Improved Shortest Remaining Burst Round Robin (ISRBRR) Using RMS as its time quantum
Journal Title: International Journal of Advanced Research in Computer Engineering & Technology(IJARCET) - Year 2012, Vol 1, Issue 8
Abstract
Round Robin (RR) performs optimally in timeshared systems because each process is given an equal amount of static time quantum. But the effectiveness of RR algorithm solely depends upon the choice of time quantum. I have made a comprehensive study and analysis of RR algorithm and SRBRR algorithm. I have proposed an improved version of SRBRR (Shortest Remaining Burst Round Robin) by assigning the processor to processes with shortest remaining burst in round robin manner using the RMS as its time quantum. Time quantum is computed as the root mean square of the burst times. My experimental analysis shows that ISRBRR performs better than RR algorithm and SRBRR in terms of reducing the number of context switches, average waiting time and average turnaround time.
Authors and Affiliations
P. Surendra Varma,
Authentication for Online Voting Using Steganography and Biometrics
In this paper an online voting authentication technique is proposed which provides biometric as well as password security to voter accounts. Voters are first identified by their facial image by using PCA. Second st...
An ACO Approach to Solve a Variant of TSP
This study is an investigation on the application of Ant Colony Optimization to a variant of TSP. This paper presents an Ant Colony Optimization (ACO) approach to solve a randomly generated TSP problem known as RTS...
Some New Steganographic Techniques using Spatial Resolution Reduction
In this paper, we present four new techniques to hide a large volume of text in a gray level image by reducing its spatial resolution to its half, to its quarter and by reducing the spatial resolution in width and in...
A Customized Ontological-Based Web Information Collection Model
It is known that Ontologies can be used to describe and formalize knowledge to represent user profiles in personalized web information collection. Though, there are many models adopted to represent user profiles ei...
CLUSTER ANALYSIS OF SSTS FRAMEWORK USING SOCIAL NETWORK ANALYSIS
Educational Data Mining (EDM) is an emerging trend, concerned with developing methods for exploring the large data related to educational system. The data is used to obtain the Implicit and Explicit knowledge distr...