Millimeter-wave technology is rising as a crucial component for 5G radio access and other emerging ancillary wireless networks including Gb/s device-to-device communication and mobile backhaul. This paper envisions that millimeter-wave cognitive radio in 5G network is a proposed smart energy consumption solution of Internet of Things (IoT) devices. Improving resource efficiency and enhancing data rates, resource sharing is a proposed advantage over millimeter wave cognitive radio in 5G IoT network. IoT Fog collaboration is proposed to apply artificial intelligence techniques to offer important energy-saving services allowing integrated systems to perceive, reason, learn, and act intelligently in intelligent gateway control. Smart energy meters are the current energy-saving utility in the flexible deployment of IoT architecture. NarrowBand IoT (NB-IoT) delivers Low Power Wide Area access (LPWA) to a new generation of connected things in the race to 5G IoT network, reducing energy computation and achieving promising network capacity. The renewable energy strategy is a proposed energy-efficiency solution in IoT network, maximizing the power supply while minimizing power consumption. A novel kind of visible light communications (VLC) is proposed to enable mmWave cognitive radio receiver in 5G IoT network. Simulation results show the proposed solution can reap the benefits of higher data rates, more IoT device connectivity, and lower energy consumption.
To fulfill various enhanced requirements of next generation wireless access, 5 G cellular network will drive towards higher energy efficiency, lower latency and higher reliable wireless networks. The key contributions can summarize as follows: (1) proposes frame-based max-weight scheduling (FMWS) with reconfiguration delay in combination of round–robin algorithm can dynamically control throughput and delay. The frame-based dynamic control (FBDC) policy is applicable to 5 G cellular network control systems in data link layer, provides a new framework for developing throughput-optimal network control policies using state-action frequencies. (2) proposes a novel approach in MAC layer--Virtual multichannels Parallelism Carrier Sense Multiple Access (VMCP-CSMA) which can compute a set of TDDM schedules for multiple channels at once rather than computing one schedule at a time and constantly switching or recomputing schedules. (3) proposes a novel criticality aware scheduler prioritization in VMCP-CSMA policy can reorder a set of TDDM schedules based on max-weight scheduling with reconfiguration delay according to different application requirements. It can achieve high throughput and low delay with low complexity compared with other schedulings.
This paper proposes an Energy-efficient Secured Distributed Collaborative Neighbor Discovery protocol for IoT mobile sensing applications to enhance on IoT capabilities and efficiencies. Maximum throughput access control model with ultra-low-power constraints is proposed for blockchain-based IoT framework. Simulation result demonstrates the proposed protocol can achieve better discovery performance with minimum discovery latency and maximum duty cycle. Analysis of the comparison results present best choice of primes and duty cycle in the designed low-complexity algorithm.
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