AN EFFICIENT TASK SCHEDULING ALGORITHM TO OPTIMIZE RELIABILITY IN MOBILE COMPUTING

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1 AN EFFICIENT TASK SCHEDULING ALGORITHM TO OPTIMIZE RELIABILITY IN MOBILE COMPUTING Faizul Navi Khan, Kapil Govil Teerthanker Mahaveer University, Moradabad, U.P., India ABSTRACT Mobile computing can be describes as a way of transmission of data, via a computing device, without having a wired connection. Mobile computing also includes a number of technologies and devices such as wireless network, notebook, Smart phones, tablets and Personal Digital Assistant (PDAs) etc. Various applications are running under the Mobile Computing domain can be accessible by the users regardless their locations to fulfill their day to day business or personal needs. Multiple users send their requests from the different locations and these requests execute on available resources and send back to their originating point in reliable manner. The problem of task scheduling in Mobile Computing is always critical in order to execute a numbers of tasks on different processors to achieve maximum level of optimization. Efficient task scheduling is always a main concern to enhance the performance of application in Mobile Computing. In Mobile Computing multiple processors are joined together that acts as single system and it handles the various tasks requests in such environments. This research paper demonstrates the problem of task scheduling where numbers of tasks m are greater than the available processes n (m>n) through a task scheduling algorithm that will provide optimal solution in order to achieve optimal reliability to the task. The Scheduling algorithm describe in this research paper is based on the consideration of processing reliability of the task to the processors. KEYWORDS: Mobile Computing, Performance, Processing reliability, Task scheduling I. INTRODUCTION Mobile computing is precisely to permit users and applications to be as effective as possible in this environment of uncertain connectivity, without changes to the manner in which they operate. Mobile data communication has become a very important and rapidly evolving technology as it allows users to transmit data from remote locations to other remote or fixed locations. An application running Mobile Computing network is accessible on every hosts and it looks like a combinations of multiple tasks, these tasks executes on available processor in Mobile Computing in distributed manner. And the tasks are processed and information is provided to the requester hosts in form of the output. Different users have the different computing needs. In Mobile Computing multiple processors act as a single system that parallel receives multiple requests and execute these requests within the available resources. This research paper present the design of task scheduling algorithm that would solve task scheduling problem in Mobile Computing where the number of tasks m will execute on numbers of processors n (where m>n) in heterogeneous environment. Multiple tasks from the different mobile host will come and arrange in an ordered queue and will execute in First In First Out (FIFO) order one by one. In case the new task will come from the any of the mobile user in the queue, it will search for available processor in Mobile Computing, if the processor is free then the task will be scheduled for its execution otherwise the task will be arrange in waiting queue until the present assignment will be completed. As given in Figure Vol. 7, Issue 2, pp

2 Figure 1: Tasks are waiting in queue to allocate in Mobile Computing Domain This research paper discusses the problem of Mobile Computing, in such scenario where multiple mobile host accessing application running in wireless network. An application can be consider as multiple task and these tasks are arranged in an order queue and get scheduled to the available processor in Mobile Computing. If number of tasks is greater than available processors, the same numbers of task will be scheduled to available processors and the rest of the tasks will be in the queued status until present allocation will execute and processors will be free. To avoid such situation in the Mobile Computing, this research paper proposed a new task scheduling algorithm that will ensure that all the tasks in queue will execute by achieving optimal reliability to the processor in mobile computing. Some of the other related methods have been reported in the literature, such as Routing Scheme [1], Reliability and Performance [2], Task allocation[3, 4], Task scheduling [5, 8, 9], Task assignment [6], Reliable Distributed Grid Scheduler [7], Scheduling Manager for Mobile Cloud [10], Enhancement of Performance of Distributed Computing System [11], Task allocation for maximizing reliability [12, 13], Mobile Computing [14], Job Scheduling [15], resource allocation [16, 17, 18] Performance modeling and analysis [19], Energy-efficient deadline scheduling [20].This research paper has considered an example of task scheduling problem in Mobile Computing and introduce a new task scheduling algorithm with the help of Hungarian algorithm in order to get maximum processing reliability in Mobile Computing, the scheduling algorithm would also be deal with load balancing issues in the Mobile Computing so that performance of the Mobile Computing can be enhanced by using the proper utilization processors. II. NOTATIONS p t n m PRM Processor Task Number of Processors Number of Tasks Processing Reliability Matrix III. OBJECTIVE The main objective of this research paper is to improve the performance by maximizing the overall processing reliability for a Mobile Computing by introduce a new task scheduling algorithm to assign the tasks on various processors with in heterogonous environment to enhance the performance of the Mobile Computing. The nature of assignment of tasks to the processor is static. Task scheduling algorithm will also ensure the processing of all the tasks within the application in optimal way. In this paper performance is measured in term of processing reliability of the task that have to be get 636 Vol. 7, Issue 2, pp

