A market-oriented dynamic collaborative cloud services platform

Currently, interoperability and scalability are two major challenging issues for cloud computing. Forming a dynamic collaboration (DC) platform among cloud providers (CPs) can help to better address these issues. A DC platform can facilitate expense reduction, avoiding adverse business impacts and offering collaborative or portable cloud services to consumers. However, there are two major challenges involved in this undertaking; one is to find an appropriate market model to enable a DC platform, and the other one is to minimize conflicts among CPs that may occur in a market-oriented DC platform. In this paper, we present a novel combinatorial auction (CA)-based cloud market (CACM) model that enables a DC platform in CPs. To minimize conflicts among CPs, a new auction policy is proposed that allows a CP to dynamically collaborate with suitable partner CPs to form groups and publishes their group bids as a single bid to compete in the auction. However, identifying a suitable combination of CP partners to form the group and reduce conflicts is a NP-hard problem. Hence, we propose a promising multi-objective (MO) optimization model for partner selection using individual information and past collaborative relationship information, which is seldom considered. A multi-objective genetic algorithm (MOGA) called MOGA-IC is proposed to solve the MO optimization problem. This algorithm is developed using two popular MOGAs, the non-dominated sorting genetic algorithm (NSGA-II) and the strength pareto evolutionary genetic algorithm (SPEA2). The experimental results show that MOGA-IC with NSGA-II outperformed the MOGA-IC with SPEA2 in identifying useful pareto-optimal solution sets. Other simulation experiments were conducted to verify the effectiveness of the MOGA-IC in terms of satisfactory partner selection and conflict minimization in the CACM model. In addition, the performance of the CACM model was compared to the existing CA model in terms of economic efficiency.     

Design of energy‐efficient cloud systems via network and resource virtualization

Data centers play a crucial role in the delivery of cloud services by enabling on‐demand access to the shared resources such as software, platform and infrastructure. Virtual machine (VM) allocation is one of the challenging tasks in data center management since user requirements, typically expressed as service‐level agreements, have to be met with the minimum operational expenditure. Despite their huge processing and storage facilities, data centers are among the major contributors to greenhouse gas emissions of IT services. In this paper, we propose a holistic approach for a large‐scale cloud system where the cloud services are provisioned by several data centers interconnected over the backbone network. Leveraging the possibility to virtualize the backbone topology in order to bypass IP routers, which are major power consumers in the core network, we propose a mixed integer linear programming (MILP) formulation for VM placement that aims at minimizing both power consumption at the virtualized backbone network and resource usage inside data centers. Since the general holistic MILP formulation requires heavy and long‐running computations, we partition the problem into two sub‐problems, namely, intra and inter‐data center VM placement. In addition, for the inter‐data center VM placement, we also propose a heuristic to solve the virtualized backbone topology reconfiguration computation in reasonable time. We thoroughly assessed the performance of our proposed solution, comparing it with another notable MILP proposal in the literature; collected experimental results show the benefit of the proposed management scheme in terms of power consumption, resource utilization and fairness for medium size data centers. Copyright © 2013 John Wiley & Sons, Ltd.     

Universal privacy‐preserving platform for SecaaS services

With the rapid growth of the Security‐as‐a‐Service market, concerns about privacy in exposing customer security policies to Cloud Service Providers have become critical. To resolve these issues, several solutions have been proposed over the past few years, each for a different kind of security service. However, as the number of security services outsourced into a cloud continues to grow, the need for a unified solution has become significant. This article introduces and presents a universal privacy‐preserving platform for SecaaS services that is based on a hybrid cloud architecture for maintaining the confidentiality of the customer's security policy. It is shown that this platform can be applied to all security services whose security policies can be represented in the form of a decision tree. This includes the vast majority of existing cloud‐based security services. With the small number of computationally‐expensive operations performed in a private cloud, the solution also does not require the implementation of a performant security engine on the customer's premises, allowing full advantage to be taken of private cloud offloading. It is also shown that the platform achieves better performance results than other existing solutions of this type. These findings were confirmed by experimental results.     

