Proactive Scheduling in Cloud Computing

Autonomic fault aware scheduling is a feature quite important for cloud computing and it is related to adoption of workload variation. In this context, this paper proposes an fault aware pattern matching autonomic scheduling for cloud computing based on autonomic computing concepts.  In order to validate  the proposed solution, we performed two experiments one with traditional approach and other other with pattern recognition fault aware approach. The results show the effectiveness of the scheme.

[1]  Satya Prakash Ghrera,et al.  Load and Fault Aware Honey Bee Scheduling Algorithm for Cloud Infrastructure , 2014, FICTA.

[2]  Rajkumar Buyya,et al.  Fault-tolerant Workflow Scheduling using Spot Instances on Clouds , 2014, ICCS.

[3]  Sandeep Sharma,et al.  A Comparative Review on Fault Tolerance methods and models in Cloud Computing , 2016 .

[4]  J. Singh,et al.  High Availability of Clouds: Failover Strategies for Cloud Computing Using Integrated Checkpointing Algorithms , 2012, 2012 International Conference on Communication Systems and Network Technologies.

[5]  Amal Ganesh,et al.  A study on fault tolerance methods in Cloud Computing , 2014, 2014 IEEE International Advance Computing Conference (IACC).

[6]  Gang Chen,et al.  SHelp: Automatic Self-Healing for Multiple Application Instances in a Virtual Machine Environment , 2010, 2010 IEEE International Conference on Cluster Computing.

[7]  Pabitra Mohan Khilar,et al.  VFT: A virtualization and fault tolerance approach for cloud computing , 2013, 2013 IEEE CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES.

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

[9]  Mohammed Amoon.  A framework for providing a hybrid fault tolerance in cloud computing , 2015, 2015 Science and Information Conference (SAI).

[10]  Raouf Boutaba,et al.  Cloud computing: state-of-the-art and research challenges , 2010, Journal of Internet Services and Applications.

[11]  Angelos D. Keromytis,et al.  ASSURE: automatic software self-healing using rescue points , 2009, ASPLOS.

[12]  Rajkumar Buyya,et al.  A framework for ranking of cloud computing services , 2013, Future Gener. Comput. Syst..

[13]  K. Chandrasekaran,et al.  Essentials of Cloud Computing , 2014 .

[14]  Inderveer Chana,et al.  Autonomic fault tolerant scheduling approach for scientific workflows in Cloud computing , 2015, Concurr. Eng. Res. Appl..

[15]  Arshdeep Bahga,et al.  Cloud Computing: A Hands-On Approach , 2013 .

[16]  Gautam Shroff.  Enterprise Cloud Computing: Technology, Architecture, Applications , 2010 .