A Study on Task Scheduling Algorithms in Cloud Computing

Cloud computing has increased its popularity due to which it is been used in various sectors. Now it has come to light and is in demand because of amelioration in technology. Many applications are submitted to the data centers, and services are given as pay-per-use basis. As there is an increase in the client demands, the workload is increased, and as there are limited resources, workload is moved to different data centers in order to handle the client demands on as-you-pay basis. Hence, scheduling the increasing demand of workload in the cloud environments is highly necessary. In this paper, we propose three different task-scheduling algorithms such as Minimum-Level Priority Queue (MLPQ), MIN-Median, Mean-MIN-MAX which aims to minimize the makespan with maximum utilization of cloud. The results of our proposed algorithms are also compared with some existing algorithms such as Cloud List Scheduling (CLS) and Minimum Completion Cloud (MCC) Scheduling.

International Journal of Scientific & Technology Research, 2020

Now a days, Cloud computing has become an significant and most popular computing model that usually supports on demand servic es. Cloud Computing provides its services on pay-as-you-go basis .By using cloud computing resources expeditiously and by reducing in managing time and cost and increasing the outcome of the project is the main idea of cloud service provider. Therefore, using effective cloud scheduling algorithms is still main concern in cloud computing. Task scheduling is a pivotal part in the field of the cloud environment. In task scheduling user requests for certain task, then tasks are scheduled to certain resources at a specific exemplification of time. Basically task scheduling mainly f ocuses to diminish the make span and lengthen the resource utilization. Task scheduling is an Non Polynomial-Complete problem. There are lots of subsisting trail-and-error techniques for task scheduling till now but more amelioration and rectification is needed for better execution and ...

International Journal of Advanced Computer Science and Applications

The enhanced form of client-server, cluster and grid computing is termed as Cloud Computing. The cloud users can virtually access the resources over the internet. Task submitted by cloud users are responsible for efficiency and performance of cloud computing services. One of the most essential factors which increase the efficiency and performance of cloud environment by maximizing the resource utilization is termed as Task Scheduling. This paper deals with the survey of different scheduling algorithms used in cloud providers. Different scheduling algorithms are available to achieve the quality of service, performance and minimize execution time. Task scheduling is an essential downside within the cloud computing that has to be optimized by combining different parameter. This paper explains the comparison of several job scheduling techniques with respect to several parameters, like response time, load balance, execution time and makespan of job to find the best and efficient task scheduling algorithm under these parameters. The comparison of scheduling algorithms is also discussed in tabular form in this paper which helps in finding the best algorithms.

international journal for research in applied science and engineering technology ijraset, 2020

The on-demand availability of computer system resources such as data storage and computing power is cloud computing. Scheduling is the method of allocating jobs onto resources in time. Scheduling increases the efficiency and performance of cloud environment by maximizing the resource utilization. This scheduling process has to respect constraints given by the jobs and the cloud providers. Ordering the tasks by scheduler along with maintaining the balance between Quality of Service (QoS), fairness and efficiency of jobs is difficult. Scheduling algorithms are designed and implemented considering some parameters like latency, cost, priority, etc. The aim of this paper is a study of various types of job scheduling algorithms that provide efficient cloud services.

The cloud computing is the bunch of computing resources which are delivered as a service to the customer or multiple tenants over the internet. The task scheduling is the very important part of a cloud computing. The task scheduling mainly focuses on enhancing the efficient utilization of resources and hence reduction in task completion time. Task scheduling is used to distribute specific tasks to certain resources at a particular time. Different approaches have been presented to overcome the problems of task scheduling. Task scheduling improves the efficient utilization of resource and yields less response time. Task scheduling helps to reduce the completion time of the tasks. The scheduling algorithm is presented in this paper, which schedules the tasks based on their length and deadline. Results are compared with traditional algorithms and comparative analysis shows a reduction in makespan and average waiting time.

2022

The provider of the service today is expected to serve many users. The increasing number of requests for services from the users to the providers has caused the providers of the service to have to offer scalable solutions. In the cloud computing environment, various scheduling algorithms have been proposed, such as the (SJF) and (FCFS) algorithms. Using cloud computing, the paper seeks to improve the shortest job scheduling algorithm. In tasks scheduling (TS), makepan and response time are the most important parameters. In order to reduce the length of time to complete the last task (Makespan), decrease the average response time, and maximize resource utilization, we present a Shortest Job First algorithm. This method consists of two functions, one is the calculation of the average task length, and the other is load balancing between virtual machines. Sending the longest tasks to the fastest machine is one of the benefits of SJF.

