Preemptable priority based dynamic resource allocation in cloud computing with fault tolerance

Today, cloud computing serves as a request response model, where a client makes request for various available services on “pay as you go basis”. Cloud computing offers a dynamic flexible resource allocation phenomenon. For reliable and guaranteed services there must be a scheduling mechanism that all resources are efficiently allocated to satisfy the customer's request. Cloud services are based on scalability, availability, security and fault tolerance features. Service provisioning in cloud is based on SLA. Service level agreement is the terms of cloud provider's contracts with customers to define the level(s) of service being sold in plain language terms. QoS (quality of service) plays important role in cloud environment. Resource scheduling and service deployment is done by considering multiple SLA parameters like CPU requirement, network bandwidth, memory and storage. In this paper we propose an algorithm which perform resource preemption from low priority task to high priority task and advanced reservation for resources considering multiple SLA parameters for deploying service. This algorithm is also effective for fault tolerance mechanism.

[1]  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..

[2]  Vincenzo Piuri,et al.  Fault Tolerance Management in Cloud Computing: A System-Level Perspective , 2013, IEEE Systems Journal.

[3]  Kwang Mong Sim,et al.  Agent-Based Adaptive Resource Allocation on the Cloud Computing Environment , 2011, 2011 40th International Conference on Parallel Processing Workshops.

[4]  Meikang Qiu,et al.  Adaptive resource allocation for preemptable jobs in cloud systems , 2010, 2010 10th International Conference on Intelligent Systems Design and Applications.

[5]  Rajkumar Buyya,et al.  A Particle Swarm Optimization-Based Heuristic for Scheduling Workflow Applications in Cloud Computing Environments , 2010, 2010 24th IEEE International Conference on Advanced Information Networking and Applications.

[6]  Oscar H. Ibarra,et al.  Heuristic Algorithms for Scheduling Independent Tasks on Nonidentical Processors , 1977, JACM.

[7]  Jan Janecek,et al.  A high performance, low complexity algorithm for compile-time task scheduling in heterogeneous systems , 2004, 18th International Parallel and Distributed Processing Symposium, 2004. Proceedings..

[8]  Ivona Brandic Towards Self-Manageable Cloud Services , 2009, 2009 33rd Annual IEEE International Computer Software and Applications Conference.

[9]  Zhen Xiao,et al.  Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Environment , 2013, IEEE Transactions on Parallel and Distributed Systems.

[10]  Ivona Brandic,et al.  SLA-Aware Application Deployment and Resource Allocation in Clouds , 2011, 2011 IEEE 35th Annual Computer Software and Applications Conference Workshops.

[11]  Schahram Dustdar,et al.  Low level Metrics to High level SLAs - LoM2HiS framework: Bridging the gap between monitored metrics and SLA parameters in cloud environments , 2010, 2010 International Conference on High Performance Computing & Simulation.

[12]  Abdallah Khreishah,et al.  Resource Planning for Parallel Processing in the Cloud , 2011, 2011 IEEE International Conference on High Performance Computing and Communications.

[13]  Rajnikant B. Wagh,et al.  Priority Based Dynamic Resource Allocation In Cloud Computing , 2017 .

[14]  Albert Y. Zomaya,et al.  Profit-Driven Service Request Scheduling in Clouds , 2010, 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing.

[15]  R. B. Wagh,et al.  Priority based dynamic resource allocation in Cloud computing with modified waiting queue , 2013, 2013 International Conference on Intelligent Systems and Signal Processing (ISSP).

[16]  Bernd Freisleben,et al.  Virtual Machine Resource Allocation in Cloud Computing via Multi-Agent Fuzzy Control , 2013, 2013 International Conference on Cloud and Green Computing.

[17]  Stefan Kuhr,et al.  Department of Mathematics and Computer Science , 2002 .