Energy use and Ecological Impact of Large scale Data Centres

The Energy use and Ecological Impact of Large scale Data Centres can be described by analysis of the concept of Energy proportion system.

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Typical Operating Region

Percentage of System Utilization

Percentage of Power Usage

Power

Energy Efficiency

The above diagram shows power requirements scale linearly with the load, the energy efficiency of a computing system is not a linear function of the load; even when idle, a system may use 50% of the power corresponding to the full load. Data collected over a long period of time shows that the typical operating region for the servers at a data centre is from about 10% to 50% of the load.

This is a very important concept of resource management in a cloud environment in which load is concentrated in a subset of servers and rest of the servers are kept in standby mode whenever possible. An energy proportional system consumes on power when idle, very little power under light load and gradually more power as load increases.

            An ideal energy proportion system is always operating at 100% efficiency. Operating efficiency of a system is captured by an expression of performance per watt power. Energy proportion Network consumes energy proportional to their communication load. An example of energy proportion network is infiniband.

Strategy to reduce energy consumption is to concentrate the load on a small no. Of disk and allow others to operate in low power mode.

Another technique is based on data migration. The system uses data storage in virtual nodes managed with distributed hash table, the migration is controlled by two algorithms, a short term optimization algorithm used for gathering or spreading virtual nodes according to the daily variation of workload so that the number of active physical node is reduced to a minimum and a long term optimization algorithm, used for coping with changes in the popularity of data over a longer period i.e. a week. 

Dynamic resource provisioning is also necessary to minimize power consumption. Two critical issues related to it are i) amount of resource allocated to each application ii) placement of individual work load.