CLUSTER BASED TASK SCHEDULING ALGORITHM IN CLOUD COMPUTING

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1 Volume 118 No , ISSN: (on-line version) url: ijpam.eu CLUSTER BASED TASK SCHEDULING ALGORITHM IN CLOUD COMPUTING R.Vijay Sai, M.Lavanya, K.Chakrapani, S.Saravanan School of Computing, SASTRA Deemed University, India ABSTRACT This paper proposes the optimization of grouped task scheduling algorithm that is used to schedule tasks in cloud computing network by applying quality of service (QoS) to satisfy user s needs. After adding tasks into the right category, scheduling is done. The task with the lowest execution time will be scheduled first. The improved grouped task scheduling algorithm uses TS algorithm and Reliable Task Allocation (RTA) algorithm to achieve minimum latency and minimum completion time. In cluster based task scheduling algorithm, the tasks are grouped into five categories. The first step is to decide which category is to be scheduled first. Then the second step is to schedule the tasks within each category based on the priority. Keywords: Cloud computing, GTS Algorithm, Reliable Task Scheduling Algorithm, minimum completion time. 1. INTRODUCTION The increasing demands of users is met by Cloud Computing by providing services like shared computing, storage resources and also gives information to users [7][6]. In cloud computing environment, the requirement is to schedule the existing tasks with the given restrains. QoS according to the user s needs to be applied and there must be balance between the QoS and equality among the tasks [8]. There are numerous algorithms to improve the cloud computing requirements. Among the algorithms, one is a task scheduling algorithm that calculates priority to each task based on its attributes and then schedules tasks according to the increased priority. This paper proposes a new algorithm named cluster based task scheduling (CBTS) algorithm which is based on the methods of improved cost-based algorithm, TS algorithm and Reliable task scheduling (RTA) algorithm. Cluster Based Task Scheduling (CBTS) algorithm uses the same way to calculate priority to tasks in TS algorithm to calculate priority to each category. However, cluster based task scheduling algorithm uses the method of RTA algorithm instead of Min-Min algorithm to schedule tasks inside each category. 2. RELATED WORKS Improved cost-based scheduling algorithm used in cloud computing is to achieve minimum makes span and to reduce the total cost [3]. Minimum makes span is achieved by distributing the tasks into categories depending on their priorities. 3197

2 Grouped Task Scheduling (GTS) algorithm used in cloud computing uses both TS algorithm and Min- Min algorithm to achieve both minimum latency and execution time of the tasks [1]. This also uses the idea of the grouping tasks from cost-based algorithm. GTS algorithm has five categories (Urgent User& Task, Urgent Task, Urgent User, Long Task and Normal Task). Task scheduling (TS) algorithm is used in cloud computing based on the Quality of Service (QoS) [2].This algorithm determines the priority of the tasks according to the four attributes of the tasks (User Type, Priority Type, Task Length, Task Latency). Using the four attributes TS algorithm calculates the priorities of the tasks. The tasks are sorted according to the priority and scheduled onto services in which the tasks are completed earlier. This algorithm results in reduced latency of the tasks. Min-Min algorithm used in cloud computing depends on the execution time for scheduling tasks [4]. Tasks having minimum execution time will be scheduled first and have delay for long tasks. This algorithm produces minimum make span compared to TS algorithm. Modified Max-Min algorithm mainly based on the execution time for task scheduling and not on the completion time [5]. Modified Max-Min algorithm uses the the concept of basic max-min algorithm. 3. PROPOSED CBTS A low latency rate is achieved by TS algorithm when compared with the RTA algorithm whereas the RTA algorithm records a lower execution time when compared with the TS algorithm. Hence, the algorithm proposed in this paper aims to attain low latency with minimum execution time. The idea in improved cost-based algorithm of grouped tasks is used to implement QoS given in TS algorithm and the tasks are scheduled using the RTA algorithm. Based on its attributes, the tasks are divided into categories in the Improved GTS. Each category consists of tasks with tasks which are similar. Weights are assigned to the attributes of the tasks according to which the categories are to be scheduled in TS algorithm. The scheduling is done only for the categories and not the tasks. The category which is scheduled first will consist of tasks with attributes which have a higher priority than the other categories. In the selected category, the task scheduled first would be the one with the minimum execution time. MCT Matrix (Initialized minimum completion time) is a matrix that stores the estimation of Expected completion duration of all tasks on all services. The number of rows in MCT matrix is equal to the number of tasks(n) and the number of columns is equal to the number of services(m) and MCT (i,j) is the time that service j needs to complete the task i. MCT matrix is loaded with random numbers, but the type of task whether it is long or normal should be considered. The mapping list matrix is a matrix that saves the number of tasks, the number of assigned services to these tasks and the execution time that the services require to complete these tasks. Mapping list matrix is considered as the output of the algorithm. It is used to calculate the performance measure needed to evaluate the algorithm. 3.1 ALGORITHM Input: Tasks with attributes (UserType, TaskType, TaskLength, Latency) 1. The tasks are classified based on its attributes under one of the Five categories. 3198

