Task Scheduling Algorithms in Cloud Computing: A Review

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.

2020

Cloud computing is a controlled model that defines computing services, in which data and resources are retrieved from the cloud service provider through the internet with the help of web-based tools and functions. It is a collection of resources and services shared together and are provided to the users on pay-as-you-go model. An efficient task scheduling algorithm is required, for mapping the resources with tasks. A Heuristic based algorithm is used to attain the optimal or near optimal solution of task scheduling in the cloud environment. In this paper, various types of task scheduling algorithms in cloud computing have been discussed.

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.

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 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.

IJANA, 2025

Cloud computing has become a current and popular technology in recent years and has come across us in every field. In fact, the fact that it comes across us in every field shows why this technology is popular. Today, many devices do not have sufficient resources despite having an internet connection. What we mean by resources here is that the processing ability, storage space and energy source are not sufficient. This is where cloud computing comes into play to solve these problems. Devices with low resources can also access large data and the high complexity calculations it requires. We can define cloud computing as an internet-based computing system that provides adaptive computing resources, storage areas, different applications and servers without the need for interaction with the service provider and with minimum management cost. Systems and commercial service services that provide services related to Cloud Computing and open source systems such as OpenStack have been researched and CloudSim has been used for research studies. CloudSim is a simulator that includes the infrastructure and services of open source cloud computing. It was developed in Java by CLOUDS Lab. Java is an object-oriented language, which provides researchers with ease of use in this sense. We use task scheduling algorithms in CloudSim with 30 inputs and their process performance was examined.

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.

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.

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.

IJRET, 2013

Cloud computing is known as a provider of dynamic services using very large scalable and virtualized resources over the Internet. Due to novelty of cloud computing field, there is no many standard task scheduling algorithm used in cloud environment. Especially that in cloud, there is a high communication cost that prevents well known task schedulers to be applied in large scale distributed environment. Today, researchers attempt to build job scheduling algorithms that are compatible and applicable in Cloud Computing environment Job scheduling is most important task in cloud computing environment because user have to pay for resources used based upon time. Hence efficient utilization of resources must be important and for that scheduling plays a vital role to get maximum benefit from the resources. In this paper we are studying various scheduling algorithm and issues related to them in cloud computing.

International journal of engineering research and technology, 2018

Cloud Computing is one of the emerging technology based upon on demand pay per use model. It is a platform where various services like applications, bandwidth and data are provided to its users using Internet. The main objective of Job Scheduling Algorithms in Cloud Computing is to optimize the resource allocation and utilization to meet user requirements and for cloud service providers it is the efficient use of resources and thus attaining maximum profit. All this leads us right to the requirement of Job Scheduling in Cloud Computing. Scheduling is the method of deciding how to provide resources amongst the various available tasks or processes so as to achieve the maximum throughput efficiently. In this paper various Job Scheduling algorithms have been presented on the basis of different parameters which provide efficient cloud services.

International Journal of Innovative Research in Science, Engineering and Technology, 2014

Cloud computing is a computing paradigm where applications, data, memory, bandwidth and IT services are provided over the Internet. Cloud computing is based on pay per usage model. Cloud service providers provide virtual resources to the cloud users. The ultimate goal of cloud service providers is to gain maximum profit and use resources efficiently. Scheduling refers to a set of policies to control the order of work to be performed by a system. Task scheduling plays vital role in cloud computing system to manage heavy load or traffic. Efficient task scheduling improves resource utilization, response time and also meets user requirements. In this paper, Survey on various task scheduling methods for parallel workloads is made.

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]

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.

Ciência e Natura

Cloud computing is the latest distributed technology providing a rich environment of dynamically shared resources through virtualization, which can fulfill the requirements of users by allocating resources to programs. Any program in a cloud environment is delivered by workflows which are a series of interlinked tasks to accomplish a goal. One of the most important tasks in cloud computing is correct mapping of tasks onto resources. It is essential to schedule processes in distributed systems such as cloud, since it leaves a tremendous impact on the system performance. This is done by scheduling algorithms. Therefore, it is crucial to present and adopt an efficient algorithm in the cloud environment. This article attempted to examine the parameters effective in the efficiency of scheduling algorithms including deadline, cost constraint, balanced loading, power consumption and fault tolerance. Additionally, the performances of several algorithms were briefly discussed.