3 processed on the processors of the environment with the achieving maximum level of processing reliability in Mobile computing. IV. TECHNIQUE This research paper has chosen the problem where a set P = {p 1, p 2, p 3, p n} of n processors with different processing speed and a set T = {t 1, t 2, t 3, t m} of m tasks, where m>n in order to evaluate optimal processing reliability in Mobile Computing. Processing reliability are known for all tasks for every processor and will be arrange the processing reliability for each task for different processor in a Processing Reliability Matrix (PRM) of order (n*m) and processing load (in terms of reliability) will initialize to zero for all processors by 1. After that scheduling algorithm will search for the maximum value by row (without repeating the column in the matrix), in result it would get the tasks equal to number of processors available in the Mobile Computing and those task will get scheduled. The process will repeat until number of tasks will remain lesser than the number of processors available in the mobile computing. Once this condition will occur where the numbers of processors are greater than the tasks waiting for the execution then will make slide change in the technique. Instead of searching element with maximum value row wise, the search will be steer column wise and that will make enable the final scheduling of remaining unallocated task in Mobile Computing. V. ALGORITHM 1. Start Algorithm 2. Read the number of task in m 3. Read the number of processor in n 4. Store task and Processing Reliability into Matrix PRM (,) n x m of order 5. While (All task! = Assigned) { i. Check if the matrix containing numbers of tasks are greater than or equal to numbers of processors (m>=n) then go to step (ii) else step (iv) ii. Search maximum value row wise in the matrix iii. Check if the column is previously selected for maximum value then GO TO step (ii) to find next maximum value for the row else Goto step (vi) to assign eligible task. iv. Search the maximum value column wise in the matrix v. Check if the row is previously selected for maximum value then GO TO step (iv) to find next maximum value for the column else Goto step (vi) to assign eligible task. vi. Assign the eligible tasks to available processors } 6. State the results 7. End of algorithm VI. IMPLEMENTATION This research paper consider Mobile Computing Domain which consist a set P of 3 processors {p 1, p 2, p 3} with different processing speed, and a set T of 7 tasks {t 1, t 2, t 3, t 4, t 5, t 6, t 7}. It is shown in the table 1. The processing reliability of each task varies for each processor in the domain, processing reliability are also known and mentioned in the processing reliability matrix namely PRM of order 3 x 7. Table 1: Processing Reliability Matrix PTM[3][8] t1 t2 t3 t4 t5 t6 t7 p p p Vol. 7, Issue 2, pp

