Conferences related to Cloud Computing

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2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

robotics, intelligent systems, automation, mechatronics, micro/nano technologies, AI,

2019 Winter Simulation Conference (WSC)

WSC is the premier international forum for disseminating recent advances in the field of system simulation. In addition to a technical program of unsurpassed scope and quality, WSC provides the central meeting for practitioners, researchers, and vendors.

IEEE INFOCOM 2019 - IEEE Conference on Computer Communications

IEEE INFOCOM solicits research papers describing significant and innovative research contributions to the field of computer and data communication networks. We invite submissions on a wide range of research topics, spanning both theoretical and systems research.

2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)

The conference aims at bringing together researchers and practitioners in the world working on trusted computing and communications, with regard to trust, security, privacy, reliability, dependability, survivability, availability, and fault tolerance aspects of computer systems and networks, and providing a forum to present and discuss emerging ideas and trends in this highly challenging research field

2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)

Cluster Computing, Grid Computing, Edge Computing, Cloud Computing, Parallel Computing, Distributed Computing

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Periodicals related to Cloud Computing

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Antennas and Wireless Propagation Letters, IEEE

IEEE Antennas and Wireless Propagation Letters (AWP Letters) will be devoted to the rapid electronic publication of short manuscripts in the technical areas of Antennas and Wireless Propagation.

Communications Letters, IEEE

Covers topics in the scope of IEEE Transactions on Communications but in the form of very brief publication (maximum of 6column lengths, including all diagrams and tables.)

Communications Magazine, IEEE

IEEE Communications Magazine was the number three most-cited journal in telecommunications and the number eighteen cited journal in electrical and electronics engineering in 2004, according to the annual Journal Citation Report (2004 edition) published by the Institute for Scientific Information. Read more at This magazine covers all areas of communications such as lightwave telecommunications, high-speed data communications, personal communications ...

Communications Surveys & Tutorials, IEEE

Each tutorial reviews currents communications topics in network management and computer and wireless communications. Available tutorials, which are 2.5 to 5 hours in length contains the original visuals and voice-over by the presenter. IEEE Communications Surveys & Tutorials features two distinct types of articles: original articles and reprints. The original articles are exclusively written for IEEE Communications Surveys & Tutorials ...


Computer, the flagship publication of the IEEE Computer Society, publishes peer-reviewed technical content that covers all aspects of computer science, computer engineering, technology, and applications. Computer is a resource that practitioners, researchers, and managers can rely on to provide timely information about current research developments, trends, best practices, and changes in the profession.

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Most published Xplore authors for Cloud Computing

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Xplore Articles related to Cloud Computing

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Cloud Computing Innovation in India: A Framework and Roadmap - White Paper 2.0

[] Cloud Computing Innovation in India: A Framework and Roadmap - White Paper 2.0, 2014

Explores the market opportunities for cloud computing in India. Cloud Computing is a new paradigm in information technology (IT) and IT-enabled services(ITES) that transforms “computing as a resource” to “computing as a service”. It is a disruptive technology with influence pervading across all aspects of a modern economy. While this has the potential of leapfrogging the economy of emerging markets ...

Block Design-based Key Agreement for Group Data Sharing in Cloud Computing

[{u'author_order': 1, u'affiliation': u'School of Computer and Software, Nanjing University of Information Science and Technology, 71127 Nanjing, Jiangsu China 210044 (e-mail:', u'full_name': u'Jian Shen'}, {u'author_order': 2, u'affiliation': u'School of Computer and Software, Nanjing University of Information Science & Technology, Nanjing, Jiangsu China (e-mail:', u'full_name': u'Tianqi Zhou'}, {u'author_order': 3, u'affiliation': u'State Key Lab of Software Engineering, Wuhan University, Wuhan, HuBei China 430072 (e-mail:', u'full_name': u'Debiao He'}, {u'author_order': 4, u'affiliation': u'School of Information Technology, Deakin University, Melbourne, Victoria Australia (e-mail:', u'full_name': u'Yuexin Zhang'}, {u'author_order': 5, u'affiliation': u'College of Computer and Software, Nanjing University of Information Science & Technology, Nanjing, Jiangsu Province China (e-mail:', u'full_name': u'Xingming Sun'}, {u'author_order': 6, u'affiliation': u'School of Information Technology, Deakin University, Burwood, Victoria Australia (e-mail:', u'full_name': u'Yang Xiang'}] IEEE Transactions on Dependable and Secure Computing, None

