Tag: cloud energy consumption

Energy Aware Cloud Load Management

Resource Management in Cloud Computing is a topic that has received much interest both within the research community and within the operations of the large cloud providers; naturally, as it has a significant impact on the cloud provider’s bottom line. Much of the work to date on resource management focuses on Service Level Agreements (for different definitions of an SLA); some of the work also considers energy as a factor.

Objectives

The primary objective of this work is to develop an energy aware load management solution for Openstack: variants of this have been proposed before and indeed implemented in other stacks (e.g. Eucalyptus) but no such capability exists for Openstack as yet. As well as realizing the solution, the work will involve deploying a variant of the solution on the cloud platform without impacting the operation of the platform and determining what energy savings can be made. It is worth noting that the classical load balancing approach which is very typical for resource managers in cloud contexts is somewhat contradictory to minimizing energy consumption; consequently, the very standard load management tools are not suitable for minimizing cloud energy consumption.

Research Challenges

The research challenges are the following:

  • How to characterize the load in the system, particularly relating to spikes in demand
  • How much buffer space to maintain to accommodate load spikes
  • How to perform load consolidation – what load should be moved to what machines?
  • When to perform load consolidation – how frequently should it take place?
  • What are the energy gains that can be achieved from such a dynamic system?

Relevance to current and future markets

Advanced resource management mechanisms are a necessity for cloud computing generally. In the case of large deployments, Facebook’s autoscale is an example of how they can be used to achieve energy savings of the order of 15%. In the case of smaller deployments, it is still the case that there are many [[ https://gigaom.com/2013/11/30/the-sorry-state-of-server-utilization-and-the-impending-post-hypervisor-era/ | highly underutilized servers ]] in typical Data Centres and ultimately there will be a need to reduce costs and realize energy efficiencies. The problem is a large, general problem and energy is one specific aspect of it – one of the challenges for this work is how to integrate with other active parts of the ecosystem.

There are some commercial offering which explicitly address energy efficiency in the cloud context. These include:

Impact

Architecture

See the Energy Theme for the larger system architecture.

Implementation Roadmap

The next steps on the implementation roadmap are as follows:

  • Get tunnelled post-copy live migration working with modifications to libvirt (Jan 2015)
  • See if this can be pushed upstream to libvirt
  • Consolidate live migration work into clearer message relating to the potential of live migration (Jan 2015)
  • Devise control mechanism which can be used to provide energy based control (Feb 2015)
  • Deploy and test on Arcus servers (Mar 2015)
  • Determine if it is ready for deployment on Bart/Lisa (April 2015)

Contact

 

Understanding Cloud Energy Consumption

Energy in general and energy consumption in particular is a major issue for the large cloud providers today. Smaller cloud providers – both private and public – also have an interest in reducing their energy consumption, although it is often not their most important concern. With increasing competition and decreasing margins in the IaaS sector, management of energy costs will become increasingly important.

A basic prerequisite of advanced energy management solutions is a good understanding of energy consumption. This is increasingly available in multiple ways as energy meters proliferate: as well as having energy meters on racks, energy meters typically exist in modern hardware and even at subsystem level within today’s hardware. That said, energy metering is something that is commonly coupled to proprietary management systems.

The focus of this initiative is to develop an understanding of cloud energy consumption through measurement and analysis of usage.

Objectives

The objectives of the energy monitoring initiative are:

  • to develop a tool to visualize how energy is being consumed within the cloud resources;
  • to understand the correlation between usage of cloud resources and energy consumption;
  • to understand what level of granularity is appropriate for capturing energy data;
  • to devise mechanisms to disaggregate energy consumption amongst users of cloud platforms.

Research Challenges

Understanding cloud energy consumption does not give rise to fundamental research challenges – indeed, it is more of an enabler for a more advanced energy management system. However, to have a comprehensive understanding of cloud energy consumption, some research effort is required. The following research challenges arise in this context:

  • How to consolidate energy consumption from disparate sources to realize a clear understanding of energy consumption within the cloud environment
  • How to correlate energy consumption with revenue generating services at a fine-grained level (compute, storage and networking)

Relevance to current and future markets

Understanding energy consumption is essential for the large cloud providers as well as for today’s Data Centre providers. Consequently, there are already solutions available which support monitoring of energy consumption of IT resources. Today’s solutions typically do not have specific knowledge of cloud resource utilization and consequently, there is an opportunity for new tools which correlate cloud usage with energy monitoring.

In the Gartner Hype Cycle for Green IT 2014, there are some related technologies which have growth potential over the coming years. Specifically, these are:

  • DCIM Tools
  • Server Digital Power Management Module
  • Demand Response Management Tools

As such, there are future market opportunities for such energy related work. However, we are still evaluating its commercial potential.

Impact

Architecture

TBA.

Implementation Roadmap

This work has largely resulted in a live demonstrator. At present, there is not a significant effort to add more features and capabilities.

The current tasks on the roadmap are:

  • Ensure system is live – maintenance task
  • Periodically review energy consumption
  • Review usage of cloud resources and determine the amount of resources necessary to support this amount of utilization; thus the potential energy saving can be determined.
  • Promote the tool somewhat
  • Presentation at next Openstack Meetup
  • Investigate deployment opportunities

Contact