Application-Aware Migration Algorithm with Prefetching in Heterogeneous Cloud Environments
Abstract : Inappropriate service migrations can lead to undesirable situations, such as high traffic overhead, long service latency, and service disruption. In this paper, we propose an application-aware migration algorithm (AMA) with prefetching. In AMA, a mobile device sends a service offloading request to the controller. After receiving this request, the controller determines the initial service cloud where virtual machine (VM) of the service initially operates by considering the application type. In addition, it periodically decides where to migrate VM and prefetch its core part considering the mobility of the mobile device and application type. To minimize the generated traffic volume while satisfying the requirements of the application, a constraint Markov decision process (CMDP) is formulated and its optimal policy is obtained via linear programming. Evaluation results demonstrate that AMA with the optimal policy can reduce the generated traffic volume while satisfying the requirements of the application (i.e., service latency and probability of service disruption).
? This analysis reveals the existing gap in those approaches in terms of the migration downtime (performance), decoupling VMs from underlying systems (flexibility) and securing live migration channel (security).
? The book provides case studies of numerous existing compute, storage, and application cloud services and illustrates capabilities and limitations of current providers of cloud computing services.
? In most cases, establishing a private cloud means restructuring an existing infrastructure by adding virtualization and cloud-like interfaces.
? At the same time, existing, wellunderstood technologies can be leveraged, such as data encryption, VLANs, and firewalls.
? This paper addresses the issues mentioned above by introducing a resource management algorithm, called resource utilization-aware VM migration (RU-VMM) algorithm, to distribute the loads among the overloaded and underloaded vehicles, such that energy consumption is minimized.
? With an increase in popularity, VCC also faces various notable problems, such as resource management, energy consumption, bandwidth, latency and many more.
? Researchers have explored different dimensions of VCC to address the above-mentioned problems.
? Therefore, minimizing the energy consumption of the VMs that are hosted by both overloaded and underloaded is a challenging issue in the VCC environment.
• This paper focuses on analysing recently proposed live, cloud migration approaches for VMs at the infrastructure level in the cloud architecture.
• Various approaches have been proposed to improve cloud interoperability for all the three levels (IaaS, PaaS and SaaS)
• As standardization efforts proceed, alternative user-centric approaches to achieve cloud interoperability are being proposed as more immediate, practical solutions.
• Cloud brokerages, providercentric and user-centric approaches are among the proposed solutions. Three user-centric approaches (Supercloud, Kangaroo and HVX) for VMs live migration across the cloud are analysed in this survey based on performance, flexibility and security QoS attributes.
? This algorithm achieves better performance and low overhead as it minimizes the number of migrations.
? On the other hand, a large number of VM migrations can lead to wastage of energy and time, which ultimately degrades the performance of the VMs.
? If the performance exceeds a threshold, then it initiates the process of migration. The threshold value is relying on the service level agreement.
? The simulation results show the better performance of the proposed algorithm RU-VMM in comparison to the existing algorithms.
? The comparison has been shown in terms of three performance metrics, namely number of nal source vehicles, percentage of successful migration(s) and percentage of dropped migration(s).
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