The Experts below are selected from a list of 93 Experts worldwide ranked by ideXlab platform
Diwakar Shukla - One of the best experts on this subject based on the ideXlab platform.
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some new methods for Ready Queue processing time estimation problem in multiprocessing environment
2020Co-Authors: Sarla More, Diwakar ShuklaAbstract:Ready Queue processing time estimation problem deals with many constraints. Because the processes which reside in the Ready Queue of computer memory come in varieties such as process size, process requirement indifferences and process types. To match up all these differences is a difficult task to solve so that the processes can be used to perform its task efficiently at any platform. A prior estimation of Ready Queue processing time helps to meet the system reliability and robustness. A pre-calculated time will ensure the system from failure; also, the backup of task performed can be maintained. In this paper, the existing methods on this approach are described, and how some new methods can be used for the better performance is demonstrated. For this purpose, some sampling techniques are used, and the lottery scheduling procedure is explained which very efficiently performs this task of scheduling on the basis of probabilistic approach and randomness property. The estimation is performed by using sampling methods; with the help of some mathematical calculations, the results are obtained, and finally, confidence interval will ensure the accuracy of the result. So that some new methods can be generated; this provides the result as more efficient than the previous ones. Although various scheduling schemes are available, the lottery scheduling scheme provides the fairness and also removes starvation. Rather than working on the complete data set, some samples can be generated to modularize the work which will be efficient too. So, this paper proposed some new methods in Ready Queue processing time estimation in multiprocessor environment.
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analysis and extension of methods in Ready Queue processing time estimation in multiprocessor environment
Social Science Research Network, 2019Co-Authors: Sarla More, Diwakar ShuklaAbstract:Lottery scheduling is a technique which is based on probabilistic approach and randomness. Selection of processes from Ready Queue performed randomly and a fair share of resources is done with some probabilistic value so that the problem of starvation has no place. The advancement of lottery scheduling schemes is described here and compared to each other to find out the best one method. By using lottery scheduling scheme and sampling methods (Ratio estimation) the estimation of total processing time of Ready Queue processes is performed to get the estimated time. If system fails suddenly or other disaster happens in the system, the predicted time will safeguard the system and also for the backup requirements the predicted time is very much useful. In the multiprocessor environment the estimation of Ready Queue processing time with the modified lottery scheduling algorithm is performed. To calculate the Ready Queue processing time the mean and variance of the sampled processes is obtained and to check efficiency of the result the confidence interval is calculated. Here systematic lottery scheduling scheme is explained and other modified lottery scheduling schemes are compared to obtain a best approach in future.
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estimation of Ready Queue processing time using transformed factor type t f t estimator in multiprocessor environment
International Journal of Computer Applications, 2013Co-Authors: Diwakar Shukla, Anjali Jain, Kapil VermaAbstract:Ready Queue processing time estimation problem appears when many processes remain in the Ready Queue just before the occurrence of sudden failure of system. The system administrator has to decide immediately, how much further time is required to process the remaining jobs in the Ready Queue, before shutting down the entire system as precautionary measure, so that while restart, it may remain in the safe state. In lottery scheduling, this prediction is possible with the help of sampling techniques. Factor- Type estimation method, existing in literature of sampling, was used by many authors to predict the time required provided the highly correlated sources of auxiliary information are available. This paper suggests two new estimation methods to predict the remaining total processing time required to process completely the Ready Queue provided sources of auxiliary information are negatively correlated. Under this approximation, the bias and m.s.e of the proposed estimators have been obtained using the set up of random sampling applicable to lottery scheduling. Performance of both estimation methods are compared in terms of mean squared error. The confidence intervals are calculated for comparing the efficiency of the estimate. One proposed estimator found better over other. . KeywordsScheduling, Transformed Factor-Type (T-F-T) Estimator, Mean Squared Error (M.S.E), Variance, Confidence Intervals
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Ready Queue mean time estimation in lottery scheduling using auxiliary variables in multiprocessor environment
International Journal of Computer Applications, 2012Co-Authors: Diwakar Shukla, Anjali JainAbstract:The Ready Queue estimation problem appears when many processes remain in the Ready Queue after the sudden failure. The system manager has to decide immediately how much further time is required to process all the remaining jobs in the Ready Queue. In lottery scheduling, this prediction is possible with the help of sampling techniques. To strengthen the prediction methodology, the auxiliary source of data is often utilized. This paper considers the three additional data sources as (i) process size (ii) process priority and (iii) process expected time. The Ratio method, existing in sampling literature, is used to predict the time required for remaining jobs after failure. A comparative study between different auxiliary sources has been made. It is found that highly correlated source of auxiliary information provides better processing time prediction.
