Towards a Traffic-Aware Cloud-Native Cellular Core
Abstract
Advances in virtualization technologies have revolutionized the design of the core of cellular networks. However, the adoption of microservice design patterns and migration of services from purpose-built hardware to virtualized hardware has adversely affected the delivery of latency-sensitive services. In this dissertation, we make a case for cloud-native (microservice container packaged) network functions in the cellular core by proposing domain knowledge-driven, traffic-aware, orchestration frameworks to make network placement decisions. We begin by evaluating the suitability of virtualization technologies for the cellular core and demonstrating that container-driven deployments can significantly outperform other virtualization technologies such as Virtual Machines for control and data plane applications. To support the deployment of latency-sensitive applications on virtualized hardware, we propose using Virtual Network Function (VNF) bundles (aggregates) to handle transactions. Specifically, we design Invenioto leverage a combination of network traces and domain knowledge to identify VNFs involved in processing a specific transaction, which are then collocated by a traffic-aware orchestrator. By ensuring that a user request is processed by a single aggregate of collocated VNFs, Invenio can significantly reduce end-to-end latencies and improve user experience. Finally, to understand the challenges in using container-driven deployments in real-world applications, we develop and evaluate a novel caller-ID spoofing detection solution in Voice over LTE (VoLTE) calls. Our proposed solution, NASCENT, cross validates the caller-ID used during voice-call signaling with a previously authenticated caller-ID to detect caller-ID spoofing. Our evaluation with traditional and container-driven deployments shows that container-driven deployment can not only support complex cellular services but also outperform traditional deployments.
Degree
Ph.D.
Advisors
Fahmy, Purdue University.
Subject Area
Computer science
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