Analysis of QoS aware energy-efficient resource provisioning techniques in cloud computing

By incorporating on-demand resources, software and data for collaborative services through the Internet, the conventional Information Technology enterprise has been transformed by cloud computing. Based on the pay-per-use approach, Infrastructure, platform or Software resources and servers located across data centres are among the several types of resources offered to consumers in cloud computing. Data centres handle these resources. These resources are constantly provisioned to users based on their availability, demand, and quality requirements. Cloud computing systems are known as one of the largest utilisers of energy resources all over the world. Also, power consumption has become a crucial aspect as most cloud computing systems work on traditional nonrenewable resources of energy. In order to make data centres environment-friendly, there is a need for optimal approaches to reduce energy consumption and their hazardous effects on the environment. To analyse different available strategies for building and maintaining an energy-efficient cloud is the main objective of this paper. The paper will comprehensively review several energy-efficient resource provisioning methods and provide a graphical comparative study of Quality of Service (QoS) Metrics in cloud computing. Moreover, the present study identifies the areas of study that need to be further improved to increase the energy efficiency of cloud computing systems.     

基于用例的云计算互操作性分析

如何保障云计算平台间以及云计算平台和本地系统间的互操作性便成了一个重要问题.从四个方面分析了云计算平台的互操作性问题,然后根据典型三层应用的使用模式分析了几个典型的互操作应用场景,并以微软云计算平台为例分析了其对互操作性的支持.     

基于云计算服务模式的数据挖掘应用平台的构建

本文将云计算的服务模式应用到数据挖掘应用平台的设计中,提出了3层4模式的云计算服务层次体系,并将此体系应用到数据挖掘平台的构建中,构建了基于云计算服务模式的数据挖掘应用平台框架,详述了平台各子系统的功能,阐述了该平台的特色.此平台集成了多种数据挖掘方法,具有良好的通用性和可扩展性,可以为从事数据挖掘应用和研究的企业或学者提供一个良好的交流平台.     

移动云服务的自适应业务质量管理

The rapid growth of cloud computing and mobile Internet services has triggered the emergence of mobile cloud services. Among many challenges, QoS management is one of the crucial issues for mobile cloud services. However, existing works on QoS management for cloud computing can hardly fit well to the mobile environment. This paper presents a QoS management architecture and an adaptive management process that can predict, assess and ensure QoS of mobile cloud services. Furthermore, we propose an adaptive QoS management model based on Fuzzy Cognitive Maps (FCM), which suitably represents the causal relationships among QoS related properties and cloud service modes. We evaluate the proposed solution and demonstrate its effectiveness and benefits based on simulation work.     

Intent‐based service management for heterogeneous software‐defined infrastructure domains

One of the main challenges in delivering end‐to‐end service chains across multiple software‐defined networking (SDN) and network function virtualization (NFV) domains is to achieve unified management and orchestration functions. A very critical aspect is the definition of an open, vendor‐agnostic, and interoperable northbound interface (NBI) that should be as abstract as possible and decoupled from domain‐specific data and control plane technologies. In this paper, we propose a reference architecture and an intent‐based NBI for end‐to‐end service management across multiple technological domains. The general approach is tested in a heterogeneous OpenFlow/Internet‐of‐Things (IoT) SDN test bed, where the proposed solution is applied to a rather complex service provisioning scenario spanning three different technological domains: an IoT infrastructure deployment, a cloud‐based data collection, processing, and publishing platform, and a transport domain over a geographic network interconnecting the IoT domain and the data center hosting the cloud services.     

云制造概论

基于云计算的思想,文章提出一种面向服务、高效低耗和基于知识的网络化智能新模式——云制造。云制造融合现有信息化制造、云计算、物联网、语义Web、高性能计算等技术,能够为制造全生命周期过程提供可随时获取、按需使用、安全可靠、优质廉价的服务。基于云仿真原型平台COSIM-CSP的云仿真应用已初步用于某飞行器多学科虚拟样机的协同设计中,为云制造的进一步研究工作奠定了基础。     

A management architecture for client‐defined cloud storage services

Cloud service providers offer virtual resources to users, who then pay for as much as they use. High‐speed networks help to overcome the limitation of geographical distances between clients and cloud servers, which encourage users to adopt cloud storage services for data backup and sharing. However, users use only a few cloud storage services because of the complexity of managing multiple accounts and distributing data to store. In this paper, we propose the client‐defined management architecture (CLIMA) that redefines a storage service by coordinating multiple cloud storage services from clients. We address practical issues of coordinating multiple cloud service providers using a client‐based approach. We implement a prototype as a realization of CLIMA, which achieves both reliability and privacy protection using erasure code and higher performance by optimally scheduling data transmission. We use our prototype to evaluate the benefits of CLIMA on commercial cloud storage service providers. Finally, CLIMA empowers clients to increase the manageability and flexibility of cloud storage services. Copyright © 2015 John Wiley & Sons, Ltd.     