3 2. The tasks with more instructions are given higher priority within each category. 3. An MCT matrix is calculated which stores the expected completion time of all the tasks under the given services. 4. RTA algorithm allocates the tasks to the services under which the lowest completition time is given in the MCT matrix. 5. The makespan time is calculated from the MCT matrix for each category. 6. The total completion time is the sum of the makespan time of tasks allocated to the services under the different categories. 4. EXPERIMENTAL ANALYSIS As explained earlier, the Cluster Based Task Scheduling (CBTS) algorithm uses the Reliable Task scheduling algorithm to schedule tasks within the selected category whilst it uses the TS algorithm to decide which category should be scheduled first. The CBTS algorithm compares its performance with the existing GTS algorithm. The same attributes as that of the GTS algorithm is used in the CBTS algorithm as well such as UserType, TaskType, TaskLength and Latency. The results obtained from the comparison will be accurate when the same parameters are used. The total completion time will be the performance metric for comparing the existing and proposed model. Table 1: Comparison of Results Algorithm Number of services used Completion time GTS Algorithm 4 42 CBTS Algorithm The above table (Table 1) shows that with the same number of tasks and services used, the completion time is better for the proposed CBTS algorithm. 3199

4 Hence the following graph (Fig 1) shows that the proposed CBTS algorithm shows better result than the GTS algorithm GTS CBTS Fig 1: Comparison of GTS and CBTS algorithm based on completion time 5. CONCLUSION Cloud computing is a promising technology for computing platforms to provide easier access to remote computational resources that are locally limited. High system throughput is expected to be achieved and computing resources are allocated to various applications. The objective of this paper is to establish an algorithm which reduces the total completion time of the tasks allocated to a set of services when compared to other algorithms. CBTS algorithm schedules tasks with given attributes to the set services based on higher priority. Java language is used for the implementation of the task allocation processes. The Experimental and Comparative analysis shows that the CBTS algorithm is more efficient over the existing GTS algorithm for reducing the total completion time. 6. REFERENCES [1] Gamal El Din Hassan Ali H, Imane Aly Saroit, Amira Mohamed Kotb et al., Grouped tasks scheduling algorithm based on QoS in cloud computing network, Egyptian Informatics J, 2016 [2] Wu Xiaonian, Deng Mengqing, Zhang Runlian, Zeng Bing, Zhou Shengyuan, A task scheduling algorithm based on QoS-driven in cloud computing,international conference on information technology and quantitative management, China, [3] Selvarani S, Sudha Sadhasivam G. Improved cost-based algorithm for task scheduling in cloud computing. In: International conference. IEEE;

5 [4] Liu Gang, Li Jing, Xu Jianchao. In: Proceedings of the 2012 international conference of modern computer science and applications, Zhenyu Du; p [5] O.Elzeki, M. Reshad, M. Elsoud, Improved max-min algorithm in cloud computing, International Journal of Computer Applications,vol 50 (12) (2012)pages [6] Mell, Peter and Grance, Tim, The NIST definition of cloud computing, National Institute of Standards and Technology, 2009,vol53, pages50, Mell 2009 [7] Tilak Sujit, Patil Dipti. A survey of various scheduling algorithms in cloud environment. Int J Eng Invent 2012;1(September):36 9. [8]Abdullah Monir, Othman Mohamed, Cost-based multi-qos job scheduling using divisible load theory in cloud computing. In:International conference on computational science, ICCS;

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