Proficient selection of gateway and base station by adroit algorithm in cloud‐VMesh network

Cloud computing is alluring for the vehicular mesh (VMesh) network. Cloud computing stipulates the computing resources and services on demand using the Internet. The VMesh network is a type of networking where each vehicle must not only capture and disseminate its own data but also serve as a gateway for another vehicle. The cloud‐VMesh network is a convergent technology encompassed of three key technologies, namely, vehicular mesh network, cloud computing, and networking. In this paper, we propose a new routing algorithm for cloud‐VMesh network, dubbed as adroit algorithm. The proposed adroit algorithm addresses the choosing of an optimal gateway and base station in the network layer from and to the service requesters and cloud server. The simulation study shows that the adroit algorithm augments the routing issues such as delay, packet loss, congestion and deployment cost in the cloud‐VMesh network, and it is justified based on the packet delivery ratio, average response time, routing overhead ratio, and packet collision ratio. The simulation results demonstrate that the adroit algorithm outperforms the existing protocols. Copyright © 2016 John Wiley & Sons, Ltd.     

云网融合数智赋能架构及关键技术研究

本文基于云网融合基础,针对多云接入算力和海量数据分发所带来的网络确定性响应和高效服务保障等问题,提出一种基于ELK开源架构,融合Telemetry实时采集和人工智能分析的技术架构,同时研发和分析网元Telemetry能力统一、实时采智控一体和海量数据精准获取等关键技术,为行业相关业务实施提供参考与借鉴.     

An efficient clustering and load balancing of distributed cloud data centers using graph theory

The prime focus of the Cloud Service Providers is enhancing the service delivery performance of the distributed cloud data centers. The clustering and load balancing of distributed cloud data centers have significant impact on its service delivery performance. Hence, this paper models distributed cloud data center environment as a network graph and proposes a two‐phase cluster‐based load balancing (CLB) algorithm based on a graph model. The first phase proposes a Cloud Data Center Clustering algorithm to cluster the distributed cloud data centers based on their proximity. The second phase proposes a Client‐Cluster Assignment algorithm to perform uniform distribution of the client requests across the clusters to enable load balancing. To assess the performance, the proposed algorithms are compared with other K‐constrained graph‐based clustering algorithms namely, graph‐based K‐means and K‐spanning tree algorithms on a simulated distributed cloud data center environment. The experimental results reveal that the proposed CLB algorithm outperforms the compared algorithms in terms of the average clustering time, load distribution, and fairness index and hence improves the service delivery performance of the distributed cloud data centers.     

Dynamic Resource Allocation and Scheduling for Cloud‐Based Virtual Content Delivery Networks

This paper proposes a novel framework for virtual content delivery networks (CDNs) based on cloud computing. The proposed framework aims to provide multimedia content delivery services customized for content providers by sharing virtual machines (VMs) in the Infrastructure‐as‐a‐Service cloud, while fulfilling the service level agreement. Furthermore, it supports elastic virtual CDN services, which enables the capabilities of VMs to be scaled to encompass the dynamically changing resource demand of the aggregated virtual CDN services. For this, we provide the system architecture and relevant operations for the virtual CDNs and evaluate the performance based on a simulation.     

Game theory approach for detecting vulnerable data centers in cloud computing network

Nowadays, cloud computing has many benefits to accessibility, scalability, and cost‐effectiveness, leading to network security risks and vulnerabilities. Cloud computing is gaining in popularity with the advances and growth of its systems. Therefore, the security of this system and the identification of vulnerable data centers are more complicated than the past. Definitely discovering vulnerable data centers that are vulnerable to attacks can help to strengthen these data centers and provide a safer and more secure network structure. This paper examines the vulnerability of malware data centers in the infrastructure and cloud computing network structure. Based on the analysis of the cloud computing system in the field of game theory, we introduce a developed model for identifying vulnerable data centers in cloud computing. The developed model in this paper is based on the game theory as a mathematical tool. According to the game theory, we introduce a measure of the degree of vulnerability of data centers in the cloud computing network.     

Fog‐SDN: A light mitigation scheme for DDoS attack in fog computing framework

Cloud computing is one of the most tempting technologies in today's computing scenario as it provides a cost‐efficient solutions by reducing the large upfront cost for buying hardware infrastructures and computing power. Fog computing is an added support to cloud environment by leveraging with doing some of the less compute intensive task to be done at the edge devices, which reduces the response time for end user computing. But the vulnerabilities to these systems are still a big concern. Among several security needs, availability is one that makes the demanded services available to the targeted customers all the time. Availability is often challenged by external attacks like Denial of service (DoS) and distributed denial of service (DDoS). This paper demonstrates a novel source‐based DDoS mitigating schemes that could be employed in both fog and cloud computing scenarios to eliminate these attacks. It deploys the DDoS defender module which works on a machine learning–based light detection method, present at the SDN controller. This scheme uses the network traffic data to analyze, predict, and filter incoming data, so that it can send the filtered legitimate packets to the server and blocking the rest.     

