Technological Innovation In Sdn.docx

"Technological Innovation in SDN/NFV, Cloud Computing and Big Data" Guest Editor: Dr. Ankur Dumka, University of Petroleum and Energy Studies, India The objective of this issue will be to produce novel and fundamental advances in terms of technological innovation in the fields of SDN/NFV, Cloud Computing and Big Data. It will also serve to foster communication among researchers and practitioners working in a wide variety of scientific areas with a common interest in improving SDN/NFV, Cloud Computing and Big Data Analysis related techniques. It will act as medium for IT industry, scientists and research scholar across the globe to showcase their research and recent advances in this field. This issue will set off a wave of reform in many areas, and will gradually create more value for humans. We will solicit high quality original research papers in all aspects of SDN/NFV, Cloud Computing and Big Data related to improvements in networks, cloud computing and big data platforms and services as well as applications utilising such platforms. The issue will carry revised and substantially extended versions of selected papers presented at the International Conference on Intelligent Communication, Control and Devices (ICICCD-2017), the International Conference on Computing Communication and Automation (ICCCA-2017), the 3rd International Conference on Advances in Computing, Communication and Automation (ICACCA-2017) and the 3rd International Conference On Internet of Things: Smart Innovation and Usages (IoT-SIU 2018), but we also strongly encourage researchers unable to participate in the conferences to submit articles for this call. Subject Coverage Suitable topics include, but are not limited, to the following:  o o o o o o o o o o o

NFV and SDN SDN architectures, application programming interfaces, protocols, and programming languages Control plane architectures and network operating systems in NFV and SDN infrastructures Design of SDN-based forwarding elements (switch/router, optical, wireless, gateways, etc.) Tools for validating network services and automating their deployment and management Applying compositional patterns for parallelism, control logic, performance, monitoring and reliability of network services Application of Big Data models and analytics to NFV and SDN Management, monitoring, and metering in NFV and SDN-based networks Data plane and control plane scalability and inter-operability studies Applications enabled by NFV and SDN networks. Commercial and economic models and implications for NFV and SDN ecosystems Service and information orchestration/chaining and life-cycle management

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Cloud computing Datacentre and cloud networking Cloud storage Cloud resource management and virtualisation Cloud applications Mobile cloud computing High-performance cloud computing Cloud and cluster computing platforms and systems Large-scale graph processing systems Green cloud computing and datacenter energy optimisations GPU and FPGA cloud computing and processing Internet of Things (IoT) and the cloud Cloud services – Infrastructure/Platform/Software as a Service (IaaS, PaaS, SaaS) Security and privacy in the cloud Interactive big-data analytics Big data management and analysis Intelligence in the cloud Large-scale machine learning and statistical analysis approaches in the cloud

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Big data science and foundations Novel theoretical models for big data New computational models for big data Data and information quality for big data New data standards

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Big data infrastructure Cloud/grid/stream computing for big data High performance/parallel computing platforms for big data Autonomic computing and cyber-infrastructure, system architectures, design and deployment Energy-efficient computing for big data Programming models and environments for cluster, cloud, and grid computing to support big data Software techniques and architectures in cloud/grid/stream computing Big data open platforms New programming models for big data beyond Hadoop/MapReduce, STORM Software systems to support big data computing

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Big data management Search and mining of variety of data including scientific and engineering, social, sensor/IoT/IoE, and multimedia data Algorithms and systems for big data search Distributed, and peer-to-peer search Big data search architectures, scalability and efficiency Data acquisition, integration, cleaning, and best practices Visualisation analytics for big data Computational modelling and data integration Large-scale recommendation systems and social media systems

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Big data search and mining Social web search and mining Algorithms and systems for big data search Distributed and peer-to-peer search Big data search architectures, scalability and efficiency Data acquisition, integration, cleaning, and best practices Visualisation analytics for big data Computational modelling and data integration Large-scale recommendation systems and social media systems Cloud/grid/streamdata mining- big velocity data

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Big data security, privacy and trust Intrusion detection for gigabit networks Anomaly and APT detection in very large scale systems High performance cryptography Visualising large scale security data Threat detection using big data analytics Privacy threats of big data Privacy preserving big data collection/analytics HCI challenges for big data security and privacy

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Big data applications Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance, Business, Law, Education, Transportation, Retailing, Telecommunication Big Data Analytics in Small Business Enterprises (SMEs) Big Data Analytics in Government, Public Sector and Society in General Real-life Case Studies of Value Creation through Big Data Analytics Big Data as a Service Big Data Industry Standards

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Notes for Prospective Authors Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. (N.B. Conference papers may only be submitted if the paper has been completely re-written and if appropriate written permissions have been obtained from any copyright holders of the original paper). All papers are refereed through a peer review process. All papers must be submitted online. To submit a paper, please read our Submitting articles page.

KRITIK JURNAL Judul

: "Technological

Innovation in SDN/NFV, Cloud Computing and Big Data"

Peniulis

: Dr. Ankur Dumka, University of Petroleum and Energy Studies, India

sumber :

: http://www.inderscience.com/info/ingeneral/cfp.php?id=3898 PEMBAHASAN

A. Judul Judul dari artikel jurnal adalah "Technological Innovation in SDN/NFV, Cloud Computing and Big Data"dari judul tersebut di jelaskan berbagai macam model komunikasi data dan juga komponen. B. Gaya Penulisan Sistematika cukup tersusun dengan baik. mulai dari judul, latar belakang, abstrak, tujuan, pengertian, dan kesimpulan, namun terlalu simple. Tidak terdapat kata kunci (keywoard) dalam penelitian. c. Abstrak Penjelasan dalam abstrak tidak di paparkan, bahwa jurnal ini membahas tentang Technological Innovation in SDN/NFV, Cloud Computing and Big Data, yang di bahas dalam abstrak ini ialah pengertian komunikasi data, masih terdapat kata-kata yang kurang di pahami. d. Tujuan Sudah cukup lumayan puas walaupun ada point yang kurang di pahami dengan isi dari jurnal. e. Pendahuluan Pendahuluan dalam jurnal tersebut diatas menjelaskan tentang bagaimana Inovasi Teknologi. Yang cukup jelas dan menarik sebelum membahas bagaimana inovasi teknologi akan berkembang. Selain itu, dalam pendahauluan tersebut menerangkan bagaimana inovasi teknologi akan mempengaruhi berbagai aspek. f. Kesimpulan Terdapat pembahasan dari technological inovation yang di ringkas menjadi sederhana. Dan ada beberapa kata yang tidak di pahami f. Saran Dokumen konferensi hanya dapat diajukan jika surat kabar telah ditulis ulang sepenuhnya dan jika izin tertulis yang sesuai telah diperoleh dari pemegang hak cipta dari karya asli.