGSAFS traffic scheduling algorithm, which uses GA algorithm to make up for the problems of SA algorithm in global search ability and local solution. The four traffic scheduling algorithms have the highest average network delay when the network load is 90%, and the four traffic scheduling algorithms have the highest average network throughput. The highest average network delay algorithm is GFE algorithm, with a value of 119.3 ms, while the highest average network throughput is HGSAFS algorithm, with a value of 746.3 Mbps. The proposed SDN architecture scheduling algorithm has feasibility in large traffic scheduling. © 2023 Inderscience Enterprises Ltd.

关键词： scheduling algorithms

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Near-Optimal Packet scheduling in Multihop Networks with End-to-End Deadline Constraints

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PROCEEDINGS OF THE ACM ON MEASUREMENT AND ANALYSIS OF COMPUTING SYSTEMS 2023年第3期7卷 1-32页

作者： Tsanikidis, Christos Ghaderi, Javad Columbia Univ New York NY 10025 USA

scheduling packets with end-to-end deadline constraints in multihop networks is an important problem that has been notoriously difficult to tackle. Recently, there has been progress on this problem in the worst-case traffic setting, with the objective of maximizing the number of packets delivered within their deadlines. Specifically, the proposed algorithms were shown to achieve Omega(1/log(L)) fraction of the optimal objective value if the minimum link capacity in the network is C-min = Omega( log(L)), where L is the maximum length of a packet's route in the network (which is bounded by the packet's maximum deadline). However, such guarantees can be quite pessimistic due to the strict worst-case traffic assumption and may not accurately reflect real-world settings. In this work, we aim to address this limitation by exploring whether it is possible to design algorithms that achieve a constant fraction of the optimal value while relaxing the worst-case traffic assumption. We provide a positive answer by demonstrating that in stochastic traffic settings, such as i.i.d. packet arrivals, near-optimal, (1 - epsilon)-approximation algorithms can be designed if C-min = Omega (log(L/epsilon)epsilon(2)). To the best of our knowledge, this is the first result that shows this problem can be solved near-optimally under nontrivial assumptions on traffic and link capacity. We further present extended simulations using real network traces with non-stationary traffic, which demonstrate that our algorithms outperform worst-case-based algorithms in practical settings.

关键词： scheduling algorithms Approximation algorithms Multihop traffic Deadline scheduling

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PDU-set scheduling Algorithm for XR Traffic in Multi-Service 5G-Advanced Networks 59

PDU-set Scheduling Algorithm for XR Traffic in Multi-Service...

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59th Annual IEEE International Conference on Communications (IEEE ICC)

作者： Paymard, Pouria Paris, Stefano Amiri, Abolfazl Kolding, Troels E. Moya, Fernando Sanchez Pedersen, Klaus I. Aalborg Univ Dept Elect Syst Aalborg Denmark Nokia Tampere Finland

ISBN: (纸本)9781728190549

This paper investigates a dynamic packet scheduling algorithm designed to enhance the eXtended Reality (XR) capacity of fifth-generation (5G)-Advanced networks with multiple cells, users, and services. The scheduler exploits the newly defined protocol data unit (PDU)-set information for XR traffic flows to enhance its quality-of-service awareness. To evaluate the performance of the proposed solution, advanced dynamic system-level simulations are conducted. The findings reveal that the proposed scheduler offers a notable improvement in increasing XR capacity up to 45%, while keeping the same enhanced mobile broadband (eMBB) cell throughput as compared to the well-known baseline schedulers.

关键词： scheduling algorithms

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Research on private desktop cloud platform based on random scheduling algorithm and load balancing scheduling algorithm

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International Journal of Wireless and Mobile Computing 2023年第1期25卷 37-46页

作者： Zhou, Dunkai Zhou, Jinsong Institute of Foreign Languages Hubei University of Technology Hubei Province Wuhan China School of Computing Hubei University of Technology Hubei Province Wuhan China

The research starts from the private desktop cloud, and realises the dynamic reception of computing services, the query of computing status and the task stealing based on the real-time load status by improving and optimising the scheduling module. The advantages of its performance are analysed by comparing the experimental results with the actual application results. The results show that the improved scheduling algorithm performs better than other algorithms under two different processor parallel conditions of 10 and 40, and achieves small floating differences in CPU utilisation, memory utilisation, sending traffic and receiving traffic in practical application, which can better balance tasks and perform calculations more efficiently. It can be seen that the improved scheduling algorithm has better performance, can meet the design requirements of the overall framework of the private cloud desktop and has the advantages of scientific scheduling, efficient scheduling, and load balancing in task scheduling. © 2023 Inderscience Enterprises Ltd.

关键词： scheduling algorithms

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