Enhancing the Power Consumption of the Data Centers in Energy Efficient Cloud Computing

Enhancing the Power Consumption of the Data Centers in Energy Efficient Cloud Computing Archana Soni 1, Prof. Bharat Pahadiya 2 M.Tech. Scholar 1, Assistant Professor 2, Department of CSE, Sanghvi Innovative Academy, Indore, MP, INDIA, Abstract--Green computing research works on the key issues to energy efficiency in computing for promoting environmentally friendly computer technologies. In the presented work for improving the performance cloud computing and enhancing eco-friendly effect an effort is made and the entire investigation of green computing and a new technique development is demonstrated. This technique promises to enhance the power consumption of the data centers. Thus for justifying the performance the implemented methodology is compared with the traditionally implemented technique (MAD). I. INTRODUCTION In the past a couple of years computer standard was moved to remote data farms and the software and hardware services accessible on the premise of pay for utilize.this is called Cloud computing, At present Cloud computing based framework squander an extraordinary measure of force and produces carbon dioxide. In view of the fact that various servers don't have an optimum quality cooling structure. Green Computing is used to sanction more energy proficient utilization of computing power.this paper indicates the prerequisite of Green Computing and methods to spare the vitality by distinctive methodologies Cloud computing Services are backed by a state of the servers farm (information server) which utilizes the virtual computers for detention reason. Server farm Service confronts the matter of force utilization and requisition's nature of Services [1]. Cloud computing conveys foundation stage and programming (provision) as a service of interest as a membership based Services [2]. To decrease the force utilization here the term green Computing is utilized.when the term green Computing is presented, it reflects environmental awareness with computers [3]. In various associations IT separation is for the most part devoured a ton of force [3] Green is Computing is the ecologically capable utilization of Computing. 1.1 Challenges: - Complexities of licensing are the issue with virtualization. For example a Linux based server offers a virtualized windows server must fulfill authorizing fundamentals for the reason that flexibility of virtualization and returns of on interest virtualization is hindered. Virtualized desktop brings about trust on concentrated servers furthermore SAN capacity) and the system (and higher-transfer speed necessities). Reliance on concentrated server and system leaves the end clients defenseless against server. [4] The client ready to working provincially during a shutdown, however when client logs off then over again reboots the computer it get dead This is interestingly with thick customers where the client work mainly proceed until the network could be restored. For solving the QoS of application and equipment s power consumption some of work is done to reduce the power consumption based on Metrics and Task Scheduling Policies for Energy Saving in Multi core Computers. Power consumption is analyzed by resource allocation and then analysed the power consumed by the equipment and resources which are allocated. II. 2.1 Cloud Computing BACKGROUND WORK The cloud makes it feasible for you to access your information from anywhere at any time. While a traditional computer setup needs you to be in the similar location as your data storage space device, the clouds take away that step. The clouds remove the same physical location as the hardware that stores your data [5]. This is especially helpful for businesses that cannot afford the same amount of hardware and storage space as an advanced company. The cost of purchasing and storing memory equipment is eliminated because companies are now using cloud to save their data. A big business can acquire more living space or reduce their contribution as their production grows or they find, they necessitate a smaller amount storage space. As shown in Figure 1.1 it describes a company, firm, group or individual that uses a Web-based application for every task rather than installing software or storing data on a computer. All cloud environments are not common, other than a move about toward this is a long-term objective for cloud computing enthusiasts and cloud capitalists. 100

Single constraint is that you necessitate having an internet connection in order to right to use the cloud. This means that if you want to Search at a particular manuscript you have house in the cloud, you should first set up an internet connection either all the way through a wireless or wired internet or a portable broadband connection. The benefits are that you can access that similar manuscript from wherever you are with any machine that can access the internet. This equipment s possibly will be a workstation, laptop, tablet or mobile phone. This can as well help your production to function more efficiently because anybody who can connect to the internet and your cloud can work on manuscripts, right to use software and store up information. Figure1.1 Cloud Environments 2.2 Cloud Characteristics The main essential features of Cloud computing are as follows: [6]. A. Shared Infrastructure: Uses a virtualized software replica, enable the involvement of physical services, storage space, and network capability. The cloud communications, apart from of deployment model, try to find to construct the most of the accessible infrastructure across a number of users. Figure 1.2 Cloud Characteristics B. Dynamic Provisioning: allow for the provision of services based on present order requests. This is completed automatically using software automation, enabling the improvement and decline of service capability, as necessary. This active scaling wants to be completed while maintaining high levels of consistency and protection. 101

