ATS:A Novel Time-Sharing CPU Scheduling Algorithm Based on Features Similarities

Minimizing time cost in time-shared operating systems is considered basic and essential task,and it is the most significant goal for the researchers who interested in CPU scheduling algorithms.Waiting time,turnaround time,and number of context switches are themost time cost criteria used to compare between CPU scheduling algorithms.CPU scheduling algorithms are divided into non-preemptive and preemptive.RoundRobin(RR)algorithm is the most famous as it is the basis for all the algorithms used in time-sharing.In this paper,the authors proposed a novel CPU scheduling algorithm based on RR.The proposed algorithm is called Adjustable Time Slice(ATS).It reduces the time cost by taking the advantage of the low overhead of RR algorithm.In addition,ATS favors short processes allowing them to run longer time than given to long processes.The specific characteristics of each process are;its CPU execution time,weight,time slice,and number of context switches.ATS clusters the processes in groups depending on these characteristics.The traditionalRRassigns fixed time slice for each process.On the other hand,dynamic variants of RR assign time slice for each process differs from other processes.The essential difference between ATS and the other methods is that it gives a set of processes a specific time based on their similarities within the same cluster.The authors compared between ATS with five popular scheduling algorithms on nine datasets of processes.The datasets used in the comparison vary in their features.The evaluation was measured in term of time cost and the experiments showed that the proposed algorithm reduces the time cost.

Relative Time Quantum-based Enhancements in Round Robin Scheduling

Modern human life is heavily dependent on computing systems and one of the core components affecting the performance of these systems is underlying operating system.Operating systems need to be upgraded to match the needs of modern-day systems relying on Internet of Things,Fog computing and Mobile based applications.The scheduling algorithm of the operating system dictates that how the resources will be allocated to the processes and the Round Robin algorithm(RR)has been widely used for it.The intent of this study is to ameliorate RR scheduling algorithm to optimize task scheduling.We have carried out an experimental study where we have developed four variations of RR,each algorithm considers three-time quanta and the performance of these variations was compared with the RR algorithm,and results highlighted that these variations performed better than conventional RR algorithm.In the future,we intend to develop an automated scheduler that can determine optimal algorithm based on the current set of processes and will allocate time quantum to the processes intelligently at the run time.This way the task performance of modern-day systems can be improved to make them more efficient.

An OP-TEE Energy-Efficient Task Scheduling Approach Based on Mobile Application Characteristics

Trusted Execution Environment(TEE)is an important part of the security architecture of modern mobile devices,but its secure interaction process brings extra computing burden to mobile devices.This paper takes open portable trusted execution environment(OP-TEE)as the research object and deploys it to Raspberry Pi 3B,designs and implements a benchmark for OP-TEE,and analyzes its program characteristics.Furthermore,the application execution time,energy consumption and energy-delay product(EDP)are taken as the optimization objectives,and the central processing unit(CPU)frequency scheduling strategy of mobile devices is dynamically adjusted according to the characteristics of different applications through the combined model.The experimental result shows that compared with the default strategy,the scheduling method proposed in this paper saves 21.18%on average with the Line Regression-Decision Tree scheduling model with the shortest delay as the optimization objective.The Decision Tree-Support Vector Regression(SVR)scheduling model,which takes the lowest energy consumption as the optimization goal,saves 22%energy on average.The Decision Tree-K-Nearest Neighbor(KNN)scheduling model with the lowest EDP as the optimization objective optimizes about 33.9%on average.

An Adjustable Variant of Round Robin Algorithm Based on Clustering Technique

CPU scheduling is the basic task within any time-shared operating system.One of the main goals of the researchers interested in CPU scheduling is minimizing time cost.Comparing between CPU scheduling algorithms is subject to some scheduling criteria(e.g.,turnaround time,waiting time and number of context switches(NCS)).Scheduling policy is divided into preemptive and non-preemptive.Round Robin(RR)algorithm is the most common preemptive scheduling algorithm used in the time-shared operating systems.In this paper,the authors proposed a modified version of the RR algorithm,called dynamic time slice(DTS),to combine the advantageous of the low scheduling overhead of the RR and favor short process for the sake of minimizing time cost.Each process has a weight proportional to the weights of all processes.The process’s weight determines its time slice within the current period.The authors benefit from the clustering technique in grouping the processes that are similar in their attributes(e.g.,CPU service time,weight,allowed time slice(ATS),proportional burst time(PBT)and NCS).Each process in a cluster is assigned the average of the processes’time slices in this cluster.A comparative study of six popular scheduling algorithms and the proposed approach on nine groups of processes vary in their attributes was performed and the evaluation was measured in terms of waiting and turnaround times,and NCS.The experiments showed that the proposed algorithm gives better results.