Middleware Layer Reliability Assessment in Multi Cloud Computing System

Enterprises are majorly adopting cloud computing which offers a large pool of services to users. But the capability of cloud computing is limited and some enterprises often require various cloud centers to integrate in order to deliver services to business users. So Multi Cloud Computing System (MCCS) provides integrated services across multiple autonomous clouds. Based on the dynamic parameterization of Virtual Machines (VM) an MCCS platform can build effectively. Thus multiple VMs can collaborate to provide as service with a transparent manner, facilitates a scalable environment, allocate resources dynamically and supports unlimited computing and storage service capabilities. Thus VM plays an important role in MCCS. This paper focuses on middleware layer and proposes framework for reliability assessment mechanism of middleware layer of MCCS

Exploring the firewall security consistency in cloud computing during live migration

Virtualization technology adds great opportunities and challenges to the cloud computing paradigm. Resource management can be efficiently enhanced by employing Live Virtual Machine Migration (LVMM) techniques. Based on the literature of LVMM implementation in the virtualization environment, middle-boxes such as firewalls do not work effectively after LVMM as it introduces dynamic changes in network status and traffic, which may lead to critical security vulnerabilities. One key security hole is that the security context of the firewall do not move with the Virtual Machine after LVMM is triggered. This leads to inconsistency in the firewall level of protection of the migrated Virtual Machine. There is a lack in the literature of practical studies that address this problem in cloud computing platform. This paper demonstrates a practical analysis using OpenStack testbed to study the firewalls limitations in protecting virtual machines after LVMM. Two network scenarios are used to evaluate this problem. The results show that the security context problem does not exist in the stateless firewall but can exist in the stateful firewall

Performance-oriented Cloud Provisioning: Taxonomy and Survey

Cloud computing is being viewed as the technology of today and the future. Through this paradigm, the customers gain access to shared computing resources located in remote data centers that are hosted by cloud providers (CP). This technology allows for provisioning of various resources such as virtual machines (VM), physical machines, processors, memory, network, storage and software as per the needs of customers. Application providers (AP), who are customers of the CP, deploy applications on the cloud infrastructure and then these applications are used by the end-users. To meet the fluctuating application workload demands, dynamic provisioning is essential and this article provides a detailed literature survey of dynamic provisioning within cloud systems with focus on application performance. The well-known types of provisioning and the associated problems are clearly and pictorially explained and the provisioning terminology is clarified. A very detailed and general cloud provisioning classification is presented, which views provisioning from different perspectives, aiding in understanding the process inside-out. Cloud dynamic provisioning is explained by considering resources, stakeholders, techniques, technologies, algorithms, problems, goals and more.Comment: 14 pages, 3 figures, 3 table

Data agility through clustered edge computing and stream processing

© 2018 John Wiley & Sons, Ltd. The Internet of Things is underpinned by the global penetration of network-connected smart devices continuously generating extreme amounts of raw data to be processed in a timely manner. Supported by Cloud and Fog/Edge infrastructures – on the one hand, and Big Data processing techniques – on the other, existing approaches, however, primarily adopt a vertical offloading model that is heavily dependent on the underlying network bandwidth. That is, (constrained) network communication remains the main limitation to achieve truly agile IoT data management and processing. This paper aims to bridge this gap by defining Clustered Edge Computing – a new approach to enable rapid data processing at the very edge of the IoT network by clustering edge devices into fully functional decentralized ensembles, capable of workload distribution and balancing to accomplish relatively complex computational tasks. This paper also proposes ECStream Processing that implements Clustered Edge Computing using Stream Processing techniques to enable dynamic in-memory computation close to the data source. By spreading the workload among a cluster of collocated edge devices to process data in parallel, the proposed approach aims to improve performance, thereby supporting agile data management. The experimental results confirm that such a distributed in-memory approach to data processing at the very edge of an IoT network can outperform currently adopted Cloud-enabled architectures, and has the potential to address a wide range of IoT-related data-intensive time-critical scenarios

Resumption of virtual machines after adaptive deduplication of virtual machine images in live migration

In cloud computing, load balancing, energy utilization are the critical problems solved by virtual machine (VM) migration. Live migration is the live movement of VMs from an overloaded/underloaded physical machine to a suitable one. During this process, transferring large disk image files take more time, hence more migration and down time. In the proposed adaptive deduplication, based on the image file size, the file undergoes both fixed, variable length deduplication processes. The significance of this paper is resumption of VMs with reunited deduplicated disk image files. The performance measured by calculating the percentage reduction of VM image size after deduplication, the time taken to migrate the deduplicated file and the time taken for each VM to resume after the migration. The results show that 83%, 89.76% reduction overall image size and migration time respectively. For a deduplication ratio of 92%, it takes an overall time of 3.52 minutes, 7% reduction in resumption time, compared with the time taken for the total QCOW2 files with original size. For VMDK files the resumption time reduced by a maximum 17% (7.63 mins) compared with that of for original files

An overview of virtual machine live migration techniques

In a cloud computing the live migration of virtual machines shows a process of moving a running virtual machine from source physical machine to the destination, considering the CPU, memory, network, and storage states. Various performance metrics are tackled such as, downtime, total migration time, performance degradation, and amount of migrated data, which are affected when a virtual machine is migrated. This paper presents an overview and understanding of virtual machine live migration techniques, of the different works in literature that consider this issue, which might impact the work of professionals and researchers to further explore the challenges and provide optimal solutions

A Machine Learning Approach for Desktop and Application Virtualization Design in Cloud Environment

In recent years, virtual desktop and virtual application is the important research topic for virtualization of cloud computing. Virtualization provides many benefits by using virtual machine software, including we can efficiently deploy and manage all of virtual system resources, and it offers the ability of high reliability, high elasticity and customization. In order to share the system and software resources, related basic knowledge show in our paper about the virtualization technology of desktop and application, and we proposed the virtual desktop and application services to offer an efficient and elastic service for cloud platform. A machine learning approach is also applied to manage resource allocation. It implements the VDaaS (Virtual Desktop as a Service) and VAaaS (Virtual Application as a Service) by developing the sharing technology for virtual desktop and virtual application with the cloud platform