Data sharing in cloud computing enables multiple participants to freely share the group data, which improves the efficiency of work in cooperative environments. However, how to ensure the security of data sharing within a group and how to efficiently share the outsourced data in a group manner are formidable challenges. Note that key agreement protocols have played a very important ...

An anonymous remote attestation for trusted cloud computing

[{u'author_order': 1, u'affiliation': u'Department of Computer Science and Technology, East China Normal University, Shanghai 200241, China', u'full_name': u'Yong Zhang'}, {u'author_order': 2, u'affiliation': u'Department of Computer Science and Technology, East China Normal University, Shanghai 200241, China', u'full_name': u'Xiangxue Li'}, {u'author_order': 3, u'affiliation': u'Department of Computer Science and Technology, East China Normal University, Shanghai 200241, China', u'full_name': u'Haifeng Qian'}] 2012 IEEE 2nd International Conference on Cloud Computing and Intelligence Systems, 2012

Cloud computing provides users and companies a cost-efficient and flexible service. However, for a cloud computing client, one of most worrying problems is that IT infrastructure is under control of the cloud provider. To secure cloud users' computation, efficient remote attestation protocol is required. In this paper, by combining trusted computing and dynamic accumulators, we put forward an anonymous remote ...

Cloud Computing for Emerging Mobile Cloud Apps

[{u'author_order': 1, u'authorUrl': u'', u'full_name': u'Mehdi Bahrami', u'id': 37085426002}] 2015 3rd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, 2015

The tutorial will begin with an explanation of the concepts behind cloud computing systems, cloud software architecture, the need for mobile cloud computing as an aspect of the app industry to deal with new mobile app design, network apps, app designing tools, and the motivation for migrating apps to cloud computing systems. The tutorial will review facts, goals and common ...

Security of virtual working on cloud computing platform

[{u'author_order': 1, u'affiliation': u'College of Computer Science and Software Engineering, Shenzhen University, China', u'authorUrl': u'', u'full_name': u'Zhengping Liang', u'id': 37929509900}, {u'author_order': 2, u'affiliation': u'College of Computer Science and Software Engineering, Shenzhen University, China', u'authorUrl': u'', u'full_name': u'Songsong Jia', u'id': 38580998300}, {u'author_order': 3, u'affiliation': u'College of Computer Science and Software Engineering, Shenzhen University, China', u'authorUrl': u'', u'full_name': u'Jianyong Chen', u'id': 37311010700}, {u'author_order': 4, u'affiliation': u'Center for Cloud Computing, Shenzhen Institutes of Advanced Technology, China', u'authorUrl': u'', u'full_name': u'Pengfu Chen', u'id': 38580735500}] 2012 IEEE Asia Pacific Cloud Computing Congress (APCloudCC), 2012

With the development of information technology and attention of energy reservation, more and more people and organizations are interested in working virtually. However, security is one of important challenges for virtual working since sensitive data is transmitted and stored online. In this paper, we propose a novel solution as a security service on cloud computing platform to protect virtual working ...

