Q1. How to use Green Computing strategies for energy efficiency, productivity and profitability?Answer. The answer lies in algorithmic efficiency which is a green computing strategy that provides better power management and increased energy utilization. (a) There is an energy model on the base that has a linear relationship with CPU usage and power consumption. It means that the information requested is sufficient to measure the time between CPU usage and power consumption. For a resource Ri at a given time, the usage Ui is defined as where n is the number of tasks running at that time and Ui, j is the resource usage of task tj. The energy consumption Ei of a resource ri at a given time is defined as: Where pmax is the energy consumption at peak load and pmin is the energy consumption at minimum load. (b) Task Consolidation Algorithm: - Task consolidation is the process of allocating tasks to resources without violating time factors, thereby maximizing resource utilization. There are two energy task consolidation algorithms, namely ECTC (Energy Consolidation and Task Consolidation) and MaxUtil (Maximum Utilization). Both are the same but their cost function is different. The ECTC cost function finds the actual energy consumption of the current task while ignoring the minimum energy consumption required to run a task simultaneously with other running tasks. The value fi,j of an activity tj on a resource Ri obtained using the cost function of the ECTC is defined as:Where is the difference between pmax and pmin. Uj is the utilization rate of tj and 0, 1, 2 is the total processing time of tj. Source: Green computing technologies, Wiley Publishers, 2001.Q2. What are the different approaches to Green Computing?Ans. (a) Virtualiza...... middle of the sheet ......res more resources. Cloud providers monitor and forecast demand and then allocate resources based on demand. Therefore, data centers always keep servers active based on current demand, which results in low power consumption compared to the conservative approach of overprovisioning. (b) Server Utilization: Generally, the local infrastructure is operated with very low utilization, sometimes going up to 5-10% of the average utilization. Using virtualization technologies, multiple applications can be hosted and run on the same server in an isolated manner, thus leading to utilization levels of up to 70%. (c) Data Center Efficiency: The energy efficiency of data centers has a significant impact on the total energy consumption of cloud computing. By using the most energy-efficient technologies, cloud providers can significantly improve the PUE of their data centers.