Anjali Jain - One of the best experts on this subject based on the ideXlab platform.
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estimation of Ready Queue processing time using transformed factor type t f t estimator in multiprocessor environment
International Journal of Computer Applications, 2013Co-Authors: Diwakar Shukla, Anjali Jain, Kapil VermaAbstract:Ready Queue processing time estimation problem appears when many processes remain in the Ready Queue just before the occurrence of sudden failure of system. The system administrator has to decide immediately, how much further time is required to process the remaining jobs in the Ready Queue, before shutting down the entire system as precautionary measure, so that while restart, it may remain in the safe state. In lottery scheduling, this prediction is possible with the help of sampling techniques. Factor- Type estimation method, existing in literature of sampling, was used by many authors to predict the time required provided the highly correlated sources of auxiliary information are available. This paper suggests two new estimation methods to predict the remaining total processing time required to process completely the Ready Queue provided sources of auxiliary information are negatively correlated. Under this approximation, the bias and m.s.e of the proposed estimators have been obtained using the set up of random sampling applicable to lottery scheduling. Performance of both estimation methods are compared in terms of mean squared error. The confidence intervals are calculated for comparing the efficiency of the estimate. One proposed estimator found better over other. . KeywordsScheduling, Transformed Factor-Type (T-F-T) Estimator, Mean Squared Error (M.S.E), Variance, Confidence Intervals
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Ready Queue mean time estimation in lottery scheduling using auxiliary variables in multiprocessor environment
International Journal of Computer Applications, 2012Co-Authors: Diwakar Shukla, Anjali JainAbstract:The Ready Queue estimation problem appears when many processes remain in the Ready Queue after the sudden failure. The system manager has to decide immediately how much further time is required to process all the remaining jobs in the Ready Queue. In lottery scheduling, this prediction is possible with the help of sampling techniques. To strengthen the prediction methodology, the auxiliary source of data is often utilized. This paper considers the three additional data sources as (i) process size (ii) process priority and (iii) process expected time. The Ratio method, existing in sampling literature, is used to predict the time required for remaining jobs after failure. A comparative study between different auxiliary sources has been made. It is found that highly correlated source of auxiliary information provides better processing time prediction.
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estimation of Ready Queue processing time using efficient factor type estimator e f t in multiprocessor environment
International Journal of Computer Applications, 2012Co-Authors: D Shukla, Anjali JainAbstract:The Ready Queue processing time estimation problem appears when many processes remain in the Ready Queue after the sudden failure. The system manager has to decide immediately how much further time is required to process remaining jobs in the Ready Queue. In lottery scheduling, this prediction is possible with the help of sampling techniques. Ratio method, existing in literature of sampling, was previously used by authors to predict the time required provided highly correlated source of auxiliary information is available and used. This paper suggests two new estimation methods which are compared in terms of estimating the total processing time. Under large sample approximation, the bias and m.s.e of proposed estimators have been obtained in the set up of random sampling applicable to lottery scheduling. Performance of both is compared in terms of mean squared error. The confidence intervals are calculated for the estimate and they provide strong numerical support to the theoretical findings.
