MapReduce in the Cloud： Data-Location-Aware VM Scheduling

We have witnessed the fast-growing deployment of Hadoop,an open-source implementation of the MapReduce programming model,for purpose of data-intensive computing in the cloud.However,Hadoop was not originally designed to run transient jobs in which us ers need to move data back and forth between storage and computing facilities.As a result,Hadoop is inefficient and wastes resources when operating in the cloud.This paper discusses the inefficiency of MapReduce in the cloud.We study the causes of this inefficiency and propose a solution.Inefficiency mainly occurs during data movement.Transferring large data to computing nodes is very time-con suming and also violates the rationale of Hadoop,which is to move computation to the data.To address this issue,we developed a dis tributed cache system and virtual machine scheduler.We show that our prototype can improve performance significantly when run ning different applications.     

CLOUD COMPUTING

Cloud computing is a novel computing paradigm that utilizes remote cloud resources to achieve a high-performance computation. Cloud provides infra- structure, platform and software as different on-demand services. China has made remarkable progress in cloud- based products and operating system technology. The government, enterprises and research institutions are all active in the development of cloud computing-related projects. Despite the progress,     

＂Smart Cafe＂： A Mobile Local Computing System Based On Indoor Virtual Cloud

With network developing and virtualization rising, more and more indoor environment （POIs） such as care, library, office, even bus and subway can provide plenty of bandwidth and computing resources. Meanwhile many people daily spending much time in them are still suffering from the mobile device with limited resources. This situation implies a novel local cloud computing paradigm in which mobile device can leverage nearby resources to facilitate task execution. In this paper, we implement a mobile local computing system based on indoor virtual cloud. This system mainly contains three key components： 1）As to application, we create a parser to generate the ＂method call and cost tree＂ and analyze it to identify resource- intensive methods. 2） As to mobile device, we design a self-learning execution controller to make offtoading decision at runtime. 3） As to cloud, we construct a social scheduling based application-isolation virtual cloud model. The evaluation results demonstrate that our system is effective and efficient by evaluating CPU- intensive calculation application, Memory- intensive image translation application and I/ O-intensive image downloading application.     

QoS-Aware Dynamic Resource Management in Heterogeneous Mobile Cloud Computing Networks

In mobile cloud computing（MCC） systems,both the mobile access network and the cloud computing network are heterogeneous,implying the diverse configurations of hardware,software,architecture,resource,etc.In such heterogeneous mobile cloud（HMC） networks,both radio and cloud resources could become the system bottleneck,thus designing the schemes that separately and independently manage the resources may severely hinder the system performance.In this paper,we aim to design the network as the integration of the mobile access part and the cloud computing part,utilizing the inherent heterogeneity to meet the diverse quality of service（QoS）requirements of tenants.Furthermore,we propose a novel cross-network radio and cloud resource management scheme for HMC networks,which is QoS-aware,with the objective of maximizing the tenant revenue while satisfying the QoS requirements.The proposed scheme is formulated as a restless bandits problem,whose ＂indexability＂ feature guarantees the low complexity with scalable and distributed characteristics.Extensive simulation results are presented to demonstrate the significant performance improvement of the proposed scheme compared to the existing ones.     

A Case for Cloud-Based Mobile Search

Mobile search is beset with problems because of mobile terminal constraints and also because its characteristics are different from the traditional Internet search model. This paper analyzes cloud computing technologies-especially mass data storage, parallel computing, and virtualization-in an attempt to solve technical problems in mobile search. The broad prospects of cloud computing are also discussed.     

Cloud Computing in Mobile Communication Networks

Cloud computing makes computing power universally available and provides flexibility in resource acquisition.It allows for scalable provision of services and more reasonable use of resources.This article considers cloud service deployment and virtualization from the perspective of mobile operators.A solution is proposed that allows mobile operators to maximize profits with minimal investment.     