With the contempo slump and the immutable crush to deliver more services at a lower cost. Delivery model offers lower cost, and can make quick construction services. IT economics are changing rapidly, and large companies, in particular, looking for new ways to secure capital at a lower cost to maintain the viability of the company. Task scheduling problems are first class related to the overall efficiency of cloud computing facilities. Most developed algorithms for automation planning approach in one parameter of quality of service (QoS). However, if we consider more than one QoS parameter then the problem becomes more challenging. To address the problem, we need to introduce a scheduling strategy for multi-workflows with multiple QoS constrained for cloud computing. We need to introduce an optimized algorithm for task scheduling in cloud computing and its implementation. Furthermore, Load Balancing is a method to distribute workload across one or more servers, network interfaces, hard drives, or other computing resources. Use these components with the load balancing, on the one chamber, grow well in redundancy.

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.

International Journal of Computer Applications, 2014

Cloud computing is one of the hottest word in IT world and it having huge demand in these days. Some big IT companies like Google, IBM, Microsoft, Amazon, Yahoo and others develop cloud computing systems and products related to it for customers. But still customers are having difficulties for adopting the cloud computing, that is only because of the security issues exist in it. Cloud Computing is collection of large number of resources like hardware and software that are provided by the cloud providers to the consumers as a service over the internet. In cloud computing every task requires to be executed by available resource to achieve minimum waiting time, reduce makespan, best performance and maximum utilization of resources. To achieve these requirements we proposed an efficient scheduling algorithm which will work effectively to provide better result as compared with the traditional scheduling approaches. For this CloudSim framework is used to simulate the proposed algorithm under various conditions and presented the better results with reduced the waiting time and processing time with optimum resource utilization and minimum overhead for the same.

International Journal for Research in Applied Science and Engineering Technology -IJRASET, 2020

The increase of cloud computing is so exponential that it offers facts connection between special structures and devices. Due to this boom in connectivity and rapid utilization cloud network desires a statistics grid or computing grid comprising of different type of processing gadgets to perform the query this is despatched to the cloud network. This work provides a review on optimized undertaking scheduling in cloud computing environment. The main element of cloud computing is offering desirable response time for end users, that affords a primary impediment in achievement of cloud computing. All components should coordinate to deal with this mission. This can be handled through a suitable Task scheduling algorithm. So, there's a need of efficient mission scheduling method in implementation of cloud computing surroundings. Due to boom in era and increase in range of statistics facilities the venture dealing with ability of each information centres is foremost concern. Keywords: Cloud computing, task scheduling, Make span, Minimum/Maximum Execution Time, Minimum/Maximum Completion Time, and Load balancing. I. INTRODUCTION Today's age is the age of technology. Technology is growing at a totally speedy charge, every and the whole lot is getting connected. Cloud computing has attracted a whole lot interest these days from each enterprise and academia. However, the size and surprisingly dynamic nature of cloud utility imposes enormous new demanding situations to useful resource management. Thus, efficient aid scheduling schemes is still a task. As a new computing version, cloud computing has converted the IT industry with its developing utility and popularization. Though cloud computing gives considerable opportunities, those are many undertaking faces in its improvement process. This research, introduces Task Scheduling strategies and Load Balancing techniques to improve the cloud assets. With the immense growing business areas, distributed computing has all the earmarks of being the main alternative to meet their extending needs. A cloud supplier initially builds up a processing framework called cloud, where a couple of virtual machines are interconnected through this; the provider shapes the undertaking of the customers. Distributed computing is certifiably not a respectful model to offer the customer to a typical pool of configurable processing assets that can be promptly given and discharged low care effort or administration will consider the particular errand planning [7] of better execution registering approaches. Cloud load adjusting server allocates the heap at the period of growing the couple of CPUs or memories for their assets to scale up with the extended solicitations. This administration is in a general sense associated for business undertaking demands. In cloud, the heap balancer is a host to screen the heap and circulate the heap to VMs by using booking draws near. The heap balancer is used for two significant techniques, one is generally to help the availability of cloud assets and the other is alternatively to propel execution. Asset provisioning framework is used to give best bring about burden adjusting and unwavering quality on distributed computing. It is planned for rendering steady administrations among the distinctive VMs. There are a few sorts of calculations that show up in the writing. Fig 1: Scheduling Model in Cloud Computing [1]