Abstract:Divisible load theory has become a popular area of research during the past two decades. Based on divisible load theory the computations and communications can be divided into some arbitrarily independent parts and each part can be processed independently by a processor. Existing divisible load scheduling algorithms do not consider any priority for allocating fraction of load. In some situation the fractions of load must be allocated based on some priorities. In this paper we propose a multi criteria divisible… Show more
“…This system does not consider the availability of resources or the weight of tasks. Shamsollah et al [15] proposed a system based on a multi-criteria algorithm for scheduling server load. Shamsollah et al [16] proposed a system based on priority for performing divisible load scheduling that employs analytical hierarchy process.…”
Cloud computing is required by modern technology. Task scheduling and resource allocation are important aspects of cloud computing. This paper proposes a heuristic approach that combines the modified analytic hierarchy process (MAHP), bandwidth aware divisible scheduling (BATS) + BAR optimization, longest expected processing time preemption (LEPT), and divide-and-conquer methods to perform task scheduling and resource allocation. In this approach, each task is processed before its actual allocation to cloud resources using a MAHP process. The resources are allocated using the combined BATS + BAR optimization method, which considers the bandwidth and load of the cloud resources as constraints. In addition, the proposed system preempts resource intensive tasks using LEPT preemption. The divide-and-conquer approach improves the proposed system, as is proven experimentally through comparison with the existing BATS and improved differential evolution algorithm (IDEA) frameworks when turnaround time and response time are used as performance metrics.
“…This system does not consider the availability of resources or the weight of tasks. Shamsollah et al [15] proposed a system based on a multi-criteria algorithm for scheduling server load. Shamsollah et al [16] proposed a system based on priority for performing divisible load scheduling that employs analytical hierarchy process.…”
Cloud computing is required by modern technology. Task scheduling and resource allocation are important aspects of cloud computing. This paper proposes a heuristic approach that combines the modified analytic hierarchy process (MAHP), bandwidth aware divisible scheduling (BATS) + BAR optimization, longest expected processing time preemption (LEPT), and divide-and-conquer methods to perform task scheduling and resource allocation. In this approach, each task is processed before its actual allocation to cloud resources using a MAHP process. The resources are allocated using the combined BATS + BAR optimization method, which considers the bandwidth and load of the cloud resources as constraints. In addition, the proposed system preempts resource intensive tasks using LEPT preemption. The divide-and-conquer approach improves the proposed system, as is proven experimentally through comparison with the existing BATS and improved differential evolution algorithm (IDEA) frameworks when turnaround time and response time are used as performance metrics.
“…Shamsollah et al discussed about the system based on a multi-criteria algorithm for scheduling server load. The scheduling process depends on the priority for performing divisible load scheduling that employs an analytical hierarchy process [19][20][21].…”
In an organization, resource allocation to a request is a complex task. Traditionally, resource allocation is done through manually with high time consumption. Similarly, collision is occurring for allocating a single resource to multiple requests. Thus, leads to complex problems and slow-down the working process. The existing resource allocation technique, allocate resources continuously to a specific request and omit another request. This kind of allocation technique also leads to lots of critical issues. That is the non-allocated process never gets a resource. To overcome these issues, the Round Robin based Resource allocation and Utilization technique is proposed in this work. The Round Robin technique allocates resources to the request in an efficient with equal priority. Similarly, the proposed technique reduces collision and takes less time for mapping a resource with a request. The experimental results shows improved accuracy than the traditional resource allocation technique.
“…It is assumed that initially amount of load is Figure:3-Gantt chart-like timing diagrams for divisible load [1] Of load held by the originator p 0 . The originator p 0 does not do any computation.…”
Cloud computing relates to the bunch of services that are provided to the customers on lease, by the servers located at different sites over the internet. The servers have pool of resources that can be scaled up and down on the basis of requirement. This results into communication and computation over the network. Divisible load theory has become popular during the past two decades. Based on divisible load theory the computations and communications can be divided into some arbitrarily independent parts and each part can be processed independently by a processor. The fraction of load must be allocated the processors based on some priorities. Analytical Hierarchy Process(AHP) is a multi-criteria based technique used for assigning priorities to the processors. Existing approach can handle the priority of processors using Eigen Value method of Analytical Hierarchy Process. The proposed model works on Geometric mean method of Analytical Hierarchy Process in order to improve parameters such as makespan, average response time and average waiting time.
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