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BIOTRUST: A Novel Biologically Inspired Optimal TRusted User Social Trait-Aware Association for Wireless Proximity Services in 5G and Beyond
Abstract
In the 5G and post-5G networks, the IMT-2020 demand among the devices in terms of throughput, reliability, low-latency and security can be observed. The intensive demand inside the network is imposed upon the network to obtain the required Quality-of-Service (QoS) to fulfill the demand. This leads to introduction of device-centric network configuration, where network can offload objectives for optimal resource allocation to the edge devices. The connectivity to ensure that required QoS is termed as trust in this research. Device-to-Device (D2D) communication is integrated in the next-generation wireless network, which facilitates optimal offloaded trust allocation in the network. From the network perspective, device trust is calculated centrally. But during device-to-device association, the trust value of the device is associated locally by the associating user. The distribution of the load and resource allocation among the devices thus lead to flexibly serving different network requirement based services: Ultra-Reliable Low-Latency Communication (URLLC), Enhanced Mobile Broadband (eMBB), Proximity Services (ProSe), Mission Critical Push To Talk (MCPTT), massive-Machine Type Communication (mMTC), etc. These services comprise of reliable low latency communication to high performing mobile broadband in the nodes. The reliability of these variety of services depends on optimal device-centric association for the last-mile network organization. The proposed measures take user-device mobility, socialness and behavior into account and prove the optimality in the device association. The novelty of the proposed optimal measures relies on capturing sporadic behavioral transition and ensuring associations in the network for hand-offs and maximal throughput. In this research, a novel biologically inspired definition of user-device trust-based interaction has been provided and the measures are proposed to find optimal joint user-device trust. The research proves the optimality of the proposed social-behavioral measures and achieves 50-100% more throughput and 6-100 times more probability of association retention compared to social aware algorithms. The guaranteed maximal throughput and association is obtained by achieving 200% more trust compared to conventional social-aware algorithms.
Subject Area
Computer Engineering|Computer science|Engineering
Recommended Citation
Banerjee, Subharthi, "BIOTRUST: A Novel Biologically Inspired Optimal TRusted User Social Trait-Aware Association for Wireless Proximity Services in 5G and Beyond" (2020). ETD collection for University of Nebraska-Lincoln. AAI27956364.
https://digitalcommons.unl.edu/dissertations/AAI27956364