A Survey and Taxonomy of Energy Efficient Resource Management Techniques in Platform as a Service Cloud

A Survey and Taxonomy of Energy Efficient Resource Management Techniques in Platform as a Service Cloud

Sareh Fotuhi Piraghaj (The University of Melbourne, Australia), Amir Vahid Dastjerdi (The University of Melbourne, Australia), Rodrigo N. Calheiros (The University of Melbourne, Australia) and Rajkumar Buyya (The University of Melbourne, Australia)
DOI: 10.4018/978-1-5225-0759-8.ch017
OnDemand PDF Download:
$30.00
List Price: $37.50

Abstract

The numerous advantages of cloud computing environments, including scalability, high availability, and cost effectiveness have encouraged service providers to adopt the available cloud models to offer solutions. This rise in cloud adoption, in return encourages platform providers to increase the underlying capacity of their data centers so that they can accommodate the increasing demand of new customers. Increasing the capacity and building large-scale data centers has caused a drastic growth in energy consumption of cloud environments. The energy consumption not only affects the Total Cost of Ownership but also increases the environmental footprint of data centers as CO2 emissions increases. Hence, energy and power efficiency of the data centers has become an important research area in distributed systems. In order to identify the challenges in this domain, this chapter surveys and classifies the energy efficient resource management techniques specifically focused on the PaaS cloud service models.
Chapter Preview
Top

Background

The numerous advantages of cloud computing environments, including cost effectiveness, on-demand scalability, and ease of management, encourage service providers to adopt them and offer solutions via cloud service models. In return, it encourages platform providers to increase the underlying capacity of their data centers to accommodate the increasing demand of new customers. One of the main drawbacks of the growth in capacity of cloud data centers is the need for more energy to power these large-scale infrastructures. This drastic growth in energy consumption of cloud data centers is a major concern of cloud providers.

An average data center consumes as much energy as 25,000 households, as reported by Kaplan et al. (Kaplan, Forrest, & Kindler, 2008). This energy consumption results in increased Total Cost of Ownership (TCO) and consequently decreases the Return of Investment (ROI) of the cloud infrastructure. Apart from low ROI, energy consumption has a great impact on carbon dioxide (CO2) emissions, which are estimated to be 2% of global emissions (Buyya, Beloglazov, & Abawajy, 2010).

The energy wastage in data centers are caused by various reasons such as inefficiency in data center cooling system (S. Greenberg, Mills, Tschudi, Rumsey, & Myatt, 2006), network equipment (Heller et al., 2010), and server utilization (A. Greenberg, Hamilton, Maltz, & Patel, 2008). However, servers are still the main power consumers in a data center (A. Greenberg et al., 2008). Both the amount of work and the efficiency with which the work is performed affects the power consumption of servers (Krioukov et al., 2010). Therefore, for improving the power efficiency of data centers, the energy consumption of servers should be made more proportional to their workload.

The power proportionality is defined as the proportion of the amount of power consumed comparing to the actual workload. The power proportionality can be achieved by either decreasing the servers idle power at hardware level (Barroso & Holzle, 2007) or efficient provisioning of servers through power aware resource management policies at software level. In this chapter, we solely focus on software level and the resource management techniques utilized for decreasing energy consumption in Cloud data centers considering four different service models (depicted in Figure 1):

Figure 1.

The container as a service cloud service model links the PaaS and IaaS layers

  • Infrastructure as a Service (IaaS): In this service a consumer has the ability to provision the required resources while running and deploying arbitrary software such as operating systems and applications. Using this model consumers do not need to worry about the underlying hardware.

  • Platform as a Service (PaaS): This model has a higher level of abstraction in comparison to the IaaS model. By offering the application-hosting environment, the consumers do not need to have any control over the underlying infrastructure including storage, processing and network.

  • Software as a Service (SaaS): Using this service model, a consumer is able to use the provider’s applications which are hosted on the Cloud. Applications are accessible through web portals. This model has also made development and testing easy for providers via having access to the software.

  • Containers as a Service (CaaS): This service is recently introduced and lies between IaaS and PaaS. While IaaS provides virtualized compute resources and PaaS provides application specific runtime services, CaaS is the missing layer that glues these two layers together.

Among the above-mentioned service models, this chapter mostly focuses on energy efficient resource management techniques for PaaS and CaaS.

Complete Chapter List

Search this Book:
Reset