In the last decade, dependency of human beings on computers has been rising at an unpredictable scale. The data related to human activities from small activities to complex tasks are being recorded and used to train machines also. This is an era of artificial intelligence. The computing resources are gaining more and more attention and so is computational emission. There is a dire need for Green Computing in the coming days. This paper identifies some of the most critical parameters that affect the decisions of the organizations for adopting the green computing. The paper uses a survey technique for the evaluation of different criteria. Major green computing decision parameters have been indentified from the existing literature and a survey of the industry professionals on these parameters has been performed. The matrix obtained after survey is analyzed using the Hasse Diagram partial order ranking technique to obtain a partial order set and thereafter the partial order is converted into a complete order. This technique helps to identify the ranking of various parameters that affect Green Computing decisions in the current state of practice. Although there are multiple criteria for making the green computing decision, this novel ranking methodology has been used as it uses discrete mathematics for weighting the different attributes.
Volume 12 | 03-Special Issue
Pages: 1161-1165
DOI: 10.5373/JARDCS/V12SP3/20201362