The Experts below are selected from a list of 20505 Experts worldwide ranked by ideXlab platform

Timos Sellis - One of the best experts on this subject based on the ideXlab platform.

  • big data analytics in telecommunications literature review and architecture recommendations
    IEEE CAA Journal of Automatica Sinica, 2020
    Co-Authors: Hira Zahid, Tariq Mahmood, Ahsan Morshed, Timos Sellis
    Abstract:

    This paper focuses on facilitating state-of-the-art applications of big data analytics ( BDA ) architectures and infrastructures to telecommunications ( telecom ) industrial sector. Telecom companies are dealing with terabytes to petabytes of data on a daily basis. IoT applications in telecom are further contributing to this data deluge. Recent advances in BDA have exposed new opportunities to get actionable insights from telecom big data. These benefits and the fast-changing BDA Technology landscape make it important to investigate existing BDA applications to telecom sector. For this, we initially determine published research on BDA applications to telecom through a systematic literature review through which we filter 38 articles and categorize them in frameworks, use cases, literature reviews, white papers and experimental validations. We also discuss the benefits and challenges mentioned in these articles. We find that experiments are all proof of concepts ( POC ) on a severely limited BDA Technology Stack ( as compared to the available Technology Stack ) , i.e., we did not find any work focusing on full-fledged BDA implementation in an operational telecom environment. To facilitate these applications at research-level, we propose a state-of-the-art lambda architecture for BDA pipeline implementation ( called LambdaTel ) based completely on open source BDA technologies and the standard Python language, along with relevant guidelines. We discovered only one research paper which presented a relatively-limited lambda architecture using the proprietary AWS cloud infrastructure. We believe LambdaTel presents a clear roadmap for telecom industry practitioners to implement and enhance BDA applications in their enterprises.

Peter Chiu - One of the best experts on this subject based on the ideXlab platform.

  • the challenges of developing an open source standards based Technology Stack to deliver the latest uk climate projections
    International Journal of Digital Earth, 2012
    Co-Authors: Ag Stephens, Philip James, D Alderson, S Pascoe, Simon Abele, Peter Chiu
    Abstract:

    Abstract To improve the understanding of local and regional effects of climate change, the UK government supported the development of new climate projections. The Met Office Hadley Centre produced a sophisticated set of probabilistic projections for future climate. This paper discusses the design and implementation of an interactive website to deliver those projections to a broad user community. The interface presents complex data sets, generates on-the-fly products and schedules jobs to an offline weather generator capable of outputting gigabytes of data in response to a single request. A robust and scalable physical architecture was delivered through significant use of open source technologies and open standards.

Hira Zahid - One of the best experts on this subject based on the ideXlab platform.

  • big data analytics in telecommunications literature review and architecture recommendations
    IEEE CAA Journal of Automatica Sinica, 2020
    Co-Authors: Hira Zahid, Tariq Mahmood, Ahsan Morshed, Timos Sellis
    Abstract:

    This paper focuses on facilitating state-of-the-art applications of big data analytics ( BDA ) architectures and infrastructures to telecommunications ( telecom ) industrial sector. Telecom companies are dealing with terabytes to petabytes of data on a daily basis. IoT applications in telecom are further contributing to this data deluge. Recent advances in BDA have exposed new opportunities to get actionable insights from telecom big data. These benefits and the fast-changing BDA Technology landscape make it important to investigate existing BDA applications to telecom sector. For this, we initially determine published research on BDA applications to telecom through a systematic literature review through which we filter 38 articles and categorize them in frameworks, use cases, literature reviews, white papers and experimental validations. We also discuss the benefits and challenges mentioned in these articles. We find that experiments are all proof of concepts ( POC ) on a severely limited BDA Technology Stack ( as compared to the available Technology Stack ) , i.e., we did not find any work focusing on full-fledged BDA implementation in an operational telecom environment. To facilitate these applications at research-level, we propose a state-of-the-art lambda architecture for BDA pipeline implementation ( called LambdaTel ) based completely on open source BDA technologies and the standard Python language, along with relevant guidelines. We discovered only one research paper which presented a relatively-limited lambda architecture using the proprietary AWS cloud infrastructure. We believe LambdaTel presents a clear roadmap for telecom industry practitioners to implement and enhance BDA applications in their enterprises.

Ag Stephens - One of the best experts on this subject based on the ideXlab platform.

  • the challenges of developing an open source standards based Technology Stack to deliver the latest uk climate projections
    International Journal of Digital Earth, 2012
    Co-Authors: Ag Stephens, Philip James, D Alderson, S Pascoe, Simon Abele, Peter Chiu
    Abstract:

    Abstract To improve the understanding of local and regional effects of climate change, the UK government supported the development of new climate projections. The Met Office Hadley Centre produced a sophisticated set of probabilistic projections for future climate. This paper discusses the design and implementation of an interactive website to deliver those projections to a broad user community. The interface presents complex data sets, generates on-the-fly products and schedules jobs to an offline weather generator capable of outputting gigabytes of data in response to a single request. A robust and scalable physical architecture was delivered through significant use of open source technologies and open standards.

Chonggang Wang - One of the best experts on this subject based on the ideXlab platform.

  • a scalable standards based approach for iot data sharing and eco system monetization
    IEEE Internet of Things Journal, 2020
    Co-Authors: K Figueredo, D Seed, Chonggang Wang
    Abstract:

    The full potential of IoT data is often unrealized because data are restricted to single-purpose use-cases or accessible to a few, siloed users. The opportunities are significantly greater when data can be shared using a marketplace concept. This provides a framework where many suppliers of data can interact with consumers of data, such as AI developers and IoT service providers. Their marketplace interactions provide a means to identify demand for specific types of data and, to incentivize suppliers to offer high quality and dependable data. Standardization is a pre-requisite for an effective marketplace in terms of setting the rules for interactions and in establishing a technical baseline for data supply and consumption. This paper introduces an IoT data marketplace framework and illustrates its application through a set of smart city and intelligent transport system deployments. It highlights use of oneM2M, which is an open standard for the middleware layer in the IoT Technology Stack. oneM2M’s middleware capabilities reside between IoT devices and communications networks and, the AI/ML and IoT applications that consume IoT data. The proposed IoT data marketplace also includes licensing, usage tracking and secured data sharing features. These provide marketplace users with the tools to control data sharing and monetization. Through reference to multiple deployments of the IoT data marketplace, the paper highlights the benefits of standardization for replicable solutions in multiple IoT segments, interoperability, and business model innovation involving multi-stakeholder ecosystems.