C. Network Access: Needs to be accessed the internet from a broad range of equipment s such as Personal Computers, laptops and Mobile phone devices, using standards-based APIs (for example HTTP) Deployments of services in the cloud include the whole thing from using Commercial applications to the latest application on the latest Smartphone. D. Managed Metering: use metering for managing and optimizing the facility and to provide reporting and bill information. In this way, consumers are billed for services according to how much they have actually used during the billing phase. In short, cloud computing allows for the contribution and scalable deployment of services, as needed, from almost any location, and for which the customer can be billed based on actual usage. 2.3 Advantages and Disadvantages Some key benefits to use cloud computing which is given in [7] are as: A. Reduced Cost: Cloud technology is paid incrementally (you pay only for what you need), economy organizations currency in the short run. Money saved can be used for other significant resources. B. Increased Storage: Organizations can store more and more data than on private computer systems. C. Highly Automated: IT personnel not needed to keep software up to date as maintenance is the job of the service provider on the cloud. D. More Mobility: Employees can access information wherever they are, rather than have to stay put at their desk. E. Allows IT to Shift Focus: The supervision organization will concentrate on innovation rather than worrying about constant server updates and other compute issue. In addition of some limitations are also provided in [8] are: GNU founder Richard Stallman says that the interesting thing about cloud computing is that we've redefined cloud computing to include everything that we previously do. One reason you should not utilize web application to do your computing is that you lose control. This one is as terrible as using a proprietary program [8]. The shifting to cloud computing certainly has other problems including: A. Security: Is there a security standard? B. Reliance on 3rd Party: Control over own data is lost in the hands of a difficult-to-trust provider. C. Cost of transition: Is it feasible for me to move from the existing architecture of my data center to the architecture of the cloud? D. Uncertainty of benefits: Are there any long term benefits? III. TECHNIQUES OF GREEN COMPUTING There are a number of techniques are developed recently for supporting the green computing concept. This section provides the different approaches to reduce power, in computational and storage environment. 3.1 Virtualization Instead of having one computer for each service or for a group of services, one can consolidate each server onto a larger virtualized system that uses its resources to the fullest, and has a much smaller energy trace. These benefits in several ways: [9] 1. It reduces the total amount of hardware used in your environment 2. Idle Virtual servers can be powered off 3. The virtualized server will have much less idle time and waste less 4. The Data centers can use up to 100 times the energy per square foot of typical office space. 5. Some power companies pay rebates for conversion to virtualized systems. There is a strong connection between virtualization, performance management and capacity planning, because of the extreme performance requirements that are placed on virtual servers. Once in place, virtual systems have a unique power flexibility that allows for power consolidation, efficiency, and ability to power-off idle systems. Numerous business companies and open-source projects at this instant suggest software packages to enable a move to virtual computing [10]. The large server can "host" many such "guest" virtual machines. This is known as Physical-to-Virtual (P2V) transformation. Virtual machine can be more easily controlled and inspected from outside than a physical one, its configuration is also more flexible. The technique is very important for teaching operating system courses and in kernel development. 102

Practical requirement of data centers are as follows: Provide a physical secure location for server. Should provide all-time network connectivity in data center. Should provide necessary power to operate all equipment. Figure 2.1 cloud infrastructure 3.2 Green Data Center Data centers or computer center has a computer system and its associated system such as telecommunication system data storage system. It needs backup power supply, some cooling system and security system. A green data center is a data center which has a efficient management of the system and associated system less power consumed environment. Characteristics Design must be simple Design must be scalable: Design should be scalable because once it finalize must work for any size of computer center. Design must be modular. Design must be flexible. 3.3 Green Data Center Background In IDC, there are two kinds of Virtualization technologies that are studied a lot recently. One is fullvirtualization technology, such as VMWare [11]. Fullvirtualization, otherwise known as native virtualization, uses a virtual machine that mediates between the guest operating systems and the native hardware. This approach obviates the need for any recompilation or trapping because the operating systems themselves cooperate in the virtualization process. A typical para-virtualization product is Xen [12] Figure 2.2 virtualization benefits 103