移动互联网环境下的云计算安全技术体系架构

文章在研究分析云计算安全风险和安全技术体系架构的基础上,结合移动互联网的特点,设计了一个多层次、多级别、弹性、跨平台和统一用户接口的移动互联网通用云计算安全技术体系架构。该架构可实现不同等级的差异化云安全服务,其中跨层的云安全管理平台可对整个系统的运维安全情况进行跨安全域和跨安全级别的监控。     

Consumer preferences of attributes of mobile payment services in South Korea

The widespread diffusion of mobile devices has led to a new method of value transfer that retains the features of mobile devices: mobile payments. Many researchers have investigated consumers’ responses to mobile payment services, which is a key indicator of the success of a service, and have examined determinants of consumer adoption. Although many studies have addressed consumer adoption of mobile payment services, only the general and abstract factors affecting adoption (e.g., perceived usefulness) have been intensively investigated. However, these studies have rarely examined the idiosyncratic and concrete aspects of mobile payment services. To improve our understanding of why consumers adopt certain mobile payment services, this study investigated consumers’ evaluations of the explicit attributes of the services. Three hundred seventy-three consumers of mobile payment services participated in an online conjoint survey. Their preference structure was generated from a conjoint analysis including five service attributes (mobile payment platform, assurance policy, mileage program, authentication method, and affiliated stores), which were identified through a literature review and focus group discussion. The results showed that an assurance policy is the most critical factor influencing consumers’ choices, and a mileage program is considered to be as imperative as the platform. We also compared the findings by two consumer clusters (safety seekers vs. platform adherers), which were classified by preference. Because this study examines concrete and specific attributes of mobile payment services beyond abstract and general adoption factors, it provides insights into consumers’ actual adoption of services.     

基于IAP云平台的电力物联网

智能电网和物联网是当今各国的研究热点.基于IAP云平台的电力物联网致力于撬动生产力的变革,直接将自动化系统的运行过程呈现在网络化协同服务平台,不仅提升设备互联运行的协同效率,也大幅提升工人及运维人员工作效率,实现减少用工成本的同时提高生产效率.     

A prediction‐based and power‐aware virtual machine allocation algorithm in three‐tier cloud data centers

With the increasing popularity of cloud computing services, the more number of cloud data centers are constructed over the globe. This makes the power consumption of cloud data center elements as a big challenge. Hereby, several software and hardware approaches have been proposed to handle this issue. However, this problem has not been optimally solved yet. In this paper, we propose an online cloud resource management with live migration of virtual machines (VMs) to reduce power consumption. To do so, a prediction‐based and power‐aware virtual machine allocation algorithm is proposed. Also, we present a three‐tier framework for energy‐efficient resource management in cloud data centers. Experimental results indicate that the proposed solution reduces the power consumption; at the same time, service‐level agreement violation (SLAV) is also improved.     

云计算热点问题分析

在云计算的研究和应用中一些热点问题比较突出,如：如何理解计算资源及其虚拟化、云计算与网格计算的差异、云计算中心与高性能计算机的关系、云安全和云标准等。文章对此给出了一些见解：计算资源的虚拟化促使信息服务走向规模化、集约化和专业化;网格计算是＂多为一＂,而云计算是＂一为多＂;部署于高性能计算中心的高性能计算机未必适合云计算;云安全已经将传统安全问题发展为服务方和被服务方之间的信任和信任管理问题;在现有标准的基础上,云计算标准将需更加关注服务的互操作等。     

Leveraging countermeasures as a service for VoIP security in the cloud

The emergence of cloud computing is contributing to the integration of multiple services, in particular VoIP services. While the cloud has recently been used for performing security attacks targeting IP telephony, it also provides new opportunities for supporting the security of this service. In that context, we propose a risk management strategy for VoIP cloud based on security countermeasures that may be outsourced as services. We present the architecture of our solution and its components in the context of services implementing the SIP protocol. We describe the mathematical modelling supporting our approach and detail different treatment strategies for the application of countermeasures. Finally, we quantify the benefits and limits of these strategies based on extensive simulation results. When a countermeasure fails, these strategies allow us to maintain the risk level low at an additional cost of up to 7%, or to accept an additional risk of up to 12%. They can also be combined to obtain a trade‐off between cost and performance. Copyright © 2013 John Wiley & Sons, Ltd.     

