Building Robust and Optimized Cloud-Native Mobile Networks

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The demand for high-bandwidth network connectivity - with extremely stringent performance requirements stemming from the combined need for remote control of devices/machines/entities in real or near real-time, realization of augmented reality, and the ability to provide high-resolution visual/spatial, tactile/haptic, and other sensory data to offer an immersive experience - has been growing significantly over the past few years. As much as this rapid increase represents a business opportunity for mobile operators, it also creates pressing network capacity/requirements challenges in need of a timely response. Investing in additional infrastructure is always there as a solution. However, this is far from a magic wand in this situation since the return-on-capital investments can be minimal. It is undeniable that upgrading network capacity depends heavily on the infrastructure upon which the network relies. However, realizing the true potential of a specific hardware setup is an objective that has more realistic room for improvement and visible impact. Operators are in insistent search for an innovative game-changing solution to elevate the network capacity beyond the expected network performance levels. Furthermore, network operators are juggling other multi-layered challenges as critical as increasing demand. Increasing energy, financial and social costs coupled with the lack of personnel with expertise to design, implement, and orchestrate a progressively complex hardware-based infrastructure are the primary concerns of operators. The scope of these issues is not limited merely to revenue loss; ripple effects manifest through lags in time-to-market, as well as supply chain challenges and general hindrances to innovation within the Information and Communications Technologies (ICT) industries. Network Function Virtualization (NFV), Mobile Edge Computing (MEC), Artificial Intelligence/Machine Learning (AI/ML), and Software-Defined Networking (SDN) technologies gained more momentum offering a gateway to reduced capital and operating (CAPEX and OPEX) expenditure budgets, improved flexibility, scalability and portability, ease of development, and time-to-market applications releases. Empowered with the ability to facilitate flexible hardware and software decoupling and the means to achieve more effective capital investments with higher returns on capital, NFV, AI/ML, SDN and MEC technologies are/have the potential to revolutionize the telecommunications industry. In this research program, the applicant aims to investigate and develop a AI-driven end-to-end continuous orchestration architectural framework that extends to the extreme edge and efficiently support the stringent requirements of future applications while considering network resource utilization, and the rapidly changing computing resource market.