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Internet of Things network cognition and traffic management system

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Abstract

In a world of ever increasing technological diversity and an advancing ‘Internet of Things’ (IoTs), business landscapes are changing. New conditions alter the way in which competence resources are regarded and how they need to be managed in order for organizations to sustain as successful actors in a knowledge economy. Information technology play an important role in this new setting, including network management systems for handling information concerning competence resources. This research focus on smart IoTs traffic management system, which is advertised by minimal cost, long scalability, great compatibility, easy to promote, to replace conventional traffic management system and the proposed approach can develop public road traffic enormously. The aim of this research proposed to develop an IoT public traffic adaptive detection system and proficient of supposing the travel time associated with each street sector based on the traffic information streamlined every 18 s, which sequentially finds the path with the minimal travel time in the traffic network by using a dynamic procedure.

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Authors and Affiliations

  1. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China

    Abida Sharif, Jian Ping Li & Muhammad Irfan Sharif

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  1. Abida Sharif
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  2. Jian Ping Li
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  3. Muhammad Irfan Sharif
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Correspondence to Abida Sharif.

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Sharif, A., Li, J.P. & Sharif, M.I. Internet of Things network cognition and traffic management system. Cluster Comput 22 (Suppl 6), 13209–13217 (2019). https://doi.org/10.1007/s10586-018-1722-1

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  • DOI: https://doi.org/10.1007/s10586-018-1722-1

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