浅析云计算技术下的移动通信网络优化

在信息技术科学技术迅速发展的今天,人和物逐渐进入通信时代和网络智能化时代,通信网络被广泛应用于人们的生活中,给人们的生活带来更多的便利。移动网络技术推动了信息技术的发展,在这种环境下云计算的诞生有利于移动通信网络进一步优化,为人们提供更加优质、高效的网络服务。所以,在云计算环境下必须合理配置和优化网络资源,将网络技术作为带动移动通信网络发展的技术核心,保障服务水平的提高。下面就云计算技术环境下的移动通信网络优化进行浅析。     

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.     

SDN‐based fault‐tolerant on‐demand and in‐advance bandwidth reservation in data center interconnects

Geographically distributed data centers are interconnected through provisioned dedicated WAN links, realized by circuit/wavelength–switching that support large‐scale data transfer between data centers. These dedicated WAN links are typically shared by multiple services through on‐demand and in‐advance resource reservations, resulting in varying bandwidth availability in future time periods. Such an inter‐data center network provides a dynamic and virtualized environment when augmented with cloud infrastructure supporting end‐host migration. In such an environment, dynamically provisioned network resources are recognized as extremely useful capabilities for many types of network services. However, the existing approaches to in‐advance reservation services provide limited reservation capabilities, eg, limited connections over links returned by the traceroute over traditional IP‐based networks. Moreover, most existing approaches do not address fault tolerance in the event of node or link failures and do not handle end‐host migrations; thus, they do not provide a reliability guarantee for in‐advance reservation frameworks. In this paper, we propose using multiple paths to increase bandwidth usage in the WAN links between data centers when a single path does not provide the requested bandwidth. Emulation‐based evaluations of the proposed path computation show a higher reservation acceptance rate compared to state‐of‐art reservation frameworks, and such computed paths can be configured with a limited number of static forwarding rules on switches. Our prototype provides the RESTful Web service interface for link‐fail and end‐host migration event management and reroutes paths for all the affected reservations.     

Identifying critical challenges in the adoption of cloud‐based services

Cloud computing provides a way to integrate and share information on a real‐time basis across an organization. The current organizations are adopting the cloud services to gain competitive advantage in real‐time data sharing. To meet the current demand in semiconductor industries, they must develop better techniques to produce electronic products at low cost and in a large scale. Adoption of cloud‐based services may resolve the fastest growing demand of technical advancement of semiconductor industries. The research presented in this paper is based on an analysis of the data obtained from the semiconductor sector. This study identifies the critical challenges associated with the cloud service adoption in semiconductor industries. Twelve critical challenges have been identified that need to be overcome for adopting the cloud services for any semiconductor industry. These are network/Internet availability, data security, integration of various services, monitoring of data and services, maintenance of computing performance, liability, power outage, service interruption, organizational change, business complexity, legal issues, and lack of awareness.     

TOPVISOR: Two‐level controller‐based approach for service advertisement and discovery in vehicular cloud network

Vehicular cloud is a kind of mobile cloud in which vehicles share their resources and provide services for each other. The first step in establishing a vehicular cloud network is the service advertisement and discovery. Due to the dynamic nature of vehicular cloud networks, services are not continuous and the service location may vary at any time depending on the vehicle location. Therefore, higher network traffic is generated to access the consistent and up‐to‐date information. In this paper, a two‐level hierarchical approach is proposed for service advertisement and discovery in vehicular cloud networks. To register the services' specification in this approach, the distributed directories in RSUs and central controllers are used. Moreover, a method is used to avoid extra update packets by localizing the updates. The simulation results show improvement in the packet delivery rate as well as a reduction in transmission bandwidth preventing the network congestion.     

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.     

