With recent advancements in machine-to-machine (M2M), the demand for fastest communication is an utmost concern of the M2M technology. The advent of 5G telecommunication networks enables to bridge the demand on satisfying the Quality-of-Service (QoS) concerns in M2M communication. The massive number of devices in M2M communication is henceforth do not lie under limited resource allocation by embedding the 5G telecommunication network. In this paper, we address the above limitation of allocation the resource to prominent M2M devices using Adaptive Neuro Fuzzy Inference System (ANFIS). In ANFIS, the adoption of rules will imply the resource allocation with the devices of top priority and it reduces based on the priority. The ANFIS controller acts as a central controller that implies the resource allocation with its rules on the M2M devices. The simulation is performed to test the efficacy of fuzzy logic system on allocation 5G resources to M2M model. The results show that the ANFIS model achieves higher level of allocating the resources than other existing methods in terms of reduced network delay, increased throughput, packet delivery rate and energy efficiency.
The geographic routing protocol (GRP) in general seeks the location of sensor nodes to decide the routing path in mobile ad hoc network. This increases the routing overhead while finding the location of nodes. On other hand, the GRP undergoes location inaccuracy and routing void problem. In order to resolve this, in this paper, Gray Wolf Optimization (GWO) is used. This GWO is responsible for proper selection of nodes selected by GRP based on the parameters and selection criteria in order to forward the packets to the next forwarding nodes to reach its destination. The simulation is carried out effectively between the GWO-GRP and existing ACO and fuzzy based GRP with varying network densities. The simulation results show that the GWO-GRP method achieves reduced average delay, increased network lifetime and reduced energy consumption than other methods. Further, it avoids the problems associated with GRP i.e. the location inaccuracy and routing void problem.
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