Cost performance of QoS Driven task scheduling in cloud computing (original) (raw)

Optimization model for QoS based task scheduling in cloud computing environment

Indonesian Journal of Electrical Engineering and Computer Science, 2020

Shortest job first task scheduling algorithm allocates task based on the length of the task, i.e the task that will have small execution time will be scheduled first and the longer tasks will be executed later based on system availability. Min- Min algorithm will schedule short tasks parallel and long tasks will follow them. Short tasks will be executed until the system is free to schedule and execute longer tasks. Task Particle optimization model can be used for allocating the tasks in the network of cloud computing network by applying Quality of Service (QoS) to satisfy user’s needs. The tasks are categorized into different groups. Every one group contains the tasks with attributes (types of users and tasks, size and latency of the task). Once the task is allocated to a particular group, scheduler starts assigning these tasks to accessible services. The proposed optimization model includes Resource and load balancing Optimization, Non-linear objective function, Resource allocation...

OTS: An Optimal Tasks Scheduling Algorithm Based on QoS in Cloud Computing Network

International Journal of Advanced Trends in Computer Science and Engineering, 2019

Cloud Computing has emerged as a service model that offers online accessible resources to the clients. These resources contain storage, servers, and other applications and it provides security, flexibility, and scalability. In Max-Min algorithm where the large tasks have their priority to be scheduled first this leads small tasks to stay longer in the queue until all huge tasks finished their execution. This study presents an optimal tasks scheduling algorithm by enhancing Max-Min algorithm. The simulation results have proven that the Proposed Optimal Tasks Scheduling OTS completes tasks execution with less execution time and higher performance compared with Max-Min and TS algorithms. The overall results show that the performance of the proposed algorithm achieved 6% better in terms of time execution compared of both of Max-Min and TS algorithms

QoS Driven Task Scheduling in Cloud Computing

International Journal of Computer Applications Technology and Research, 2013

Cloud computing systems promise to offer pay per use, on demand computing services to users worldwide. Recently, there has been a dramatic increase in the demand for delivering services to a large number of users, so they need to offer differentiate d services to users and meet their expected quality requirements. Most of scheduling schemes proceeding nowadays have no QoS (Quality of Service) differentiation, which is necessary for Cloud Computing service operation. As a cloud must provide services to many users at the same time and different users have different QoS requirements, the scheduling schemes should be developed having different QoS requirements. So, this paper explores various methods of task scheduling done in cloud computing. Real-time applications play a significant role in cloud environment. We have examine the particular scheduling algorithms for real-time tasks, that is, priority-based strategies.The purpose of this paper is to discuss the fixed priority preemptive task scheduling algorithms in cloud computing for improving the QoS parameters.

A Comparative Analysis of Scheduling Algorithms affecting QoS in Cloud Environment

2015

Cloud computing is no longer a buzzword. It has become a common name in the filed of IT and business but there is a lot of scope for better performance and more profit for providers.It deals with several kind of virtualized resources, hence scheduling place an important role in deciding the performace. There are two types of scheduling one for the task and other for allocation of virtual machines. These scheduling schemes affect the Quality of Service of cloud to a great extent. In this paper nine factors are identified affecting QoS and based on these factors exiting algorithms are compared. The result clearly shows that an optimized algorithm for better results in Cloud Computing is needed.

COST BASED TASK SCHEDULING ALGORITHM IN CLOUD COMPUTING

Cloud computing provides various significant services to the user including software as service, Infrastructure as a service. User submits the tasks to acquire various services provided by Cloud. In Cloud computing environment these task are scheduled. There are two levels of scheduling which is done in Cloud Computing. One is called platform level where task from different users are scheduled on Virtual Machines for proper execution, another one is called infrastructure level where different virtual machines are scheduled on physical machines provided in Data Centres. This paper elaborates an efficient cost based task scheduling algorithm. The problem of processing " m " jobs to " n " virtual machines in Cloud Computing is addressed here where number of task is greater than the number of service provider. As day by day numbers of user are increasing, problem of efficiently allocation of different jobs has become a great issue. This algorithm efficiently allocates different tasks to increase the performance of Cloud computing.

An Analysis of Task Scheduling Algorithm in Cloud Environment

International Journal of Advanced Research in Computer Science, 2019

Cloud Computing has become a well-liked computing paradigm that has gained huge attention in delivering o Task scheduling in cloud computing is a crucial issue that has been well researched and lots of algorithms are developed for identical. However, the goal of most of those algorithms is to attenuate the general completion time (i.e., makespan) while not trying into step price of the service (referred as budget). Moreover, several of them are of Task scheduling algorithms has been mentioned and compared on the premise of assorted planning p throughput, makespan, resource utilization, quality of service, energy consumption, interval and value.

A Scheduling Technique for Qos Sensitive Jobs in Cloud

2014

The aim of this paper is to introduce a new algorithm for QOS based resource scheduling. Cloud is a type of parallel and distributed system consisting of a collection of inter-connected and virtualized computers that are dynamically provisioned and presented as one or more unified computing resources based on service-level agreements established through negotiation between the service provider and consumers. Resource scheduling, which is a part of resource management is an important process that takes place in storage cloud which falls under IaaS cloud, so that the available resources may be properly allocated to the requesting tasks in a best fit manner so that no resources are wasted. In this paper a new algorithm is designed for task scheduling to minimize memory wastage since our task is to store some files in the storage cloud, task completion time and task response time. The task manager checks all the virtual machine and assigns the task to proper virtual machine which will h...

QoS Based Efficient Resource Allocation and Scheduling in Cloud Computing

International Journal of Technology and Human Interaction, 2019

The Cloud environment is a large pool of virtually available resources that perform thousands of computational operations in real time for resource provisioning. Allocation and scheduling are two major pillars of said provisioning with quality of service (QoS). This involves complex modules such as: identification of task requirement, availability of resource, allocation decision, and scheduling operation. In the present scenario, it is intricate to manage cloud resources, as Service provider aims to provide resources to users on productive cost and time. In proposed research article, an optimized technique for efficient resource allocation and scheduling is presented. The proposed policy used heuristic based, ant colony optimization (ACO) for well-ordered allocation. The suggested algorithm implementation done using simulation, shows better results in terms of cost, time and utilization as compared to other algorithms.

Efficient Task Scheduling Strategy Towards Qos Aware Optimal Resource Utilization in Cloud Computing

2015

QoS (Quality of Service) aware task scheduling in cloud computing is a continuous practice due to the divergent scope of user needs. Henceforth the current research is moving in a direction to find optimal solutions for efficient task scheduling towards QoS aware resource utilization in cloud workflow management. Much of the existing solutions are specific to one or two QoS factors mainly task completion and bandwidth. According to the real-time practices, the QoS assessment by one or two factors is impractical. Moreover much of the existing approaches are delivering the computational complexity as O(n 2 ), which is due to the magnification of the increment in number of tasks due to overwhelmed users and their requirements. In this context here we devised an explorative statistical approach, which is based on metrics called resource optimal value ( ropt ) and coupling between tasks ( cbt ), which enables to assess the optimal order of tasks to utilize desired cloud resource. The oth...

A SURVEY ON TASK SCHEDULING MODEL IN CLOUD COMPUTING USING OPTIMIZATION TECHNIQUE

Task scheduling is the most important part of cloud computing. To optimize the system, the tasks have to be scheduled in an efficient manner. A scheduling algorithm must be efficient in a way that it improves the performance of the system. The primary goal of task scheduling algorithm is to reduce the makespan and to increase resource utilization. In this paper a task scheduling model using various algorithms has been analyzed. These algorithms take into consideration of various parameters and improve the system.