Efficient Resource Management on Cloud Using Energy and Power Aware Dynamic Migration (EPADM) of VMs

In present decade, cloud computing provides utility-based IT services to the global consumers. According to pay-by-use manner, it facilitates hosting of persistent services from the user, business and technical fields. But, it is to be mentioned that the data centers hosting the cloud-based services utilize large amount of energy, power and resources. Hence, there is a need of an efficient resource management model for cloud that involves in reducing the resource consumption and computational cost. And, for managing the virtual resources with respect to the varying demands in cloud environment, dynamic virtual resource management is required. With that concern, this paper presents a model called Energy and Power Aware Dynamic Migration (EPADM). Based on the model design, the main objectives such as, efficient resource mapping and provisioning algorithms are presented. The dynamic Virtual Migration (VM) operation comprises the VM relocation and consolidation parts for achieving desirable results. Moreover, the paper also concentrates on reducing the SLA (Service Level Agreement) based violation, which is a significant factor to be considered on cloud. The proposed EPADM model is evaluated using the CloudSim toolkit. The results illustrate that the proposed model has massive potential than others, as it provides energy-power efficiency, reduced SLA violations under distinctive workload cases.

     

Integration of firefly optimization and Pearson service correlation for efficient cloud resource utilization

Cloud Computing (CC) environment presents a simplified, centralized platform or resources to usage while necessitated at minimum cost. In CC, the main processes in is the allocation of resources of web applications. However, with the increasing demands of Cloud User (CU), an efficient resource allocation technique for web applications is required. According to the request made by the user and response obtained, the cost of resources has also to be optimized. To overcome such limitations, Pearson service correlation‐based firefly resource cost optimization (PSC‐FRCO) technique is designed. Pearson service correlation‐based firefly resource cost optimization technique not only improves the performance of cost aware resource allocation but also achieves higher efficiency while rendering services in cloud computing environment for web applications. Pearson service correlation‐based firefly resource cost optimization technique initially uses Pearson service correlation in which the user‐required service is identified by correlating the available services provided by cloud owner. This helps in improving the Response Time (RT) of cloud service provisioning. Next, firefly resource cost optimization algorithm is applied to identify and allocate the cost‐optimized cloud resources to users to afford required service from the cloud server. Thus, PSC‐FRCO technique improves the Resource Utilization Efficiency (RUE) of web applications with minimal computational cost. This technique conducts experimental works on parameters such as RT, Bandwidth Utilization Rate (BUR) computational cost, Energy Consumption (EC), and RUE. Experimental analysis reveals that PSC‐FRCO technique enhances enhances RUE and lessens RT as compared to state‐of‐the‐art works.     

A marketplace and its market mechanism for trading commoditized computing resources

This paper presents the design and implementation of the GridEcon Marketplace. In addition to supporting a market mechanism for trading computing resources on a pay-per-use basis, this marketplace also provides an environment for integrating value-added support services. These value-added services help consumers to use the utility computing market more efficiently. The GridEcon Market Mechanism for virtual machines specifies in detail the unit-of-trade, the bids and asks, as well as the matching algorithm. The marketplace and market mechanism are validated by using the GridEcon Platform, which is a service-oriented platform for composing market scenarios. Our validation results show that the GridEcon Marketplace fulfills all functional requirements and that the GridEcon Market Mechanism is computationally and economically efficient.     

摊位信息管理系统的建立与应用

文章指出疫情的阴霾逐渐散去,各地消费活力恢复。地摊经济是就业岗位的重要来源,是中国经济即刻复苏的基础。但地摊经济不断发展的背后仍然存在市场秩序、买卖纠纷、商品质量等现实问题。由此可以打造地摊经济智慧服务平台,实地采集数据从而形成规模效应,通过大数据云计算等手段分析数据,为市场管理部门提供信息与管理支持,服务地方经济与民生;为摊主提供市场情况、摊位信息等服务;为消费者提供必要的商品导购、服务质量等信息,营造更为舒适的消费体验。