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

2016 ◽  
Vol 6 (3) ◽  
pp. 1023
Author(s):  
Choudhury Nishikanta Sahoo ◽  
Veena Goswami
Keyword(s):  
Admission Control ◽  
Virtual Machines ◽  
Control Policy ◽  
Service Rate ◽  
Model Parameters ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Tier System ◽  
Mission Critical ◽  
Admission Control Policy

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

2016 ◽  
Vol 6 (3) ◽  
pp. 1023
Author(s):  
Choudhury Nishikanta Sahoo ◽  
Veena Goswami
Keyword(s):  
Admission Control ◽  
Virtual Machines ◽  
Control Policy ◽  
Service Rate ◽  
Model Parameters ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Tier System ◽  
Mission Critical ◽  
Admission Control Policy

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.

scholarly journals OPTIMAL ADMISSION CONTROL IN QUEUES WITH WORKLOAD-DEPENDENT SERVICE RATES

2006 ◽  
Vol 20 (4) ◽  
pp. 543-570 ◽  
Author(s):  
René Bekker ◽  
Sem C. Borst
Keyword(s):  
Admission Control ◽  
Production Systems ◽  
Control Policy ◽  
Threshold Value ◽  
Service Rate ◽  
Qualitative Behavior ◽  
Threshold Policy ◽  
Long Run ◽  
Service Rates ◽  
Admission Control Policy

We consider a queuing system with a workload-dependent service rate. We specifically assume that the service rate is first increasing and then decreasing as a function of the amount of work. The latter qualitative behavior is quite common in practical situations, such as production systems. The admission of work into the system is controlled by a policy for accepting or rejecting jobs, depending on the state of the system. We seek an admission control policy that maximizes the long-run throughput. Under certain conditions, we show that a threshold policy is optimal, and we derive a criterion for determining the optimal threshold value.

scholarly journals Client Aware Scalable Cloudlet to Augment Edge Computing with Mobile Cloud Migration Service

2020 ◽  
Vol 14 (12) ◽  
pp. 165
Author(s):  
Uma Nandhini D ◽  
Udhayakumar S ◽  
Latha Tamilselvan ◽  
Silviya Nancy J
Keyword(s):  
Wireless Lan ◽  
High Speed ◽  
Virtual Machines ◽  
Linear Regression Analysis ◽  
Mobile Cloud ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Battery Lifetime ◽  
Network Bandwidth ◽  
Load Conditions

<p class="0abstract">Computing with mobile is still in its infancy due to its limitations of computational power, battery lifetime and storage capacity. These limitations hinder the growth of mobile computing, which in-turn affects the growth of computationally intensive applications developed for the mobile devices. So in-order to help execute complex applications within the mobile device, mobile cloud computing (MCC) emerged as a feasible solution. The job of offloading the task to the cloud data center for storage and execution from the mobile seems to gain popularity, however, issues related to network bandwidth, loss of mobile data connectivity, and connection setup does not augment well to extend the benefits offered by MCC. Cloudlet servers filled this gab by assisting the mobile cloud environment as an edge device, offering compute power to the connected devices with high speed wireless LAN connectivity. Implementation constraints of cloudlet faces severe challenges in-terms of its storage, network sharing, and VM provisioning. Moreover, the number of connected devices of the cloudlet and its load conditions vary drastically leading to unexpected bottleneck, in which case the availability to server becomes an issue. Therefore, a scalable cloudlet, Client Aware Scalable Cloudlet (CASC) is proposed with linear regression analysis, predicting the knowledge of expected load conditions for provisioning new virtual machines and to perform resource migration.</p>

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