4 As per the new task allocation algorithm, the approach will consider the maximum value for each row and will get the below stated results in Table 2. Table 2: Selecting maximum value row wise t4 t5 t7 PTM[3][8] p p p Since there are only three rows in the matrix that will schedule three tasks to the processors and scheduling table as mentioned in Table 3: Table 3: Scheduling Table Processor Task Processing Reliability p 1 t p 2 t p 3 t Hence the total numbers of tasks are 4 and still are greater than available numbers of processors (m>n), that will ensure repeat the same process and next three tasks will be scheduled again and now scheduling table is mentioned in Table 4: Table 4: Scheduling Table Processor Task Processing Reliability p 1 t 4* t * p 2 t 5* t * p 3 t 7* t * After repeating the same process of algorithm steps twice, still one task in the queue and gets remain unscheduled, here numbers of processors are greater than number of task (one) (m<n), now the element will be searched by column wise and that will ensure the last task will be allocated in the domain and the final scheduling table will be as stated in Table 5: Table 5: Scheduling Table Processor Task Processing Reliability p 1 t 4* t 1* t p 2 t 5* t p 3 t 7* t VII. CONCLUSION This research paper has considered m number of tasks needs to schedule to n number of processors where m is always greater than n in Mobile Computing. This research paper solves the problem task scheduling in such manner which would maximize the processing reliability of the task to the processors in Mobile Computing. In this research paper performance is measured in terms of processing reliability of the tasks that has been processed by the processor of the Mobile computing. The result as stated below of the given example here. Table 6: Final Scheduling Table Processor Task Processing Reliability p 1 t 4* t 1* t p 2 t 5* t p 3 t 7* t Total Processing Reliability The final task scheduling as mentioned in Table 6 is shown in Figure Vol. 7, Issue 2, pp

5 Figure 2: Final task assignment in Mobile Computing Domain Graphical representation of stated outcome of the given input as mentioned in Figure 3: Figure 3: Showing total processing reliability for various processors in mobile computing The technique stated in pseudo code applied on several sets of input data and that verified the objective of get maximum processing reliability for given tasks for their execution. The analysis of an algorithm mainly focuses on time complexity. The time complexity of above mentioned algorithm is O(m+n). By taking several input examples, the above algorithm returns results as mentioned in Table 3. VIII. Number of Processors (n) FUTURE WORK Table 4: Time Complexity Number of tasks (m) Complexity of algorithm [5] O(mn2) Complexity of present alogorithm O(m+n) This research paper employed static task scheduling model to optimize reliability of the Mobile computing. For future studies, dynamic task scheduling model can be designed for mobile computing or distributed network. Other future work may include develop some other routing techniques or task 639 Vol. 7, Issue 2, pp

