<p>This paper discusses the concurrent offloading of data in a multi-platform configuration consisting of cloud and fog. <Emphasis FontCategory="SansSerif">IoT</Emphasis>&#xa0;devices feed these platforms with data that need to be stored, processed, and/or shared. However, some devices could be illegitimate leading to overloading the cloud/fog platforms with irrelevant data. To cope with extra loads, some platforms offload, sometimes concurrently, these loads to other peers that are selected based on their trustworthiness levels. To mitigate the risks of dealing with illegitimate <Emphasis FontCategory="SansSerif">IoT</Emphasis>&#xa0;devices and untrustworthy platforms, this paper fosters trust between all stakeholders as well as synchronizes concurrent offloading of data using both Allen’s interval algebra and coordination relations. A set of experiments using a real dataset demonstrate the feasibility of satisfying time constraints during concurrent offloading of data.</p>

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Time-constrained concurrent data-offloading in the cloud and fog

  • Zakaria Maamar,
  • Noura Faci,
  • Fadwa Yahya,
  • Ejub Kajan

摘要

This paper discusses the concurrent offloading of data in a multi-platform configuration consisting of cloud and fog. IoT devices feed these platforms with data that need to be stored, processed, and/or shared. However, some devices could be illegitimate leading to overloading the cloud/fog platforms with irrelevant data. To cope with extra loads, some platforms offload, sometimes concurrently, these loads to other peers that are selected based on their trustworthiness levels. To mitigate the risks of dealing with illegitimate IoT devices and untrustworthy platforms, this paper fosters trust between all stakeholders as well as synchronizes concurrent offloading of data using both Allen’s interval algebra and coordination relations. A set of experiments using a real dataset demonstrate the feasibility of satisfying time constraints during concurrent offloading of data.