基于OpenStack架构的IaaS云计算资源服务快速横向扩展框架研究

基础设施即服务(Infrastruction as a Service,IaaS)云对传统数据中心的实体资源进行整合,对外提供具备按需使用、弹性等性质的资源服务。IaaS云为了应对到达时间不可预知的负载峰值段,需要快速响应资源扩展请求,而现有的横向扩展方法不能在短时间内满足资源扩展需求。本文主要研究OpenStack架构的IaaS云中计算资源服务的快速横向扩展问题,并基于SnowFlock虚拟机克隆技术[1]提出了资源服务的两阶段快速扩展框架,应对到达时间不可预知的资源需求。

云计算模式下数字图书馆的管理与服务

云计算模式为提高数字图书馆网络信息资源管理与服务水平带来了契机,大大降低了管理与服务的成本,可以有效地适应用户与图书馆的互动;分析了数字图书馆在"云"服务模式下所应注意的信息资源安全问题。

Energy efficient virtual machine migration approach with SLA conservation in cloud computing

In the age of online workload explosion,cloud users are increasing exponentialy.Therefore,large scale data centers are required in cloud environment that leads to high energy consumption.Hence,optimal resource utilization is essential to improve energy efficiency of cloud data center.Although,most of the existing literature focuses on virtual machine(VM)consolidation for increasing energy efficiency at the cost of service level agreement degradation.In order to improve the existing approaches,load aware three-gear THReshold(LATHR)as well as modified best fit decreasing(MBFD)algorithm is proposed for minimizing total energy consumption while improving the quality of service in terms of SLA.It offers promising results under dynamic workload and variable number of VMs(1-290)allocated on individual host.The outcomes of the proposed work are measured in terms of SLA,energy consumption,instruction energy ratio(IER)and the number of migrations against the varied numbers of VMs.From experimental results it has been concluded that the proposed technique reduced the SLA violations(55%,26%and 39%)and energy consumption(17%,12%and 6%)as compared to median absolute deviation(MAD),inter quartile range(IQR)and double threshold(THR)overload detection policies,respectively.

Steiner Tree Based Optimal Resource Caching Scheme in Fog Computing

Fog Computing is a new platform that can serve mobile devices in the local area. In Fog Computing, the resources need to be shared or cached in the widely deployed Fog clusters. In this paper, we propose a Steiner tree based caching scheme, in which the Fog servers, when caching resources, first produce a Steiner tree to minimize the total path weight(or cost) such that the cost of resource caching using this tree could be minimized. Then we give a running illustration to show how the Fog Computing works and we compare the traditional shortest path scheme with the proposed one. The outcome shows that the Steiner tree based scheme could work more efficiently.

Joint resource allocation scheme based on evolutionary game for mobile edge computing

To satisfy mobile terminals ’( MTs) offloading requirements and reduce MTs’ cost,a joint cloud and wireless resource allocation scheme based on the evolutionary game( JRA-EG) is proposed for overlapping heterogeneous networks in mobile edge computing environments. MTs that have tasks offloading requirements in the same service area form a population. MTs in one population acquire different wireless and computation resources by selecting different service providers( SPs). An evolutionary game is formulated to model the SP selection and resource allocation of the MTs. The cost function of the game consists of energy consumption,time delay and monetary cost. The solutions of evolutionary equilibrium( EE) include the centralized algorithm based on replicator dynamics and the distributed algorithm based on Q-learning.Simulation results show that both algorithms can converge to the EE rapidly. The differences between them are the convergence speed and trajectory stability. Compared with the existing schemes,the JRA-EG scheme can save more energy and have a smaller time delay when the data size becomes larger. The proposed scheme can schedule the wireless and computation resources reasonably so that the offloading cost is reduced efficiently.

Dynamic Web services discovery based on similarity computation

A new approach for dynamic Web services discovery based on similarity computation in the treatment of massive Web information resource is put forward. Firstly, three kinds of service description information, textual, semantic and structural information, were modeled to compute the similarity of services. Then a novel dynamic Web services discovery mechanism was provided and the experiment on it was carried out. Results show that the new approach achieves considerable performance on precision and efficiency metrics for dynamic Web services discovery.

Cloud Computing as Area of Modem Industry

Cloud computing is a new vision about the needs of information technology （IT）. It provides a comprehensive concept for building a homogeneous environment through services offered in the cloud Software-as-a-Service （SaaS）, Platform-as-a-Service （PaaS）, and Infrastructure-as-a-Service （IaaS）. Cloud computing is location-independent computing, whereby shared servers provide resources, software, and data to computers and other devices on demand, as with the electricity grid. Cloud computing is computing paradigm that is driven by economies of scale, in which a set of dynamically-scalable resources such as servers, storages, platforms, and services are delivered on demand to the customers over the interuet. ＂Cloud computing is a continuation of the direction the industry has been going for the last several years in terms of using shared and elastically scalable computing resources,＂ says Rex Wang1, VP of Product Marketing at Oracle, who spoke at the Gartner Data Center Conference, in January 2011. Cloud computing refers to dynamic provision of virtual distributed computational resources on demand via a computer network. Cloud computing is a new high technology industry that possesses a number of advantages over existing business practices： a reduction of expenses, technical staff, and efforts of the end users.

Adaptive service configuration approach for quality of service management in ubiquitous computing environments

Mobility and resource-limitedness pose challenging issues to service configuration for quality of service (QoS) management in ubiquitous computing environments. Previous configuration approaches, such as static resource reservation, dynamic resource allocation and single service composition are not valid in the environments. In this study, we present an adaptive service configuration approach. Firstly, we reduce the dynamic configuration process to a control model which aims to achieve the variation of critical QoS on minimal level with less resource cost. Secondly, to deal with different QoS variations, we design two configuration strategies—service chain reconfiguration and QoS parameter adjustment—and implement them based on fuzzy logic control theory. Finally, a configuration algorithm is developed to flexibly employ the two configuration strategies in tune with the error of critical QoS in configuration process. The results of simulation experiments suggest that our approach outper- forms existing configuration approaches in both QoS improvement and resource utilization.