Dynamic control and Resource management for Mission Critical Multi-tier Applications in Cloud Data Center

The multi-tier architecture style has become an industry standard in modern data centers with each tier providing certain functionality. To avoid congestion and to adhere the SLA under fluctuating workload and unpredictable failures of Mission Critical Multi-tier applications hosted in the cloud, we need a Dynamic admission control policy, such that the requests must be processed from the first tier to the last without any delay. This paper presents the least strict admission control policy, which will induce the maximal throughput, for a two-tier system with parallel servers. We propose an optimization model to minimize the total number of virtual machines for computing resources in each tier by dynamically varying the mean service rate of the VMs. Some performance indicators and computational results showing the effect of model parameters are presented. This model is also applicable to priority as well as real-time based applications in Cloud based environment.

Dynamic control and Resource management for Mission Critical Multi-tier Applications in Cloud Data Center

The multi-tier architecture style has become an industry standard in modern data centers with each tier providing certain functionality. To avoid congestion and to adhere the SLA under fluctuating workload and unpredictable failures of Mission Critical Multi-tier applications hosted in the cloud, we need a Dynamic admission control policy, such that the requests must be processed from the first tier to the last without any delay. This paper presents the least strict admission control policy, which will induce the maximal throughput, for a two-tier system with parallel servers. We propose an optimization model to minimize the total number of virtual machines for computing resources in each tier by dynamically varying the mean service rate of the VMs. Some performance indicators and computational results showing the effect of model parameters are presented. This model is also applicable to priority as well as real-time based applications in Cloud based environment.