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检索条件"主题词=scheduling algorithms"

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Hybrid Grey Wolf and Particle Swarm Optimized (HGW-PSO) scheduling in Containerized Cloud Computing Environment

Hybrid Grey Wolf and Particle Swarm Optimized (HGW-PSO) Sche...

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Emerging Technology (INCET), International Conference for

作者： S.M. Udhaya sankar Martin Joel Rathnam Aswanth Babu Harikumar G J Keerthi Nadh Department of Computer Science and Engineering(Cyber Security) R.M.K College of Engineering and Technology Chennai Tamilnadu India Department of Electronics and Communication Engineering Sri Sairam college of Engineering Bengaluru Karnataka India

ISBN: (数字)9798350361155

ISBN: (纸本)9798350361162

The concept of containerization consists of encapsulating applications with their libraries with the help of operating system level virtualization, ensuring they are separated from other processes on the same machine. Containers gained popularity in several data centers due to their lightweight nature and simplified deployment. Application containerization technology is a fundamental technology that enables the deployment of numerous containers on a single physical node. A single physical node has the capability to offer several services to users. The adoption of microservice architecture is on the rise as it offers several benefits over monolithic designs, such as simplified deployment, enhanced versatility, and improved accessibility. The rise of containerization has significantly increased the significance of microservices, enhancing their scalability and portability. Many researchers have developed theories and solutions for the microservice container scheduling problem, yet limits remain. The algorithm's tendency to become stuck in local optimization and its slow optimal solution search are examples. In this work we present a proposal for grey wolf and particle swarm optimized (GW-PSO) scheduling in a Containerized Cloud Computing Environment. During the first phase of the search, the GW's global search can direct the PSO away from local optima, preventing early convergence. In the last phases of the search, the PSO can improve GW search along the Pareto optimum frontier. The research findings demonstrate, in comparison to the other 3 methods, the algorithm achieves a 19.06% reduction in network transmission cost, a 15.57% improvement in load balancing performance, and a 6.67% enhancement in service stability.

关键词： Cloud computing scheduling algorithms Scalability Microservice architectures Containers Resource management Proposals

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Pre-emptive scheduling of on-line real time services with task migration for cloud computing

Pre-emptive scheduling of on-line real time services with ta...

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International Conference on Pattern Recognition, Informatics and Medical Engineering

作者： R. Santhosh T. Ravichandran Department of CSE Karpagam University Coimbatore India Hindusthan Institute of Technology Coimbatore India

This paper presents a new scheduling approach to focus on providing a solution for online scheduling problem of real-time tasks using “Infrastructure as a Service” model offered by cloud computing. The real time tasks are scheduled pre-emptively with the intent of maximizing the total utility and efficiency. In traditional approach, the task is scheduled non- pre-emptively with two different types of Time Utility Functions (TUFs) - a profit time utility function and a penalty time utility function. The task with highest expected gain is executed. When a new task arrives with highest priority then it cannot be taken for execution until it completes the currently running task. Therefore the higher priority task is waiting for a longer time. This scheduling method sensibly aborts the task when it misses its deadline. Note that, before a task is aborted, it consumes system resources including network bandwidth, storage space and processing power. This leads to affect the overall system performance and response time of a task. In our approach, a preemptive online scheduling with task migration algorithm for cloud computing environment is proposed in order to minimize the response time and to improve the efficiency of the tasks. Whenever a task misses its deadline, it will be migrated the task to another virtual machine. This improves the overall system performance and maximizes the total utility. Our simulation results outperform the traditional scheduling algorithms such as the Earliest Deadline First (EDF) and an earlier scheduling approach based on the similar model.

关键词： Real-time systems Cloud computing Algorithm design and analysis scheduling algorithms Time factors scheduling

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ELITE: Near-Optimal Heuristics for Coflow scheduling

ELITE: Near-Optimal Heuristics for Coflow Scheduling

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IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGRID)

作者： Afaf Arfaoui Rachid Elazouzi Francesco De Pellegrini Cé dric Richier Jeremie Leguay LIA University of Avignon France NEST Research Group ENSEM Hassan II University of Casablanca Morocco Huawei Technologies France Research Center

Reducing Coflow Completion Time (CCT) has a significant impact on data-intensive application performance in datacenter networks. An efficient allocation of network resources allows for accelerating the computations to be performed. In this paper, we propose a new scheduler, named ELITE, to minimize the Weighted Coflow Completion Time (WCCT). Our scheduling algorithm is a 2-approximation of the optimal and the rate allocation can achieve a 4-approximation as long as the scheduling priority is respected. We also present a new rate allocation procedure, named RACO, that shows near-optimal performance when combined with our scheduling algorithms. We also propose a low complexity online scheduler, named LSPRT to attain near-optimal performance in online setting. With extensive simulations, we demonstrate the effectiveness of our algorithms by measuring the performance gain of ELITE and LSPRT over previous solutions in the literature. In particular, ELITE and LSPRT perform about 44 % better than Varys, while Sincronia achieves only 32 % against Varys.

