Power Curtailment in Cloud Environment Utilising Load Balancing Machine Allocation

Cloud computing is a new technology to provide services users on the Internet. Companies providing services in this area are trying to offer attractive solutions and services business with the slogan desire to use this technology to reduce operating costs and increase their endurance. The increasing use of cloud computing with great benefits, also faces challenges as the most important of which can be noted consumable supplies. Load balancing algorithms are several parameters that can be used by the utility and productivity of the most important features to regard power consumption will be given. In this paper, a method based on network load balancing to optimize the energy consumption by using Dynamic Voltage and Frequency Scaling (DVFS). Load balancing algorithms and power energy management are absence maximum of workloads in the data center for service. This algorithm given time intervals by monitoring utilization rates of server hosts, the hosts have the additional burden reduction and load them into hosts with little time has passed.

[1]  Jing Yao,et al.  Load balancing strategy of cloud computing based on artificial bee algorithm , 2012, 2012 8th International Conference on Computing Technology and Information Management (NCM and ICNIT).

[2]  Ruth C. Carter,et al.  Principles , 2003, Law’s Reality.

[3]  Jie Wu,et al.  Achieving reliable and secure services in cloud computing environments , 2017, Comput. Electr. Eng..

[4]  K. Bergman,et al.  Optically interconnected data center architecture for bandwidth intensive energy efficient networking , 2012, 2012 14th International Conference on Transparent Optical Networks (ICTON).

[5]  Shakir Khan,et al.  Using cloud computing to improve network operations and management , 2015, 2015 5th National Symposium on Information Technology: Towards New Smart World (NSITNSW).

[6]  Ulas C. Kozat,et al.  Dynamic resource allocation and power management in virtualized data centers , 2010, 2010 IEEE Network Operations and Management Symposium - NOMS 2010.

[7]  Burak Kantarci,et al.  Communication Infrastructures for Cloud Computing , 2013 .

[8]  M. Ajit,et al.  VM level load balancing in cloud environment , 2013, 2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT).

[9]  A. Kartit,et al.  A taxonomy and survey of Cloud computing , 2013, 2013 National Security Days (JNS3).

[10]  Rajkumar Buyya,et al.  Energy Efficient Resource Management in Virtualized Cloud Data Centers , 2010, 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing.

[11]  Rajkumar Buyya,et al.  Article in Press Future Generation Computer Systems ( ) – Future Generation Computer Systems Cloud Computing and Emerging It Platforms: Vision, Hype, and Reality for Delivering Computing as the 5th Utility , 2022 .

[12]  Guojun Wang,et al.  Feature Selection and Intrusion Detection in Cloud Environment Based on Machine Learning Algorithms , 2017, 2017 IEEE International Symposium on Parallel and Distributed Processing with Applications and 2017 IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC).

[13]  Liang Liu,et al.  Energy efficient scheduling of virtual machines in cloud with deadline constraint , 2015, Future Gener. Comput. Syst..

[14]  Amir Javadpour,et al.  A wearable medical sensor for provisional healthcare , 2015, 2015 2nd International Symposium on Physics and Technology of Sensors (ISPTS).

[15]  A Javadpour,et al.  Implementing a Smart Method to Eliminate Artifacts of Vital Signals , 2015, Journal of biomedical physics & engineering.

[16]  Chuang Lin,et al.  Delay guaranteed live migration of Virtual Machines , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[17]  Berthold Bitzer,et al.  Cloud computing framework for smart grid applications , 2013, 2013 48th International Universities' Power Engineering Conference (UPEC).

[18]  Zibin Zheng,et al.  BFTCloud: A Byzantine Fault Tolerance Framework for Voluntary-Resource Cloud Computing , 2011, 2011 IEEE 4th International Conference on Cloud Computing.

[19]  Farshad Lahouti,et al.  Automatic fault detection and diagnosis in cellular networks using operations support systems data , 2016, NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium.

[20]  Aameek Singh,et al.  Server-storage virtualization: Integration and load balancing in data centers , 2008, 2008 SC - International Conference for High Performance Computing, Networking, Storage and Analysis.

[21]  Amir Javadpour,et al.  A temperature monitoring system incorporating an array of precision wireless thermometers , 2015, 2015 International Conference on Smart Sensors and Application (ICSSA).

[22]  Issa M. Khalil,et al.  Cloud Computing Security: A Survey , 2014, Comput..

[23]  Mehdi Esnaashari,et al.  Data Storages in Wireless Sensor Networks to Deal With Disaster Management , 2019, Emergency and Disaster Management.

[24]  Kavic Ms.  World Congress , 1970 .

[25]  Wei Zhang,et al.  MAPP: A Modular Arithmetic Algorithm for Privacy Preserving in IoT , 2017, 2017 IEEE International Symposium on Parallel and Distributed Processing with Applications and 2017 IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC).

[26]  Xiaoning Zhang,et al.  Power-Efficient Provisioning for Online Virtual Network Requests in Cloud-Based Data Centers , 2015, IEEE Systems Journal.

[27]  Yang Li,et al.  Sustainable and Efficient Data Collection from WSNs to Cloud , 2019, IEEE Transactions on Sustainable Computing.

[28]  Sven Helmer,et al.  Affordable and Energy-Efficient Cloud Computing Clusters: The Bolzano Raspberry Pi Cloud Cluster Experiment , 2013, 2013 IEEE 5th International Conference on Cloud Computing Technology and Science.

[29]  Alfio Lombardo,et al.  A Model-Assisted Cross-Layer Design of an Energy-Efficient Mobile Video Cloud , 2014, IEEE Transactions on Multimedia.

[30]  Xiaoyu Yang.  Principles, Methodologies, and Service-Oriented Approaches for Cloud Computing , 2013 .

[31]  Jie Wu,et al.  Effective Query Grouping Strategy in Clouds , 2017, Journal of Computer Science and Technology.

[32]  Rajkumar Buyya,et al.  Energy-aware simulation with DVFS , 2013, Simul. Model. Pract. Theory.

[33]  Massoud Pedram,et al.  Energy-Efficient Datacenters , 2012, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[34]  Rajkumar Buyya,et al.  Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in Cloud data centers , 2012, Concurr. Comput. Pract. Exp..

[35]  Norman W. Paton,et al.  Optimizing virtual machine placement for energy and SLA in clouds using utility functions , 2016, Journal of Cloud Computing.

[36]  Jin Heo,et al.  Understand and replay cloud platform SDK with vimShark , 2011, 2011 International Conference on Cloud and Service Computing.

[37]  T. K. Ghosh,et al.  Load balanced static grid scheduling using Max-Min heuristic , 2012, 2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing.

[38]  Omran Malik Omer Awad,et al.  Cloud computing versus in-house clusters: a comparative study , 2014, 2014 World Congress on Computer Applications and Information Systems (WCCAIS).