Call for Papers——Feature Topic,Vol.18,No.11,2021

Machine Learning in Mobile Edge Computing In recent years,mobile edge computing has attracted a considerable amount of attention from both academia and industry through its many advantages(such as low latency,computation efficiency and privacy)caused by its local model of providing storage and computation resources.In addition,machine learning has become the dominant approach in applications such as industry,healthcare,smart home,and transportation.All of these applications heavily rely on technologies that can be deployed at the network edge.Therefore,it is essential to combine machine learning with mobile edge computing to further promote the proliferation of intelligent edges.In general,machine learning relies on powerful computation and storage resources for superior performance,while mobile edge computing typically provides limited computation resources locally.     

MTBAC： A Mutual Trust Based Access Control Model in Cloud Computing

As a new computing mode, cloud computing can provide users with virtualized and scalable web services, which faced with serious security challenges, however. Access control is one of the most important measures to ensure the security of cloud computing. But applying traditional access control model into the Cloud directly could not solve the uncertainty and vulnerability caused by the open conditions of cloud computing. In cloud computing environment, only when the security and reliability of both interaction parties are ensured, data security can be effectively guaranteed during interactions between users and the Cloud. Therefore, building a mutual trust relationship between users and cloud platform is the key to implement new kinds of access control method in cloud computing environment. Combining with Trust Management（TM）, a mutual trust based access control （MTBAC） model is proposed in this paper. MTBAC model take both user＇s behavior trust and cloud services node＇s credibility into consideration. Trust relationships between users and cloud service nodes are established by mutual trust mechanism. Security problems of access control are solved by implementing MTBAC model into cloud computing environment. Simulation experiments show that MTBAC model can guarantee the interaction between users and cloud service nodes.     

云计算专题（英文）

正Cloud computing is a novel computing paradigm that utilizes remote cloud resources to achieve a high-performance computation.Cloud provides infrastructure,platform and software as different on-demand services.China has made remarkable progress in cloudbased products and operating system technology.The government,enterprises and research institutions are all active in the development of cloud computing-related projects.Despite the progress,many important problems     

ID-Based User Authentication Scheme for Cloud Computing

In cloud computing environments, user authentication is an important security mechanism because it provides the fundamentals of authentication, authorization, and accounting (AAA). In 2009, Wang et al. proposed an identity-based (ID-based) authentication scheme to deal with the user login problem for cloud computing. However, Wang et al.’s scheme is insecure against message alteration and impersonation attacks. Besides, their scheme has large computation costs for cloud users. Therefore, we propose a novel ID-based user authentication scheme to solve the above mentioned problems. The proposed scheme provides anonymity and security for the user who accesses different cloud servers. Compared with the related schemes, the proposed scheme has less computation cost so it is very efficient for cloud computing in practice.     

Energy-efficient computation offloading assisted by RIS-based UAV

The new applications surge with the rapid evolution of the mobile communications. The explosive growth of the data traffic aroused by the new applications has posed great computing pressure on the local side. It is essential to innovate the computation offloading methods to alleviate the local computing burden and improve the offloading efficiency. Mobile edge computing(MEC) assisted by reflecting intelligent surfaces(RIS)-based unmanned aerial vehicle(UAV) is a promising method to assist the us...     

Cloud Computing （3）

Editor's Desk: In the preceding two parts of this series, several aspects of cloud computing-including definition, classification, characteristics, typical applications, and service levels-were discussed. This part continues with a discussion of Cloud Computing Oopen Architecture and Market-Oriented Cloud. A comparison is made between cloud computing and other distributed computing technologies, and Google's cloud platform is analyzed to determine how distributed computing is implemented in its particular model.     

DIV： Dynamic Integrity Validation Framework for Detecting Compromises on Virtual Machine Based Cloud Services in Real Time

with the increasing popularity of cloud services,attacks on the cloud infrastructure also increase dramatically.Especially,how to monitor the integrity of cloud execution environments is still a difficult task.In this paper,a real-time dynamic integrity validation（DIV） framework is proposed to monitor the integrity of virtual machine based execution environments in the cloud.DIV can detect the integrity of the whole architecture stack from the cloud servers up to the VM OS by extending the current trusted chain into virtual machine＇s architecture stack.DIV introduces a trusted third party（TTP） to collect the integrity information and detect remotely the integrity violations on VMs periodically to avoid the heavy involvement of cloud tenants and unnecessary information leakage of the cloud providers.To evaluate the effectiveness and efficiency of DIV framework,a prototype on KVM/QEMU is implemented,and extensive analysis and experimental evaluation are performed.Experimental results show that the DIV can efficiently validate the integrity of files and loaded programs in real-time,with minor performance overhead.     