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analysis of Ready Queue processing time under pps ls and srs ls scheme in multiprocessing environment
2012Co-Authors: D Shukla, Anjali JainAbstract:In operating system, process sequencing is an open problem and solved by many scientists/authors suggesting different scheduling schemes. Every process needs a time span to be processed by the CPU. Lottery scheduling is one such scheme where the process selection is purely on random basis. The Ready Queue is used for processes to wait there until selected for processor. This paper considers the environment of many processors, a Ready Queue, lottery scheduling and presents an efficient method to predict about total time needed to process the entire Ready Queue if only few are processed in a specified time. Confidence internals are calculated based on PPS-LS and compared with SRS-LS. The PPS-LS found better over SRS-LS.
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estimation of Ready Queue processing time under usual group lottery scheduling gls in multiprocessor environment
International Journal of Computer Applications, 2010Co-Authors: D Shukla, Anjali Jain, Amita ChoudharyAbstract:Lottery scheduling is one of the useful techniques for managing the process Queue by the scheduler. The significant feature it has the random selection of jobs in a probability manner so that various existing probability models could be used to derive interesting results. One of possible applications incorporated herewith by using probability based sampling models to estimate total time required to process all the jobs in a Ready Queue. A new scheduling scheme is designed named as Group Lottery Scheduling (GLS) and using this the total possible Ready Queue processing time is predicted in multi-processor environment. There are two variants involved in GLS as Type-I allocation and Type-II allocation of jobs to the multi-processors whose variabilities are compared. A numerical example is incorporated to support the theoretical findings.
Sarla More - One of the best experts on this subject based on the ideXlab platform.
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some new methods for Ready Queue processing time estimation problem in multiprocessing environment
2020Co-Authors: Sarla More, Diwakar ShuklaAbstract:Ready Queue processing time estimation problem deals with many constraints. Because the processes which reside in the Ready Queue of computer memory come in varieties such as process size, process requirement indifferences and process types. To match up all these differences is a difficult task to solve so that the processes can be used to perform its task efficiently at any platform. A prior estimation of Ready Queue processing time helps to meet the system reliability and robustness. A pre-calculated time will ensure the system from failure; also, the backup of task performed can be maintained. In this paper, the existing methods on this approach are described, and how some new methods can be used for the better performance is demonstrated. For this purpose, some sampling techniques are used, and the lottery scheduling procedure is explained which very efficiently performs this task of scheduling on the basis of probabilistic approach and randomness property. The estimation is performed by using sampling methods; with the help of some mathematical calculations, the results are obtained, and finally, confidence interval will ensure the accuracy of the result. So that some new methods can be generated; this provides the result as more efficient than the previous ones. Although various scheduling schemes are available, the lottery scheduling scheme provides the fairness and also removes starvation. Rather than working on the complete data set, some samples can be generated to modularize the work which will be efficient too. So, this paper proposed some new methods in Ready Queue processing time estimation in multiprocessor environment.
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analysis and extension of methods in Ready Queue processing time estimation in multiprocessor environment
Social Science Research Network, 2019Co-Authors: Sarla More, Diwakar ShuklaAbstract:Lottery scheduling is a technique which is based on probabilistic approach and randomness. Selection of processes from Ready Queue performed randomly and a fair share of resources is done with some probabilistic value so that the problem of starvation has no place. The advancement of lottery scheduling schemes is described here and compared to each other to find out the best one method. By using lottery scheduling scheme and sampling methods (Ratio estimation) the estimation of total processing time of Ready Queue processes is performed to get the estimated time. If system fails suddenly or other disaster happens in the system, the predicted time will safeguard the system and also for the backup requirements the predicted time is very much useful. In the multiprocessor environment the estimation of Ready Queue processing time with the modified lottery scheduling algorithm is performed. To calculate the Ready Queue processing time the mean and variance of the sampled processes is obtained and to check efficiency of the result the confidence interval is calculated. Here systematic lottery scheduling scheme is explained and other modified lottery scheduling schemes are compared to obtain a best approach in future.
Yin Zhenyu - One of the best experts on this subject based on the ideXlab platform.
