CHOPPER: an intelligent QoS-aware autonomic resource management approach for cloud computing

Cloud computing is the future generation of computational services delivered over the Internet. As cloud infrastructure expands, resource management in such a large heterogeneous and distributed environment is a challenging task. In a cloud environment, uncertainty and dispersion of resources encounters problems of allocation of resources. Unfortunately, existing resource management techniques, frameworks and mechanisms are insufficient to handle these environments, applications and resource behaviors. To provide an efficient performance and to execute workloads, there is a need of quality of service (QoS) based autonomic resource management approach which manages resources automatically and provides reliable, secure and cost efficient cloud services. In this paper, we present an intelligent QoS-aware autonomic resource management approach named as CHOPPER (Configuring, Healing, Optimizing and Protecting Policy for Efficient Resource management). CHOPPER offers self-configuration of applications and resources, self-healing by handling sudden failures, self-protection against security attacks and self-optimization for maximum resource utilization. We have evaluated the performance of the proposed approach in a real cloud environment and the experimental results show that the proposed approach performs better in terms of cost, execution time, SLA violation, resource contention and also provides security against attacks.

[1]  Inderveer Chana,et al.  QoS-Aware Autonomic Resource Management in Cloud Computing , 2015, ACM Comput. Surv..

[2]  Inderveer Chana,et al.  EARTH: Energy-aware autonomic resource scheduling in cloud computing , 2016, J. Intell. Fuzzy Syst..

[3]  Inderveer Chana,et al.  QoS-aware Autonomic Cloud Computing for ICT , 2016 .

[4]  Maninder Singh,et al.  The Journey of QoS-Aware Autonomic Cloud Computing , 2017, IT Professional.

[5]  Sushil Kumar Sah,et al.  Scalability of efficient and dynamic workload distribution in autonomic cloud computing , 2014, 2014 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT).

[6]  Bradley R. Schmerl,et al.  Architecture-based self-protecting software systems , 2013, QoSA '13.

[7]  Abul Bashar,et al.  Autonomic scaling of Cloud Computing resources using BN-based prediction models , 2013, 2013 IEEE 2nd International Conference on Cloud Networking (CloudNet).

[8]  Rajkumar Buyya,et al.  SOCCER: Self-Optimization of Energy-efficient Cloud Resources , 2016, Cluster Computing.

[9]  Wei Zhang,et al.  ARAS-M: Automatic Resource Allocation Strategy based on Market Mechanism in Cloud Computing , 2011, J. Comput..

[10]  Inderveer Chana,et al.  QRSF: QoS-aware resource scheduling framework in cloud computing , 2014, The Journal of Supercomputing.

[11]  Salim Hariri,et al.  Autonomic power and performance management for computing systems , 2006, 2006 IEEE International Conference on Autonomic Computing.

[12]  Guangzhi Qu,et al.  Self-Protection against Attacks in an Autonomic Computing Environment , 2009, Int. J. Comput. Their Appl..

[13]  Inderveer Chana,et al.  Efficient cloud workload management framework , 2013 .

[14]  Sornthep Vannarat,et al.  Autonomic resource provisioning in rocks clusters using Eucalyptus cloud computing , 2010, MEDES.

[15]  Rajkumar Buyya,et al.  Aneka: Next-Generation Enterprise Grid Platform for e-Science and e-Business Applications , 2007, Third IEEE International Conference on e-Science and Grid Computing (e-Science 2007).

[16]  Yang Liu,et al.  Collaborative Security , 2015, ACM Comput. Surv..

[17]  Asit Dan,et al.  Web services agreement specification (ws-agreement) , 2004 .

[18]  D. Tsoumakos,et al.  COCCUS: self-configured cost-based query services in the cloud , 2013, SIGMOD '13.

[19]  Christine Morin,et al.  Snooze: A Scalable and Autonomic Virtual Machine Management Framework for Private Clouds , 2012, 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012).

[20]  Rizos Sakellariou,et al.  Adaptive resource configuration for Cloud infrastructure management , 2013, Future Gener. Comput. Syst..

[21]  Palden Lama,et al.  AROMA: automated resource allocation and configuration of mapreduce environment in the cloud , 2012, ICAC '12.

[22]  Ahmad Mosallanejad,et al.  A HIERARCHICAL SELF-HEALING SLA FOR CLOUD COMPUTING , 2014 .

[23]  Fabrice Huet,et al.  Adaptive Fault Tolerance in Real Time Cloud Computing , 2011, 2011 IEEE World Congress on Services.

[24]  David Sinreich,et al.  An architectural blueprint for autonomic computing , 2006 .

[25]  Lucio Grandinetti,et al.  Autonomic resource contention‐aware scheduling , 2015, Softw. Pract. Exp..

[26]  Cheng-Zhong Xu,et al.  Coordinated Self-Configuration of Virtual Machines and Appliances Using a Model-Free Learning Approach , 2013, IEEE Transactions on Parallel and Distributed Systems.

[27]  Marimuthu Palaniswami,et al.  Internet of Things (IoT): A vision, architectural elements, and future directions , 2012, Future Gener. Comput. Syst..

[28]  Maninder Singh,et al.  SHAPE—an approach for self-healing and self-protection in complex distributed networks , 2013, The Journal of Supercomputing.

[29]  Sakshi Patil STAR: SLA-Aware Autonomic Management of Cloud Resources , 2018 .

[30]  Noel De Palma,et al.  Autonomic Management for Grid Applications , 2008, 16th Euromicro Conference on Parallel, Distributed and Network-Based Processing (PDP 2008).

[31]  Laurent Lefèvre,et al.  Exploiting performance counters to predict and improve energy performance of HPC systems , 2014, Future Gener. Comput. Syst..

[32]  Noel De Palma,et al.  Component-Based Autonomic Management for Legacy Software , 2009, Autonomic Computing and Networking.

[33]  Thierry Monteil,et al.  Non-Intrusive Autonomic Approach with Self-Management Policies Applied to Legacy Infrastructures for Performance Improvements , 2011, Int. J. Adapt. Resilient Auton. Syst..

[34]  Noel De Palma,et al.  Autonomic management policy specification in Tune , 2008, SAC '08.

[35]  Rajkumar Buyya,et al.  CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms , 2011, Softw. Pract. Exp..

[36]  Inderveer Chana,et al.  Q-aware: Quality of service based cloud resource provisioning , 2015, Comput. Electr. Eng..

[37]  Rajkumar Buyya,et al.  Towards autonomic detection of SLA violations in Cloud infrastructures , 2012, Future Gener. Comput. Syst..

[38]  Inderveer Chana,et al.  Resource provisioning and scheduling in clouds: QoS perspective , 2016, The Journal of Supercomputing.

[39]  José Simão,et al.  Partial Utility-Driven Scheduling for Flexible SLA and Pricing Arbitration in Clouds , 2016, IEEE Transactions on Cloud Computing.

[40]  Valeria Cardellini,et al.  SLA-aware Resource Management for Application Service Providers in the Cloud , 2011, 2011 First International Symposium on Network Cloud Computing and Applications.

[41]  Inderveer Chana,et al.  Quality of Service and Service Level Agreements for Cloud Environments: Issues and Challenges , 2014 .

[42]  Jie Li,et al.  Cloud auto-scaling with deadline and budget constraints , 2010, 2010 11th IEEE/ACM International Conference on Grid Computing.