关键词： Social networking (online) scheduling algorithms Heuristic algorithms Optimal scheduling Performance gain Gain measurement Particle measurements

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Introducing PSO for Optimal Packet scheduling of Collective Communication

Introducing PSO for Optimal Packet Scheduling of Collective ...

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International Symposium on Computing and Networking (CANDAR)

作者： Takashi Yokota Kanemitsu Ootsu Takeshi Ohkawa Department of Information Systems Science Utsunomiya University Tochigia Japan

ISBN: (纸本)9781509026562

Interconnection network is an inevitable component that is responsible to the system's communication capability. It affects the system-level performance as well as the physical and logical structure of the parallel system. Many studies are reported to enhance the interconnection network technology, however, we have to further discuss remaining issues for building large-scale systems. One of the most important issues is congestion management. In an interconnection network, packets are transferred simultaneously, and the packets interfere to each other on the network. Congestion arises as a result of the interference among packets. Its fast spreading speed degrades communication performance drastically and it continues for long time. Thus, we should appropriately control the network to suppress the congested situation for maintaining the maximum performance. Many studies address the problem and present effective methods, however, the maximal performance in an ideal situation is not sufficiently clarified. Solving the ideal performance is, in general, an NP-hard problem. This paper introduces particle swarm optimization (PSO) method to overcome the problem. In this paper, we first formalize the optimization problem suitable for the PSO method and present three PSO methods for avoiding local minima. We furthermore introduce some non-PSO methods for comparison. Our preliminary evaluation results reveal high potentials of the PSO method.

关键词： scheduling algorithms Particle swarm optimization Multiprocessor interconnection Optimization Schedules Large-scale systems Ports (Computers)

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Delay-aware Cellular Traffic scheduling with Deep Reinforcement Learning

Delay-aware Cellular Traffic Scheduling with Deep Reinforcem...

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GLOBECOM 2020 - 2020 IEEE Global Communications Conference

作者： Ticao Zhang Shuyi Shen Shiwen Mao Gee-Kung Chang Auburn University Auburn AL School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA

ISBN: (数字)9781728182988

ISBN: (纸本)9781728182995

Radio access network (RAN) in 5G is expected to satisfy the stringent delay requirements of a variety of applications. The packet scheduler plays an important role by allocating spectrum resources to user equipments (UEs) at each transmit time interval (TTI). In this paper, we show that optimal scheduling is a challenging combinatorial optimization problem, which is hard to solve within the channel coherence time with conventional optimization methods. Rule-based scheduling methods, on the other hand, are hard to adapt to the time-varying wireless channel conditions and various data request patterns of UEs. Recently, integrating artificial intelligence (AI) into wireless networks has drawn great interest from both academia and industry. In this paper, we incorporate deep reinforcement learning (DRL) into the design of cellular packet scheduling. A delay-aware cell traffic scheduling algorithm is developed to map the observed system state to scheduling decision. Due to the huge state space, a recurrent neural network (RNN) is utilized to approximate the optimal action-policy function. Different from conventional rule-based scheduling methods, the proposed scheme can learn from the interactions with the environment and adaptively choosing the best scheduling decision at each TTI. Simulation results show that the DRL-based packet scheduling can achieve the lowest average delay compared with several conventional approaches. Meanwhile, the UEs' average queue lengths can also be significantly reduced. The developed method also exhibits great potential in real-time scheduling in delay-sensitive scenarios.

关键词： Delays scheduling algorithms Job shop scheduling Optimal scheduling Wireless communication Resource management Recurrent neural networks

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An efficient task scheduling algorithm for heterogeneous multi-cloud environment

An efficient task scheduling algorithm for heterogeneous mul...

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International Conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： Sanjaya K. Panda Prasanta K. Jana Department of Computer Science and Engineering Indian School of Mines Dhanbad India

ISBN: (纸本)9781479930814

Cloud Computing has been adopted as one of the growing technologies in the business and research community. However, due to significant client demands, there is a need to overflow some workloads to other data centers as no data center has unlimited resources. The workload sharing provides even more flexible and cheaper resources to complete the applications submitted to the data centers. However, scheduling workloads in multi-cloud environment is challenging as the data centers have resources which are heterogeneous in nature. In this paper, we propose a task scheduling algorithm in a heterogeneous multi-cloud environment. The algorithm is based on two popular algorithms namely, Min-Min and Max-Min. We perform extensive experiments on some benchmark and synthetic data sets and compare the results with two existing multi-cloud scheduling algorithms. The results show that the proposed algorithm outperforms both the algorithms in terms of makespan and average cloud utilization.

关键词： scheduling Coordinate measuring machines Benchmark testing scheduling algorithms Data models

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An Improved Upper-Bound Algorithm for Non-preemptive Task scheduling

An Improved Upper-Bound Algorithm for Non-preemptive Task Sc...