While various management strategies have been developed to effectively reduce server power consumption by transitioning hardware components to lower-power states, they cannot be directly applied to today s data centers that rely on virtualization technologies. In [13], Chen et al. have proposed ON/OFF control strategies to investigate the optimization of energy saving with desired performance levels. Nathuji et al. [14] have proposed an online power management to support the isolated and independent operation assumed by VMs running on a virtualized platform and globally coordinate the diverse power management strategies applied by the VMs to the virtualized resource. In order to map the soft power state to the actual changes of the underlying virtualized resource, the Virtual Power Management (VPM) state, channels, mechanisms, and rules are implemented as the multiple system level abstraction. In the early research, the Collective project [15], has designed VM migration as a tool to provide mobility to users who work on different physical machines at different times. With a set of enhancement work to reduce the image size, it will stop the running of the VM during the migration duration. Zap [16], which implement the partial virtualization technology to enable the migration of process domains, using a modified Linux Kernel. Figure 2.3GreenCloud Architecture Recently, researchers have noticed the performance deterioration brought out by the traditional VM migration, which may lead to service unavailable during the period of the migration, which could not be acceptable in a performance-sensitive computing environment. To address this challenge, NomadBIOS [17], which is a virtualization and migration technology built on top of the L4 microkernel [18], implements pre-copy migration to achieve very short best-case migration downtimes. Later, with the research of live migration conducted by Clark, the latest version of Xen now supports the live migration of VM [19] [10]. IV. RECENT CONTRIBUTIONS In this section different contribution on green computing and their performance enhancement techniques are considered and reported. Cloud computing is emerging as a new paradigm of large-scale distributed computing. Load balancing is one of the main challenges in cloud computing which is required to distribute the dynamic workload across multiple nodes to ensure that no single node is overwhelmed. It helps in optimal utilization of resources and hence in enhancing the performance of the system. 104

The goal of load balancing is to minimize the resource consumption which will further reduce energy consumption and carbon emission rate that is the dire need of cloud computing. This determines the need of new metrics, energy consumption and carbon emission for energyefficient load balancing in cloud computing. Nidhi Jain Kansal et al [20] discusses the existing load balancing techniques in cloud computing and further compares them based on various parameters like performance, scalability, associated overhead etc. that are considered in different techniques. It further discusses these techniques from energy consumption and carbon emission perspective. Until now, green computing research has largely relied on few, short-term power measurements to characterize the energy use of enterprise computing. Maria Kazandjieva et al [21] bring new and comprehensive power datasets through Power-net, a hybrid sensor network that monitors the power and utilization of the IT systems in a large academic building. Over more than two years, we have collected power data from 250+individual computing devices and have monitored a subset of CPU and network loads. Given datasets provide an opportunity to examine assumptions commonly made in green computing. They show that power variability both between similar devices and over time for a single device can lead to cost or savings estimates that are off by 15-20%. Extending the coverage of measured devices and the duration (to at least one month) significantly reduces errors. Author provides several methodology guidelines for future green computing research. Data centers now play an important role in modern IT infrastructures. Lizhe Wang et al [22]is devoted to categorization of green computing performance metrics in data centers,such as basic metrics like power metrics, thermal metrics and extended performance metrics i.e. multiple data center indicators. Based on taxonomy of performance metrics, this paper summarizes features of currently available metrics and presents insights for the study on green data center computing. With the wide popularity of distributed and cloud computing a new major concern arise with respect to how green such technologies are. Naseem Ibrahim et al [23]are concerned with providing services over the cloud that are energy-aware. To achieve this goal this paper presents a novel extended service oriented architecture and a novel formal service model. The architecture and the service model extend traditional service oriented architectures to be support context information and mainly location information. Information and Communication Technology (ICT) isthe core element of any organizations green strategy. ICT is related with every aspect of our lives. Ms.Priya Chandran et al [24] describes how ICT can play a very important role in moving towards the environmental sustainability and how it is benefiting from developments in nano technology. They have proposed an architectural model for organizations to move towards green computing. V. PROPOSED WORK Thus in this proposed work for improving the performance cloud computing and enhancing eco-friendly effect an effort is made and the entire investigation of green computing and a new technique development is demonstrated. In order to achieve green computing and reducing the power consumption of the computational cloud environment required to schedule the VM (virtual machine)efficiently. Thus the following tasks are included for investigation and simulation. 1. Study of green computing and their need: in this phase about the green computing and their negative effects are studied for better understanding of need of green computing. 2. Study of different approaches to achieve green computing: in this phase the different techniques available for reducing the power consumption in computational cloud is studied and most optimum technique is investigated for extension. 3. Implement and simulate new manner of reducing energy consumption: in this phase the selected technique is extended and a new technique is explored. Additionally for simulating the effect of power consumption a simulation using CloudSim is developed in this phase. 4. Comparative performance study: after completing the simulation the performance of the proposed technique is compared with the traditionally available MAD (median absolute deviation) technique. VI. EXPECTED OUTCOMES After successfully implementation of the proposed virtual scheduling technique the following outcomes are expected from the system. 1. A rich collection of green computing: during study and literature collection a significant amount of research papers and articles on green computing and their obtaining methodology is collected. 105

