Terms Of Average Waiting Time Research Articles

Interpretive Structural Modeling Based Assessment and Optimization of Cloud with Internet of Things (CloudIoT) Issues Through Effective Scheduling

Integrated CloudIoT is an emerging field of study that integrates the Cloud and the Internet of Things (IoT) to make machines smarter and deal with real-world objects in a distributed manner. It collects data from various devices and analyses it to increase efficiency and productivity. Because Cloud and IoT are complementary technologies with distinct areas of application, integrating them is difficult. This paper identifies various CloudIoT issues and analyzes them to make a relational model. The Interpretive Structural Modeling (ISM) approach establishes the interrelationship among the problems identified. The issues are categorised based on driving and dependent power, and a hierarchical model is presented. The ISM analysis shows that scheduling is an important aspect and has both (driving and dependence) power to improve the performance of the CloudIoT model. Therefore, existing CloudIoT job scheduling algorithms are analysed, and a cloud-centric scheduling mechanism is proposed to execute IoT jobs on a suitable cloud. The cloud implementation using an open-source framework to simulate Cloud Computing (CloudSim), based on the job’s workload, is presented. Simulation results of the proposed scheduling model indicate better performance in terms of Average Waiting Time (AWT) and makespan than existing cloud-based scheduling approaches.

Improved Round Robin CPU Scheduling Algorithm with Different Arrival Times Based on Dynamic Quantum

Modern operating systems are based on the principle of time-sharing in executing simultaneous operations. Determining the length of the time slice, and the times when processes arrive at the ready queue are problems that affect metrics such as the average waiting time (AWT), average turnaround time (ATAT), response time (RT), and number of context switches (NCS) of the time-sharing round robin RR algorithms. The research aims to propose an algorithm that achieves a short waiting time while maintaining a reasonable response time, which is the most important characteristic of time-sharing algorithms. The Different Arrival-Dynamic Quantum Round Robin (DADQRR) algorithm bases its work on different parameters to adjust the time slice value dynamically. The algorithm has been compared to three other algorithms that are similar in terms of dealing with different arrival times, namely AN, MARR, and RR. The algorithm outperformed the three algorithms at a range from 6.155% to 31.409% in terms of AWT. It achieved an outperformance of 5.924% to 30.850%, considering the TAT. The ranges of outperformance values resulted from the difference in the ranges of arrival times, as well as in the ranges of burst times.