6 assignment model to optimize cost, time and reliability of the distributed computing or mobile computing. REFERENCES [1]. AShajin Nargunam, M. P. Sebastian, 2007, Hierarchical Multicast Routing Scheme for Mobile Ad Hoc Network, Vol. 4873, pp [2]. Daeyong Jung, SungHo Chin, KwangSik Chung, Taeweon Suh, HeonChang Yu, JoonMin Gil, 2010, An Effective Job Replication Technique Based on Reliability and Performance in Mobile Grids, Lecture Notes in Computer Science, Vol. 6104, 2010, [3]. Faizul Navi Khan, Kapil Govil, 2013, Distributed Task Allocation Scheme for Performance Improvement in Mobile Computing Network, International Journal of Trends in Computer Science, vol: 2 issue: 3, pp: [4]. Faizul Navi Khan, Kapil Govil, Static Approach for Efficient Task Allocation in Distributed Environment. International Journal of Computer Applications, Vol. 81, Issue 81, [5]. Ilavarasan E, Manoharan R, 2010, High Performance and Energy Efficient Task Scheduling Algorithm for Heterogeneous Mobile Computing System, International Journal of Computer Science & Information Technology, Vol. 2, Issue 2, [6]. Kapil Govil and Dr. Avanish Kumar A modified and efficient algorithm for Static task assignment in Distributed Processing Environment. International Journal of Computer Applications, Vol. 23, Number 8, Article 1, 1 5, ISBN: , ISSN: [7]. Kovvur Ram Mohan Rao, Ramachandram S, Vijaya Kumar Kadappa,Govardhan A, 2011, A Reliable Distributed Grid Scheduler for Independent Tasks, IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 2, [8]. Lei Liu, Chunlin Li, 2010, Mobile Grid Task Scheduling Considering Resource Reliability, Computer Network and Multimedia Technology, ISBN: , 1-4 [9]. Mohammad Abdollahi Azgomi, Reza Entezari-Maleki, 2010, Task scheduling modelling and reliability evaluation of grid services using coloured Petri nets, Future Generation Computer Systems, Volume 26, Issue 8, [10]. Naif Aljabr, Fathy Eassa, 2013, Scheduling Manager for Mobile Cloud Using Multi-Agents, International Journal of Computer and Information Technology, Vol. 02, Issue 3, [11]. Pankaj Saxena, Kapil Govil, An Optimized Algorithm for Enhancement of Performance of Distributed Computing System. International Journal of Computer Applications, Vol. 64, Issue 2, [12]. Qin-Ma Kang, Hong He, Hui-Min Song, and Rong Den, 2010, Task allocation for maximizing reliability of distributed computing systems using honeybee mating optimization, Journal of Systems and Software, Volume 83, Issue 11, [13]. Rajesh D. Bharati, Vilas N. Jagtap, Omsagar C. Gupta, Shivanand S. Landge, 2013, Task Allocation for Maximizing Reliability of Distributed Computing Systems using Dynamic Greedy Heuristic, International Journal of Advanced Research in Computer and Communication Engineering, Vol. 2, Issue 3, pp [14]. Raminder Kaur Introuduction to Mobile Computing. The Journal of Computer Science and Information Tehcnology, Vol. 4, Issue 1, [15]. S.C Shah, S.H. Chauhdary, A.K. Bashir, M.S.Park, 2010, A Centralized Location-Based Job Scheduling Algorithm for Inter-dependent Jobs in Mobile Ad Hoc Computational Grids, Journal of Applied Sciences, Vol. 10, Issue 3, [16]. Sayed Chhattan Shaha, Qurat-Ul-Ain Nizamanib, Sajjad Hussain Chauhdaryc, Myong-Soon Parkd, 2012, An effective and robust two-phase resource allocation scheme for interdependent tasks in mobile ad hoc computational Grids, Journal of Parallel and Distributed Computing, Vol. 72, Issue 12, [17]. Sri Chusri Haryanti, Riri Fitri Sari, 2014, Reliability of Resource Allocation in Mobile Ad Hoc Grid with Tasks Replication, Journal of Computers, Vol. 9, Issue 2, [18]. Thenmozhi, S, A. Tamilarasi, P.T. Vanathi, 2012, A Fault Tolerant Resource Allocation Architecture for Mobile Grid, Journal of Computer Science, Vol. 8, Issue 6, [19]. Wei Ming Lin Performance modeling and analysis of correlated parallel computations. Elsevier Inc. Vol. 34, Issue 9, [20]. Yan Maa, b, Bin Gonga, Ryo Sugiharab, Rajesh Guptab, 2012, Energy-efficient deadline scheduling for heterogeneous systems, Journal of Parallel and Distributed Computing, Vol. 72, Issue 12, Vol. 7, Issue 2, pp

7 AUTHORS BIOGRAPHY Faizul Navi Khan completed his Master in Computer Application from M.D. University Rohtak (Haryana) India in the year 2006, and currently pursuing Ph.D. in Computer Application from Teerthanker Mahaveer University Moradabad, UP, India. He has more than 7+ years of work experience in IT Industry. He is the author of more than 10 research papers published in various journals and conference proceedings. Kapil Govil received his Ph.D. from Bundelkhand University, Jhansi, Uttar Pradesh, India; He has more than 6+ years of work experience in R&D. He has been contributed more than 50 technical research papers, published in various journals and conference proceedings. 641 Vol. 7, Issue 2, pp

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