云计算网络虚拟化技术

云计算极大扩展了IT服务能够提供的种类和范围,网络作为云计算基础架构和服务提供的重要组成部分,需要满足更高的要求。本文首先给出网络的重要性,之后从数据中心网络、跨数据中心网络以及泛在的云接入网络三个层面分别分析了最新的技术进展和技术需求。     

基于通信云和承载网协同的算力网络编排技术

面向未来网络中计算与网络紧密结合、"算网一体"的技术发展趋势,提出了基于集中式和分布式两种控制方案的算力网络编排模型,并分别介绍了实现过程的关键技术。从方案与技术分析来看,基于电信运营商通信云和承载网协同的算力网络编排方案可以较好地适应未来移动边缘计算(MEC)站点成网后边边协同与云边协同的业务需求,增强了网络对业务的感知与调度能力,而集中式或分布式控制方案的具体选择与运营商通信云能力和承载网的演进阶段密切相关。     

基于云、网、边融合的边缘计算新方案:算力网络

边缘计算已经成为5G时代重要的创新型业务模式,尤其是其低时延特性,被认为是传统方案所不具备的,因此边缘计算能够提供更多的服务能力且具有更为广泛的应用场景。但边缘计算与处于中心位置的云计算之间的算力协同成为新的技术难题,即需要在边缘计算、云计算以及网络之间实现云网协同、云边协同,甚至边边协同,才能实现资源利用的最优化。在研究边缘计算算力分配和调度需求的基础上,提出了基于云、网、边深度融合的算力网络方案,并针对AI类应用给出了一个典型实施系统,该方案能够有效应对未来业务对计算、存储、网络甚至算法资源的多级部署以及在各级节点之间的灵活调度。     

云计算总体架构及其应用与商业模式探讨

云计算具有全新的IT架构,可以灵活提供服务给具有不同需求的用户。通过对云架构的研究,指出云架构主要分为服务和管理两部分,详细解析了软件即服务（SaaS）、平台即服务（PaaS）和基础设施即服务（IaaS）及其实现的关键技术,以及管理部分客户层、管理功能层和监控层的架构和功能实现。最后,面向应用,给出了具体云计算构架的实例,并结合应用,提出了云应用的4种商业模式,即公有云、私有云、行业云和混合云,对云服务供应商面向客户的运营选取有一定的指导作用。     

Service‐oriented 5G network architecture: an end‐to‐end software defining approach

With the ever‐increasing mobile demands and proliferation of mobile services, mobile Internet has penetrated into every aspect of human life. Although the 4G mobile communication system is now being deployed worldwide, simply evolving or incrementally improving the current mobile networks can no longer keep the pace with the proliferation of mobile services. Against this background, aiming to achieve service‐oriented 5G mobile networks, this article proposes an end‐to‐end software defining architecture, which introduces a logically centralized control plane and dramatically simplifies the data‐plane. The control plane decomposes the diversified mobile service requirements and, correspondingly, controls the functions and behaviors of data‐plane devices. Consequently, the network directly orients towards services, and the devices are dynamically operated according to the service requirements. Therefore, the proposed architecture efficiently guarantees the end‐to‐end QoS and quality of experience. The challenges and key technologies of our architecture are also discussed in this article. Real traces‐based simulations validate the performance advantages of proposed architecture, including energy efficiency and the whole performance. Copyright © 2015 John Wiley & Sons, Ltd.     

云计算层次服务关联机制及SaaS模式下数据安全取向的研究

本文首先介绍了云计算特征与分类、云服务模式,其次,由云计算的开放类型：公有云、私有云、混合云等展开叙述,分析了云计算体系结构与云服务模式融合、云计算层次结构与服务类型关联机制、SaaS#系结构与安全隐患,最后阐述了SaaS模式下数据的安全取向,具体分析了系统管理与物理安全、数据传输与网络安全、数据存储与冗余备份、强化软件效用提升云服务安全等。     

视频云在有线电视网实现交互运用的定量分析

视频云计算是基于云计算技术的理念,采用视频作为"云端"向"终端"呈现处理结果的一种云计算方案。介绍了视频云计算的主要技术特性,分析了视频云计算和广电行业结合的天然优势和典型的应用服务,并在此基础上定量分析了利用视频云计算技术开展2D/3D应用的投资成本,为广电行业利用视频云计算技术开展增值服务提供了一定的参考。     

5G边缘计算和网络切片技术

由于能够以低成本提供5G无线网络中多样化的业务场景,网络切片和边缘计算一直以来深受学术界和工业界的提倡.网络切片通过将网络实体划分成多个逻辑独立网络,为不同业务场景提供所需服务,而边缘计算利用网络中用户和边缘网络设备的计算和存储功能,承载部分核心节点中的控制、管理、业务功能,能够提升传统移动宽带业务能力和应对新兴的机器类业务.将网络切片和边缘计算融合,提出了基于边缘计算的接入网络切片,能够满足5G中广泛的用例和商业模型,使得运营商能够根据第三方需求和网络状况以低成本为用户灵活提供个性化的网络服务.