An analysis of the Green Computing Strategies (GCSs) implemented within three organizations

Q1. How to use Green Computing Strategies for energy efficiency, productivity and profitability?

Ans. The answer lies in algorithmic efficiency which is one of strategy for green computing that provides better power management and higher energy utilization.

(a) There is an energy model on the basis that has linear relationship with CPU utilization and energy consumption. It means required information is enough to measure time between CPU utilization and energy consumption.

For a resource Ri at any given time, the utilization 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 any given time is defined as:

Where pmax is the power consumption at peak load and pmin is the power consumption at minimum load.

(b) Task Consolidation Algorithm: - Task consolidation is the process of allocating tasks to resources without violating time factors thus maximize resource utilization. There are two energy task consolidation algorithms i.e. ECTC (Energy Consolidation and Task Consolidation) and MaxUtil (Maximum Utilization). Both are same but their cost function is different. The cost function of ECTC finds the actual energy consumption of the current task by ignoring the minimum energy consumption that is required to run a task simultaneously with other running tasks.

The value fi,j of a task tj on a resource Ri obtained using the cost function of ECTC is defined as:

Where is the difference between pmax and pmin. Uj is the utilization rate of tj and 0, 1, 2 is total processing time of tj.

Source: Green computing technologies, Wiley Publishers, 2001.

Q2. What are the different approaches to Green Computing?

Ans. (a) Virtualiza...

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...res more resources. Cloud providers monitor and predict the demand and thus allocate resources according to demand. Thus, datacenters always maintain the active servers according to current demand, which results in low energy consumption than the conservative approach of over-provisioning.

(b) Server Utilization: In general, on-premise infrastructure run with very low utilization, sometimes it goes down up to 5 to 10 percent of average utilization. Using virtualization technologies, multiple applications can be hosted and executed on the same server in isolation, thus lead to utilization levels up to 70%.

(c) Datacenter Efficiency: The power efficiency of datacenters has major impact on the total energy usage of Cloud computing. By using the most energy efficient technologies, cloud providers can significantly improve the PUE of their datacenters.