Advance reservation, co-allocation and pricing of network and computational resources in grids

Depoorter, Wim; Vanmechelen, Kurt; Broeckhove, J.

doi:10.1016/j.future.2014.07.004

Cited by 11 publications

(4 citation statements)

References 15 publications

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“…A reliable hybrid model of Genetic Algorithm (GA) and Bacterial Foraging Optimization Algorithm (BFOA) is proposed by [1] and [18]. The tasks are assigned to suitable resource to minimize makespan, cost and throughput.…”

Section: Related Workmentioning

confidence: 99%

“…In a grid environment, various resources are geographically distributed and used for meeting the demand of high-performance computing. Due to dynamicity and availability issue, discovery [1], selection and allocation of resource [2] is challenging task. Broadly every resource allocation technique follows three phases [3]- Resource discovery-In this phase, a list is made of all resources which are accessible for executing the user request.…”

Section: Introductionmentioning

confidence: 99%

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An Improved Resource Allocation Model for Grid Computing Environment

Shukla¹,

Kumar²,

Singh³

2019

IJIES

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Grid is collection of heterogeneous resources which are highly dynamic and unpredictable in nature. Various resource allocation techniques are used for effective use of resources. Tasks are submitted with constraints (cost, deadline, etc.) to improve the performance of distributed environment. Based on resource availability, several tasks select the same resource to achieve minimum execution cost. Therefore, an effective scheduling is required to execute tasks on the same resource to reduce average waiting time of tasks. In this paper, an extensive survey of resource allocation techniques is done based on several parameters. A resource allocation and task scheduling mechanism is proposed to optimize cost and average waiting time of heterogeneous tasks. The uniqueness of the proposed model is that it makes task execution schedule and sends calculated data to resource manager before actual task execution for reducing average waiting time of tasks. Further, we validate the effectiveness of the proposed model using GridSim by considering random values of task and resources. Experimental results show that the proposed model provides up to 37% reduction in average waiting time than existing approaches under various environment conditions.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Improved Resource Allocation Model for Grid Computing Environment

Shukla¹,

Kumar²,

Singh³

2019

IJIES

View full text Add to dashboard Cite

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“…Advance network resource reservation has applications for both wide-area and grid networks and has been studied frequently in recent years [9,10,11,12,13,14,15]. Current research mostly focuses on optical networks in combination with wavelength division multiplexing [1].…”

Section: Advance Resource Reservationmentioning

confidence: 99%

Design and evaluation of a dual dynamic adaptive reservation approach in media production networks

Barshan

Moens

Volckaert

et al. 2017

Journal of Network and Computer Applications

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Media production networks require an ecient collaboration between geographically distributed actors and oer predictable workloads, making it possible to exploit this predictability and use advance bandwidth reservation services to achieve greater bandwidth utilization and service guarantees. To oer reliable reservations, the incorporation of fault-tolerance related features in bandwidth reservation strategies is a necessity, although this imposes a waste of capacity and extra performance overhead. As a rst provisional stage to oer a robust reservation system, deploying protection mechanisms ensures that the reservations remain valid when the system is in operation. To maximally utilize the network, and to ensure there is a quick response in a dynamic network environment, constant monitoring and optimization is needed. In this article, we propose an ecient dual optimization approach consisting of two consecutive processes. First, a schedule is produced by a resilient advance reservation algorithm. Then, the generated schedule is continually updated over time using a runtime adaptation approach in order to be capable of dynamically adapting the network to changing conditions and mitigating the side eects of provisioned reliability. This step uses the interconnecting network links' leftover capacity, resulting in an increased performance both in steady and unsteady network conditions. Our evaluations show that in failure-prone environments, the proposed approach leads to signicant increase in the success rate of admitted requests, up to 6.77 times, compared to the resilient advance reservation algorithms.

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“…Resource pricing is an important aspect in resource allocation. In [34], authors mention Commodity Market which means that the sellers set the price for merchandise and the buyers pay money to get it. The price is predetermined by the seller and does not change over time based on supply-demand relationship.…”

Section: Related Workmentioning

confidence: 99%

A Dynamic Pricing Reverse Auction-Based Resource Allocation Mechanism in Cloud Workflow Systems

Ding

Liu

et al. 2016

Scientific Programming

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Market-oriented reverse auction is an efficient and cost-effective method for resource allocation in cloud workflow systems since it can dynamically allocate resources depending on the supply-demand relationship of the cloud market. However, during the auction the price of cloud resource is usually fixed, and the current resource allocation mechanisms cannot adapt to the changeable market properly which results in the low efficiency of resource utilization. To address such a problem, a dynamic pricing reverse auction-based resource allocation mechanism is proposed. During the auction, resource providers can change prices according to the trading situation so that our novel mechanism can increase the chances of making a deal and improve efficiency of resource utilization. In addition, resource providers can improve their competitiveness in the market by lowering prices, and thus users can obtain cheaper resources in shorter time which would decrease monetary cost and completion time for workflow execution. Experiments with different situations and problem sizes are conducted for dynamic pricing-based allocation mechanism (DPAM) on resource utilization and the measurement of Time⁎Cost (TC). The results show that our DPAM can outperform its representative in resource utilization, monetary cost, and completion time and also obtain the optimal price reduction rates.

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Advance reservation, co-allocation and pricing of network and computational resources in grids

Cited by 11 publications

References 15 publications

An Improved Resource Allocation Model for Grid Computing Environment

An Improved Resource Allocation Model for Grid Computing Environment

Design and evaluation of a dual dynamic adaptive reservation approach in media production networks

A Dynamic Pricing Reverse Auction-Based Resource Allocation Mechanism in Cloud Workflow Systems

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