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Ready Queue optimization research in task scheduling
Computer Simulation, 2006Co-Authors: Yin ZhenyuAbstract:Most of embedded real-time systems only equip limited necessary resources so the extra overheads of preemptions among tasks debase the performance of systems significantly.Through scheduling process analysis of periodic task,the waiting limit formula of each task in Ready Queue was obtained while guarantees its deadline.In addition,some properties,such as final preempting time was deduced and the necessary condition of periodic tasks preempting behavior was described quantitatively.Based on them,a micro scheduling preemption model for periodic tasks in Ready Queue was put forward,which decreased the number of preemptions and optimized system performance through changing the preempting sequences.The simulation results of the case study show that the model can not only decrease the number of preemptions effectively but also improve the processor utilization for static priority scheduling algorithm such as rate monotonic scheduling.
Risat Mahmud Pathan - One of the best experts on this subject based on the ideXlab platform.
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design of an efficient Ready Queue for earliest deadline first edf scheduler
Design Automation and Test in Europe, 2016Co-Authors: Risat Mahmud PathanAbstract:Although dynamic-priority-based EDF algorithm is known to be theoretically optimal for scheduling sporadic real-time tasks on uniprocessor, fixed-priority (FP) scheduling is mostly used in practice. One of the main reasons for FP scheduling being popular in the industry is its efficient implementation: operations on the Ready Queue can be done in constant time. On the other hand, Ready Queue of EDF scheduler is generally implemented as a priority Queue, for example, using a binary min-heap data structure in which (insertion/deletion) operation cannot be done in constant time. This paper proposes a new design of Ready Queue for EDF scheduler: a simple data structure for the Ready Queue and efficient operations to insert and remove task control blocks (TCBs) to and from the Ready Queue are proposed. Insertion of a TCB of a newly released job (that cannot preempt the currently-executing job) is done in non-constant time. However, insertion of a TCB of a preempted job or the removal of the TCB of job having the highest EDF priority from the Ready Queue can be done in constant time. Simulation using randomly generated task sets shows that the overhead of managing jobs in our proposed Ready Queue for EDF scheduler is significantly lower than that of other approaches. We believe that theoretically optimal EDF algorithm implemented based on our proposed Ready-Queue data structure will make EDF popular in industry.
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Unifying fixed- and dynamic-priority scheduling based on priority promotion and an improved Ready Queue management technique
21st IEEE Real-Time and Embedded Technology and Applications Symposium, 2015Co-Authors: Risat Mahmud PathanAbstract:This paper proposes a new preemptive scheduling algorithm, called Fixed-Priority with Priority Promotion (FPP), for scheduling sporadic tasks on uni- and multiprocessor platform. In FPP scheduling, tasks are executed similar to traditional fixed-priority (FP) scheduling but the priority of some tasks may be promoted at fixed time interval (called, promotion point) relative to the release time of each job. A policy called Increase Priority at Deadline Difference (IPDD) to compute the promotion points and promoted priorities for each task is proposed. It is shown that when all tasks' priorities are governed under IPDD policy, then FPP scheduling essentially prioritizes jobs according to Earliest-Deadline-First (EDF) priority. It is known that inserting and removing jobs to and from the Ready Queue of traditional EDF scheduler is more complex and has higher overhead than that of FP scheduler. To avoid such problem in FPP scheduling, a simple data structure and efficient operations to insert and remove jobs to and from the Ready Queue are proposed. Finally, an effective scheme to reduce overhead due to priority promotion is proposed: if a task set is not schedulable using traditional FP scheduling, then promotion points are assigned only to those tasks that need them to meet the deadlines; otherwise, tasks are assigned fixed priorities without any priority promotion and executed same as traditional FP scheduling. Empirical investigation shows the effectiveness of the proposed scheme in reducing overhead on uniprocessor and in accepting larger number of task sets in comparison to that of using state-of-the-art global schedulability tests for multiprocessors.