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Educational Resources on Cloud Computing

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  • Resource Management: Performance Assuredness in Distributed Cloud Computing via Online Reconfigurations

    Cloud computing relies on software for distributed batch and stream processing, as well as distributed storage. This chapter focuses on an oft‐ignored angle of assuredness: performance assuredness. A significant pain point today is the inability to support reconfiguration operations, such as changing of the shard key in a sharded storage/database system, or scaling up (or down) of the number of virtual machines (VMs) being used in a stream or batch processing system. We discuss new techniques to support such reconfiguration operations in an online manner, whereby the system does not need to be shut down and the user/client‐perceived behavior is indistinguishable regardless of whether a reconfiguration is occurring in the background, that is, the performance continues to be assured in spite of ongoing background reconfiguration. Next, we describe how to scale‐out and scale‐in (increase or decrease) the number of machines/VMs in cloud computing frameworks like distributed stream processing and distributed graph processing systems, again while offering assured performance to the customer in spite of the reconfigurations occurring in the background. The ultimate performance assuredness is the ability to support SLAs/SLOs (service‐level agreements/objectives) such as deadlines. We present a new real‐time scheduler that supports priorities and hard deadlines for Hadoop jobs. We implemented our reconfiguration systems as patches to several popular and open‐source cloud computing systems, including MongoDB and Cassandra (storage), Storm (stream processing), LFGraph (graph processing), and Hadoop (batch processing).

  • Research Topics in Cloud Computing

    The cloud computing research trends of industry and academia are determined by considering the aims and output of journals, conferences, and workshops during 2012 and 2013, white papers from major industry players in cloud computing; objectives of major cloud computing laboratories in universities; published government and industry research funding for cloud computing; and major government projects undertaken in various parts of the world.

  • Enterprise Cloud Computing Strategy and Policy

    In order for the benefits of cloud computing to be fully realized, cloud computing must first be properly integrated into the enterprise ecosystem. To achieve the benefits and desired level of success, a clear, functional and well executed strategy should be developed that enables the full potential of cloud computing to be achieved. This strategy should take a structured engineering approach, which balances four important elements: requirements, schedule, cost, and risk. When developing a strategy for implementing cloud computing across an enterprise, an organization should keep in mind that the success or failure of its integration relies on meeting the needs and desires of its potential customers. To achieve this, cloud service(s) must be implemented using a methodology that can be integrated into the given ecosystem without becoming a hindrance, and is looked upon by all parties as an opportunity.


    Both 'machine‐to‐machine (M2M) systems' and 'Internet of Things (loT)' are broad terms that are sometimes used interchangeably, and there is little point in debating where one ends and the other begins. Cloud computing refers to a class of on‐demand compute services available over the internet. These services include foundational offerings like computation and data storage, as well as more specialized services like machine learning and parallel data set processing. Remote monitoring represents the basic features common to most IoT solutions. Asset management builds on remote monitoring by adding capabilities of command and control to the system. In predictive maintenance scenarios, additional cloud services are added like machine learning and distributed analysis tools like Apache Hadoop; vending machines provide an excellent example of the benefits of predictive maintenance. With remote monitoring and machine learning, failure patterns can be recognized and addressed before actual failure happens, this is predictive maintenance.

  • Risks and Benefits: Game‐Theoretical Analysis and Algorithm for Virtual Machine Security Management in the Cloud

    The growth of cloud computing has spurred many entities, both small and large, to use cloud services in order to achieve cost savings. Public cloud computing has allowed for quick, dynamic scalability without much overhead or long‐term commitments. However, there are some disincentives to using cloud services, and one of the biggest is the inherent and unknown danger stemming from a shared platform – namely, the hypervisor. An attacker who compromises a virtual machine (VM) and then goes on to compromise the hypervisor can readily compromise all virtual machines on that hypervisor. That brings into play the game‐theoretic problem of negative externalities, in which the security of one player affects the security of another. Using game theory to model and solve these externalities, we show that there are multiple Nash equilibriums. Furthermore, we demonstrate that the VM allocation type can adversely affect the role that externality plays in the cloud security game. Finally, we propose an allocation method based on a Nash equilibrium such that the negative externality imposed on other players can be significantly lowered compared to that found with other common VM allocation methods.

