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Intelligent Internet of things in wireless networks

Intelligent Internet of things in wireless networks

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Nowadays, intelligence Internet of things (IoT) wireless networks are the most promising technologies for intelligent future applications, since it takes the advantages of artificial intelligence for sensing and data analysis to develop a new generation of smarter IoT applications around everywhere. Next-generation wireless networks are expected to support extremely high data rates and radically new applications, which require a new wireless radio technology paradigm. The challenge is that of assisting the radio in intelligent adaptive learning and decisionmaking so that the diverse requirements of next-generation wireless networks can be satisfied. Machine learning is one of the most promising artificial intelligence tools, conceived to support smart radio terminals. The main challenge for future IoT networks is how to cope with such complex systems, where a huge number of devices compete for limited wireless resources and where heterogeneity is everincreasing. There is an urgent need for more intelligent networks that lead to more interoperable solutions and that can make autonomous decisions on optimal operation modes and configurations. In IoT wireless networks, the AI can insure to collect only adequate data in order to reduce the processing time of big data amount sent by sensors. To manage big data and store it in IoT networks, AI processes play a major role in data integration, selection, classification, and mining, as well as assessment of information patterns. It offers unique solutions in decision-making, measurement, and contribution to the construction of IoT networks with a new, fast, and intelligent character. In this chapter, we will provide intelligence IoT wireless networks in addition to the AI contribution in programming and configuring of IoT network devices. This chapter will also introduce the algorithms and strategy of intelligence related to cognitive IoT networks and quality of service, in addition to the benefits of cognitive and SDN to IoT operations in heterogeneous networks.

Chapter Contents:

  • 6.1 Introduction
  • 6.2 IoT networks
  • 6.2.1 LPWAN IoT networks
  • 6.2.2 Cognitive IoT networks
  • 6.2.3 Dynamic IoT networks
  • 6.2.4 Semantics intelligent IoT networks
  • 6.3 Reprogrammable and reconfigurable of IoT devices
  • 6.4 Open source platforms in IoT networks
  • 6.4.1 Cognitive IoT-based LPWAN
  • 6.4.2 SDN over IoT network
  • 6.5 Analysis IoT network context
  • 6.6 Intelligent IoT network algorithms and strategy
  • 6.7 Heterogeneous IoT-based 5G networks
  • 6.8 IoT network adaptive quality of service
  • 6.8.1 Q-learning algorithm
  • 6.8.2 Deep generative network
  • 6.9 Summary
  • References

Inspec keywords: artificial intelligence; data analysis; open systems; learning (artificial intelligence); Internet of Things

Other keywords: heterogeneous networks; IoT network devices; extremely high data rates; adequate data; wireless radio technology paradigm; wireless resources; intelligence IoT wireless networks; smarter IoT applications; promising artificial intelligence tools; smart radio terminals; IoT operations; data integration; intelligent future applications; intelligent adaptive; cognitive IoT networks; intelligent networks; big data amount; radically new applications; future IoT networks; intelligence Internet; next-generation wireless networks; sensing data analysis; intelligent character; things wireless networks

Subjects: Mobile radio systems; Data handling techniques; Radio links and equipment; Computer communications; Information networks

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