2. Implementation and simulation of enhance power consumption:for simulating the power optimization and consumption a simulation is prepared using the simulation tool and JAVA technology. 3. Comparative performance study of existing and proposed technique: the comparative performance is investigated with respect to the traditional MAD (median absolute deviation) technique. VII. CONCLUSION The cloud computing infrastructure helps in efficient computation, data hosting and other various tasks. On the other hand the cloud systems are affected with the huge amount of power consumption. Thus a new computational branch of the cloud is established as the green computing which keep in track the power consumption and green effect of the computational cloud. Therefore in this presented work the VM scheduling is enhanced using the Spear man's rank correlation coefficient technique. And the comparative performance is analyzed with respect to the MAD (median absolute deviation) technique. REFERENCES [1] Zhiwu Liu, Ruhui Ma, Fanfu Zhou, Yindong Yang, Zhengwei Qi, Haibing Guan Power-aware I/O- Intensive and CPU-Intensive Applications Hybrid Deployment within Virtualization Environments IEEE 2010. [2] R.Yamini, Assistant Professor Power Management in Cloud Computing Using Green Algorithm (ICAESM-2012) MARCH 2012. [3] Wang, D., Meeting Green Computing Challenges, Proceeding of the International Symposium on High Density Packaging and Microsystem Integration, 2007 (HDP 07), IEEE, 2007. [4] Zhiwu Liu, Ruhui Ma, Fanfu Zhou, Yindong Yang, Zhengwei Qi, Haibing Guan Power-aware I/O- Intensive and CPU-Intensive Applications Hybrid Deployment within Virtualization Environments IEEE 2010. [5] Alexa Huth and James Cebula, The Basics of Cloud Computing, 2011 Carnegie Mellon University, Produced for US- CERT. [6] Introduction to Cloud Computing, White Paper, Dialogic, 2013 [7] Nariman Mirzaei, Cloud Computing, Community Grids Lab, Indiana University Pervasive Technology Institute 2008. [8] Mike Ricciuti, Stallman: Cloud computing is stupidity, http://news.cnet.com/8301-1001_3-10054253-92.html. [9] Eun Kyung Lee, Hariharasudhan Viswanathan, and Dario Pompili, VMAP: Proactive Thermal-aware Virtual Machine Allocation in HPC Cloud Datacenters, This work was supported by the NSF Award No. CSR-1117263 [10] Mayank Mishra, Sujesha Sudevalayam, Introduction to Cloud Computing and Virtualization,http://www.cse.iitb.ac.in/convergence/workshops/Intr o_to_virtualization.pdf [11] VMWare, VMWare Inc. http://www.vmware.com [12] Xen User Manual, http:// bits.xensource.com/xen/docs/user.pdf. [13] Tremulous official website, http://tremulous.net [14] R. Nathuji, K. Schwan, "VirtualPower: coordinated power management in virtualized enterprise systems", ACM Symposium on Operating Systems Principles, Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles, 2007. [15] C. P. Sapuntzakis, R. Chandra, B. Pfaff, J. Chow, M. S. Lam, M.Rosenblum. Optimizing the migration of virtual computers. In Proc. of the 5th Symposium on Operating Systems Design and Implementation (OSDI-02), December 2002. [16] S. Osman, D. Subhraveti, G. Su, J. Nieh. The design and implementation of zap: A system for migrating computing environments. In Proc. 5th USENIX Symposium on Operating Systems Design and Implementation (OSDI-02), pages 361 376, December 2002 [17] J. G. Hansen, A. K. Henriksen. Nomadic operating systems. Master's thesis, Dept. of Computer Science, University of Copenhagen, Denmark, 2002. [18] H. H artig, M. Hohmuth, J. Liedtke, S. Sch onberg. The performance of microkernel-based systems. In Proceedings of the sixteenth ACM Symposium on Operating System Principles, pages 66 77. ACM Press, 1997. [19] C. Clark, K. Fraser, S. Hand, J. Hansen, E. Jul, C. Limpach, I. Pratt, and A. Warfield. Live migration of Virtual Machines. In USENIX NSDI, 2005. [20] Nidhi Jain Kansal, Inderveer Chana, Cloud Load Balancing Techniques : A Step Towards Green Computing, IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 1, No 1, January 2012 [21] Maria Kazandjieva, Brandon Heller, Omprakash Gnawali, Philip Levis, and Christos Kozyrakis, Green Enterprise Computing Data: Assumptions and Realities, 978-1-4673-2154-9/12/$31.00 c 2012 IEEE [22] Lizhe Wang, Samee U. Khan, Review of performance metrics for green data centers: a taxonomy study, Springer Science+Business Media, LLC 2011 [23] Naseem Ibrahim, Towards Green Service-oriented Computing, ISBN: 978-0-9891305-3-0 2013 SDIWC [24] Ms. Priya Chandran, Dr. Vaishali Patil, Green Computing Technologies towards the Development of ICT: A Critical Study, Proceedings of National Conference on Emerging Trends: Innovations and Challenges in IT, 19-20, April 2013. 106