  • Detection and Security: Achieving Resiliency by Dynamic and Passive System Monitoring and Smart Access Control

    In this chapter, we discuss methods to address some of the challenges in achieving resilient cloud computing. The issues and potential solutions are brought about by examples of (i) active and passive monitoring as a way to provide situational awareness about a system and users' state and behavior; (ii) automated reasoning about system/application state based on observations from monitoring tools; (iii) coordination of monitoring and system activities to provide a robust response to accidental failures and malicious attacks; and (iv) use of smart access control methods to reduce the attack surface and limit the likelihood of an unauthorized access to the system. Case studies covering different application domains, for example, cloud computing, large computing infrastructure for scientific applications, and industrial control systems, are used to show both the practicality of the proposed approaches and their capabilities, for example, in terms of detection coverage and performance cost.

  • Big Data Analytics and Cloud Computing in the Smart Grid

    The advanced communications infrastructure to be deployed in the smart grid is used for data exchange in many systems. This chapter introduces big data analytics and cloud computing and discusses their relevance to the smart grid. It focuses on relevant issues in demand response and wide‐area monitoring for illustration. Applications such as demand response and modern control need the information provided by massive amounts of data. In particular, price and energy forecasts will be produced by big data analytics. Preliminary results were given to demonstrate the importance of big data analytics in energy forecasts. Besides demand response, attack detection in smart grid communications is critical for secure and efficient grid operations. Machine learning and data mining, as well as big data analytics, are useful tools to achieve attack detections for both metering data and sensing data. Thus, energy fraud and system failures can be prevented.

  • Introduction

    Mission assurance for critical cloud applications is of growing importance to governments and military organizations; yet mission‐critical cloud computing may face the challenge of using hybrid (public, private, and/or heterogeneous) clouds and achieving “end‐to‐end” and “cross‐layered” security, dependability, and timeliness. In this book, we consider cloud applications in which assigned tasks or duties are performed in accordance with an intended purpose or plan in order to accomplish an assured mission.

  • Survivability: Design, Formal Modeling, and Validation of Cloud Storage Systems Using Maude

    To deal with large amounts of data while offering high availability, throughput, and low latency, cloud computing systems rely on distributed, partitioned, and replicated data stores. Such cloud storage systems are complex software artifacts that are very hard to design and analyze. We argue that formal specification and model checking analysis should significantly improve their design and validation. In particular, we propose rewriting logic and its accompanying Maude tools as a suitable framework for formally specifying and analyzing both the correctness and the performance of cloud storage systems. This chapter largely focuses on how we have used rewriting logic to model and analyze industrial cloud storage systems such as Google's Megastore, Apache Cassandra, Apache ZooKeeper, and RAMP. We also touch on the use of formal methods at Amazon Web Services.

  • Scalability, Workloads, and Performance: Replication, Popularity, Modeling, and Geo‐Distributed File Stores

    This chapter explores the problems of scalability of cloud computing systems. Scalability allows a cloud application to change in size, volume, or geographical distribution while meeting the needs of the cloud customer. A practical approach to scaling cloud applications is to improve the availability of the application by replicating the resources and files used; this includes creating multiple copies of the application across many nodes in the cloud. Replication improves availability through use of redundant resources, services, networks, file systems, and nodes, but also creates problems with respect to clients' ability to observe consistency as they are served from the multiple copies. Variability in data sizes, volumes, and the homogeneity and performance of the cloud components (disks, memory, networks, and processors) can impact scalability. Evaluating scalability is difficult, especially when there is a large degree of variability. That leads to the need to estimate how applications will scale on clouds based on probabilistic estimates of job load and performance. Scaling can have many different dimensions and properties. The emergence of low‐latency worldwide services and the desire to have higher fault tolerance and reliability has led to the design of geo‐distributed storage with replicas in multiple locations. At the end of this chapter, we consider scalability in terms of the issues involved with cloud services that are geo‐distributed and also study, as a case example, scalable geo‐distributed storage.

Standards related to Cloud Computing

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No standards are currently tagged "Cloud Computing"