Task Scheduling Algorithm with Fault Tolerance for Cloud

Information and Communication Technology for Competitive Strategies

Nowadays, to a large extent, clients look at cloud not just as service provider but also as partner. So, they want cloud to deliver timely and accurate services. Cloud nodes must be reliable in order to provide quality of services as per the customer requirements. Further, physical size of high-performance computing environment is also increasing day by day. Larger the system, more failures are likely to occur that eventually results in the poor reliability of the system which is highly undesirable for the time-critical applications. To deal with the reliability, service provider must know the failure characteristics of the cloud computing nodes in order to better handle the failure using fault-tolerance-aware techniques at the time of scheduling the application tasks. Thus, in this paper, we presented the survey of fault-tolerance-aware techniques which are classified as proactive and reactive fault tolerance. This survey provides the foundation for the researchers to work in the area of fault-tolerance-aware scheduling in order to have better scheduling decisions with the aim to enhance the performance and reliability of application execution. Keywords Reliability ⋅ Fault tolerance ⋅ Virtualization 1 Introduction Cloud is an Internet-based computing paradigm that provides basic services as Infrastructure as a Service (IaaS), Software as a Service (SaaS), Platform as a Service (PaaS) [1]. Different types of cloud providers, i.e., public, private, or hybrids, are responsible for providing above services to user. Nowadays, usage of

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 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.

Lecture Notes in Electrical Engineering, 2015

In this paper, we introduce a task scheduling methodology to help systems to resiliently maintain their availability and reliability. Particularly, this method can quickly improve system recovery from failures as well as achieve an optimized performance while considering the customers' monetary cost and network condition. As comparison is made between our work and some similar existing approaches, apparently, it shows that ours has higher effectiveness and efficiency than the other ones.

2016

Cloud computing is the latest technology that involves distributed computation over the Internet. It meets the needs of users through sharing resources and using virtual technology. The workflow user applications refer to a set of tasks to be processed within the cloud environment. Scheduling algorithms have a lot to do with the efficiency of cloud computing environments through selection of suitable resources and assignment of workflows to them. Given the factors affecting their efficiency, these algorithms try to use resources optimally and increase the efficiency of this environment. The palbimm algorithm provides a scheduling method that meets the majority of the requirements of this environment and its users. In this article, we improved the efficiency of the algorithm by adding fault tolerance capability to it. Since this capability is used in parallel with task scheduling, it has no negative impact on the makespan. This is supported by simulation results in CloudSim environme...

International Journal of Grid and Distributed Computing

Cloud Computing is a business model that based on "pay as you go" principle. It is used to provide the IT services to the user in the flexible and dynamic manner with minimal management effort. The most important feature of the Cloud Computing is the ability to dynamically schedule the application on the best resource according to the load. According to the work in this paper, a task schedule on the Cloud environment has been proposed. The principle of the proposed algorithm is to allocate the incoming task on the best resource during the runtime of some tasks based on measuring the current situation of each resource with respect to its availability level according to its processing power, cost, and the number of running tasks to know its fitness to receive the incoming task, then choosing the best one to the incoming task. To evaluate the performance of the proposed algorithm, a comparative study has been done between this proposed algorithm, Round Ribbon (RR) algorithm, and Minimum Completion Time (MCT) algorithm. The experimental results show that the proposed algorithm outperforms the RR, and MCT algorithms by reducing make-span and the cost of the running tasks.

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.

Turkish Journal of Computer and Mathematics Education, 2021

Cloud computing is the requirement based on clients and provides many resources that aim to share it as a service through the internet. For optimal use, Cloud computing resources such as storage, application, and other services need managing and scheduling these services. The principal idea behind the scheduling is to minimize loss time, workload, and maximize throughput. So, the scheduling task is essential to achieve accuracy and correctness on task completion. This paper gives an idea about various task scheduling algorithms in the cloud computing environment used by researchers. Finally, many authors applied different parameters like completion time, throughput, and cost to evaluate the system.

Cloud Computing is the environment which can be used with minimum efficiency way that provides on-demand access of the network to a computing resources like networks, storage, applications, servers and the other services. There are many issues of cloud computing system which are discussed in this paper in brief. The main aim of this paper is to focus on fault tolerance in cloud computing and recover fault with less processing time. In this, when the node which is performing task moves from its original position then that tasks are assigned to other nodes. The major problem in this is task scheduling, if one slave node get failed the task allocated by master node will not get completed and fault occurred. In this paper, we will discuss about technique which helps to reduce fault tolerance of the system and increase performance of the system.

Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication - ICUIMC '14, 2014

Nowadays, thousands of servers in a cloud datacenter coordinate tasks to provide more reliable and highly available cloud computing services, especially in multi-task processing, as a crucial step to achieve high performance. Therefore, we need effective mechanisms to prepare for a failure of computing nodes. So far, a number of research studies have been carried out, trying to eliminate these problems, yet a little has been found efficient. In this paper, we present a cost-bandwidth based on scheduling algorithm that makes recovery from a saved state faster on heterogeneous computing environments. This algorithm not only considers the network bandwidth but also looks carefully at the monetary cost, which is paid by cloud customers (CCs) for utilizing cloud resources. In order to justify our proposal, we conducted numerous simulations and compared our method with existing ones. The results show that our approach can achieve higher performance, including recovery time in case of failure, while overhead in the case of no failure is a little in typical scenarios.

—In recent years cloud computing has been considered among superior technologies worldwide. The main reason is the services and sources provided the users by the clouds. In order to avoid over interactions of the servers and given the work volume and green computations, load balancing in cloud computing is of enormous importance requiring dynamic load distribution in a proportionate manner among the servers. Load balancing may reduce the used energy through avoiding over interaction between the nodes and virtual machines providing desired resource utilization. When a system fails, high costs are imposed on both server and customer, thus load balancing algorithm needs good fault tolerance. There are various techniques to increase fault tolerance. In this study task replication technique was used. To do so three fuzzy inference engines with an approach to fault tolerance for tasks prioritization, virtual prioritization and virtual machines as a goal for task replication were designed. Fuzzy method was selected because the question environment is uncertain and the parameters determination which is carried out by fuzzy method. In the proposed procedure by tasks and virtual priority, we could provide a proper work load distribution. The aim of this study was to present a novel strategy to improve load balancing for increasing fault tolerance and reducing energy consumption via ranking the tasks and virtual machines in cloud computing by fuzzy method.

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]

Cloud computing is a promising paradigm that provides users higher computation advantages in terms of cost, flexibility, and availability. Nevertheless, with potentially thousands of connected machines, faults become more frequent. Consequently, fault-tolerant load balancing becomes necessary in order to optimize resources utilization while ensuring the reliability of the system. Common fault tolerance techniques in cloud computing have been proposed in the literature. However, they suffer from several shortcomings: some fault tolerance techniques use checkpoint-recovery which increases the average waiting time and thus the mean response time. While other models rely on task replication which reduces the cloud's efficiency in terms of resource utilization under variable loads. To address these deficiencies, an efficient and adaptive fault tolerant algorithm for load balancing is proposed. Based on the CloudSim simulator, some series of test-bed scenarios are considered to assess the behavior of the proposed algorithm.

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.