Anonymous authentication scheme of trusted mobile terminal under mobile Internet

In order to solve the contradictions between user privacy protection and identity authentication, an anonymous authentication scheme under mobile Internet is proposed, which is based on the direct anonymous attestation of trusted computing and uses the encrypting transfer and signature validation for its implementation. Aiming at two access mode of trusted mobile terminal under mobile Internet, self access and cross-domain access, the authentication process of each mode is described in details. The analysis shows that the scheme implements anonymous authentication on mobile Internet and is correct, controllable and unforgeable.     

Mobile Cloud Computing and Applications

In 2010, cloud computing gained momentum.Cloud computing is a model for real-time, on-demand, pay-for-use network access to a shared pool of configurable computing and storage resources.It has matured from a promising business concept to a working reality in both the private and public IT sectors.The U.S.government, for example, has requested all its agencies to evaluate cloud computing alternatives as part of their budget submissions for new IT investment.     

Design of a Cloud Service for Learning Chinese Pronunciation

With the fast growing of cloud computing infrastructure, learning from cloud services has become more and more convenient for people worldwide. In order to integrate the cloud computing technology and different e-learning platforms including variant mobile apps, Windows and web-based applications, we develop our Chinese learning system "analytic Chinese helper" with a service-oriented architecture(SOA). Based on the new architecture we designed and developed a cloud service for the e-learning of Chinese language on the Internet as a convenient resource for foreign students, especially in the reading of Chinese texts. There are two Chinese phonetic systems: Pinyin and Zhuyin. Pinyin is the official Romanization of Chinese characters, and Zhuyin incorporates additional Bopomofo symbols which transcribe precise sounds of Chinese characters. The proposed analytic Chinese helper provides real-time annotations with Pinyin or Zhuyin symbols, and thereby the annotated articles can be used as e-learning objects in learning Chinese.     

Joint partial computation offloading and resource allocation inMEC-enable networks

The sudden surge of various applications poses great challenges to the computation capability of mobile devices. To address this issue, computation offloading to multi-access edge computing(MEC) was proposed as a promising paradigm. This paper studies partial computation offloading scenario by considering time delay and energy consumption, where the task can be splitted into several blocks and computed both in local devices and MEC, respectively. Since the formulated problem is a nonconvex probl...     

Proactive Load Balancing Mechanism for Fog Computing Supported by Parked Vehicles in IoV-SDN

Internet of Vehicles(IoV)is a new style of vehicular ad hoc network that is used to connect the sensors of each vehicle with each other and with other vehicles’sensors through the internet.These sensors generate different tasks that should be analyzed and processed in some given period of time.They send the tasks to the cloud servers but these sending operations increase bandwidth consumption and latency.Fog computing is a simple cloud at the network edge that is used to process the jobs in a short period of time instead of sending them to cloud computing facilities.In some situations,fog computing cannot execute some tasks due to lack of resources.Thus,in these situations it transfers them to cloud computing that leads to an increase in latency and bandwidth occupation again.Moreover,several fog servers may be fuelled while other servers are empty.This implies an unfair distribution of jobs.In this research study,we shall merge the software defined network(SDN)with IoV and fog computing and use the parked vehicle as assistant fog computing node.This can improve the capabilities of the fog computing layer and help in decreasing the number of migrated tasks to the cloud servers.This increases the ratio of time sensitive tasks that meet the deadline.In addition,a new load balancing strategy is proposed.It works proactively to balance the load locally and globally by the local fog managers and SDN controller,respectively.The simulation experiments show that the proposed system is more efficient than VANET-Fog-Cloud and IoV-Fog-Cloud frameworks in terms of average response time and percentage of bandwidth consumption,meeting the deadline,and resource utilization.