NLADSS: Design of Connectivity as a Service (CaaS) Model using Node-Level Augmentation & Dynamic Sleep Scheduling for Heterogeneous Wireless Network Handoffs

Abstract

Seamless connectivity is need-of-the-hour for high-speed wireless networks. With the advent of 5th Generation (5G) wireless devices, users from different networks require inter-network connectivity with minimum packet drops, and maximum bit-rate. In order to perform this task, high efficiency handover models are proposed, which evaluate various network-level parameters including trust-levels, capacity, Quality of Service (QoS), etc. These algorithms also evaluate various node level metrics which include end-to-end delay, Received Signal Strength Indicator (RSSI), movement patterns, etc. in order to map the nodes to relevant networks. The drawback of proposed approaches is their inability to cater high-speed environments without causing QoS degradation. Moreover, most of these models do not consider node-level augmentations, which restricts their performance when applied to real-world scenarios. In order to remove these drawbacks and make the algorithms perform well with high speed environments without QoS degradation, we propose the design of a novel Connectivity as a Service (CaaS) model that uses Node-Level Augmentation & Dynamic Sleep Scheduling (NLADSS) for high efficiency heterogeneous wireless network handoffs. It was observed that the proposed algorithm is able to achieve a handoff efficiency of 98% for 5G heterogeneous networks, which outperforms most of the recently proposed models. The proposed model also aims at providing immutability, traceability, and high-performance distributed computing, while not compromising on QoS performance of the network.