Containers have emerged as the most promising lightweight virtualization technology in providing cloud services due to its flexible deployment, portability, and scalability especially in micro-services, smart vehicles...
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Containers have emerged as the most promising lightweight virtualization technology in providing cloud services due to its flexible deployment, portability, and scalability especially in micro-services, smart vehicles, IoTs, and fog/edge computing. An important and vital role in cloud container services is played by the scheduler's component to optimize performance and reduce cost due to the diverse nature of the workload and cloud resources. Despite the immense traction of containers in cloud computing, there is no comprehensive survey that covers container scheduling techniques. In this timely survey, we investi-gate the landscape of the state-of-the-art container scheduling techniques aiming to inspire more research work in this active area of research. The survey is structured around classifying the scheduling techniques into four categories based on the type of optimization algorithm employed to generate the schedule namely mathematical modeling, heuristics, meta-heuristics and machine learning. Then for each class of scheduling algorithms, we analyze and identify key benefits and pitfalls, together with key challenges of the available techniques based on the performance metrics. Finally, this paper high-lights fertile future research opportunities to realize the full potential of the emergent container technology.(c) 2021 The Authors. Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).
This paper presents a runtime system for reconfigurable accelerators that supports elastic management: it enables effective sharing of accelerator resources across multiple applications. For each application, this run...
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ISBN:
(纸本)9781479942930
This paper presents a runtime system for reconfigurable accelerators that supports elastic management: it enables effective sharing of accelerator resources across multiple applications. For each application, this runtime system allocates an appropriate amount of resources to satisfy its quality-of-service requirements, while minimising the overall execution time for a collection of applications. The effectiveness of this runtime system is due to a set of scheduling algorithms and strategies customised for different types of workloads. We demonstrate our approach by implementing a dynamic Monte Carlo bond options pricing design.
With the increase in the amount of data processing the importance of distributed computational systems is rising. The efficiency of the task scheduling algorithms used in distributed computational systems is one of th...
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ISBN:
(纸本)9781479959969
With the increase in the amount of data processing the importance of distributed computational systems is rising. The efficiency of the task scheduling algorithms used in distributed computational systems is one of the major challenges for the architecture of such systems. This paper presents and introduces a new task scheduling algorithm suggested for volunteer computing systems. It is based on an assessment of host performance, which is obtained from the characteristics of hosts participating in BOINC, the most widely used representative of volunteer computing systems. This paper also describes the simulation process and the achieved results of the proposed algorithm as compared with the original FCFS BOINC scheduling strategy.
Rate-guaranteed scheduling protocols ensure that packets from each input flow are forwarded at a rate no less than the rate reserved by the flow. WFQ is the classical example. Many of these protocols, including WFQ, p...
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ISBN:
(纸本)9781479937806
Rate-guaranteed scheduling protocols ensure that packets from each input flow are forwarded at a rate no less than the rate reserved by the flow. WFQ is the classical example. Many of these protocols, including WFQ, provide both rate and fairness guarantees. In particular, they distribute unused capacity among among the flows in proportion to the reserved rate of each flow. In earlier work, we presented a scheduling algorithm that distributes unused capacity to flows whose reserved rate is the least. However, the per-packet complexity of this algorithm, known as rate-equalization fairness, is linear in the number of flows. Here, we present an algorithm that approximates rate-equalization fairness, but with only logarithmic complexity per packet.
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