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International Symposium on Symbolic and Numeric algorithms for Scientific Computing (SYNASC)

作者： Stefan Andrei Albert M. K. Cheng Vlad Radulescu Department of Computer Science Lamar University Beaumont TX USA Computer Science Department University of Houston Houston TX USA Department of Computer Science A. I. Cuza University of Iaşi Iaşi Romania

One of the core problems in real-time systems, finding a feasible schedule for a certain task set, is subject to alternative solutions given the various system constraints. While preemptive scheduling has benefited from a large number of significant results, the non-preemptive case has still room for improvement. This paper extends our previous results regarding the minimum number of processors required for getting a feasible schedule and the possible ways of improving the well known traditional scheduling algorithms in the case of non-preemptive, single-instance, multiprocessor systems. The improvements refer to handling the situations when the already determined minimum number of processors proves insufficient, and also to extending an existing technique which allows the algorithm to overcome certain stalling situations.

关键词： Program processors Schedules scheduling Upper bound scheduling algorithms Real-time systems

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Comparative Analysis of Latest Task scheduling Techniques in Cloud Computing environment

Comparative Analysis of Latest Task Scheduling Techniques in...

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International Conference on Computing Methodologies and Communication (ICCMC)

作者： B Anushree V M Arul Xavier Department of Computer Sciences Technology Karunya University Coimbatore

Cloud computing is one of the most important services which is utilized by people all over the globe. It provides direct access to several computing components or services whenever required by the users over the internet such as servers, applications, storage, network. Task scheduling is a vital part in the field of the cloud environment. User requests i.e tasks are scheduled to certain resources at a specific instance of time. It mainly focuses to minimize the makespan and maximize the resource utilization. It is an NP-Complete problem. There are numerous existing heuristic techniques for task scheduling till now but more enhancement and modification is needed for better performance and to increase the efficiency of task scheduling. In this paper, few latest task scheduling techniques have been reviewed and their performances were analyzed in terms of various metrics.

关键词： scheduling Task analysis Cloud computing Genetic algorithms Heuristic algorithms scheduling algorithms

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A dual-kernel scheduling scheme based on TrustZone

A dual-kernel scheduling scheme based on TrustZone

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Electronic Information Engineering and Computer Communication (EIECC), International Conference on

作者： Jintao Qiu Department of Basic Software East China Institute of Computing Technology China

ISBN: (数字)9798331534622

ISBN: (纸本)9798331534639

With the continuous improvement of the performance of embedded hardware platforms, in the fields of aviation and automotive electronics, an important development direction is to concentrate functions including real-time control, information visualization and human-computer interaction into the same hardware platform. Because of its preemptive design and customized drivers for real-time scenarios, RTOS can meet the requirements of real-time control for hard real-time. However, in terms of the functions related to user experience such as human-computer interaction, the mainstream general operating system (GPOS) such as Windows and Linux is obviously a more suitable choice. In TZDKS architecture, with the help of TrustZone technology under AArch64 architecture, RTOS and GPOS are integrated into the same SoC platform, which can run real-time tasks and common tasks at the same time. However, the Idle scheduling scheme of TZDKS makes the responsiveness of GPOS completely sacrificed when the real-time kernel load is heavy. To solve this problem, this paper uses Sporadic Server algorithm to replace Idle scheduling scheme, and significantly improves the response capability of GPOS while ensuring hard real-time tasks in RTOS.

关键词： Human computer interaction Visualization scheduling algorithms Computer architecture Real-time systems Hardware User experience scheduling Servers Kernel

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Schedulability and optimization analysis for non-preemptive static priority scheduling based on task utilization and blocking factors

Schedulability and optimization analysis for non-preemptive ...

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Euromicro Conference on Real-Time Systems

作者： Georg Brüggen Jian-Jia Chen Wen-Hung Huang Department of Informatics TU Dortmund University Germany

For real time task sets, allowing preemption is often considered to be important to ensure the schedulability, as it allows high-priority tasks to be allocated to the processor nearly immediately. However, preemptive scheduling also introduces some additional overhead and may not be allowed for some hardware components, which motivates the needs of non-preemptive or limited-preemptive scheduling. We present a safe sufficient schedulability test for non-preemptive (NP) fixed priority scheduling that can verify the schedulability for Deadline Monotonic (DM-NP) and Rate Monotonic (RM-NP) scheduling in linear time, if task orders according to priority and period are given. This test leads to a better upper bound on the speedup factor for DM-NP and RM-NP in comparison to Earliest Deadline First (EDF-NP) than previously known, closing the gab between lower and upper bound. We improve our test, resulting in interesting properties of the blocking time that allow to determine schedulability by only considering the schedulability of the preemptive case if some conditions are met. Furthermore, we present a utilization bound for RM-NP, based on the ratio γ > 0 of the upper bound of the maximum blocking time to the execution time, significantly improving previous results.

关键词： Optimal scheduling Upper bound scheduling algorithms Real-time systems Dynamic scheduling Time factors

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