Visible to the public Post-Turing Computing, Hierarchical Named Networks and a New Class of Edge Computing

TitlePost-Turing Computing, Hierarchical Named Networks and a New Class of Edge Computing
Publication TypeConference Paper
Year of Publication2019
AuthorsMikkilineni, Rao, Morana, Giovanni
Conference Name2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)
ISBN Number978-1-7281-0676-2
Keywordsbiological systems, cellular organisms, Church-Turing thesis, cloud computing, Cognition, control theory, Control Theory and Resiliency, Cyber physical system, cyber physical systems, Dynamic Configuration, dynamic reconfiguration, Edge Cloud, edge cloud platform, edge computing, hierarchical named network, Hierarchical named networks, Human Behavior, inductive Turing machines, info-computation, IP address base networks, knowledge structures, Kubernetes, kubernetes provisioning stack, live-migration, living beings, managed process workflow, microservices, named microservice network, named service connections, Neural networks, Platina systems, post-turing computing, pubcrawl, resilience, Resiliency, Scalability, service network, Software systems, stored program control machines, structural machine framework, structural machines, Turing machine, Turing machines, virtual machine overlay, virtual machines
Abstract

Advances in our understanding of the nature of cognition in its myriad forms (Embodied, Embedded, Extended, and Enactive) displayed in all living beings (cellular organisms, animals, plants, and humans) and new theories of information, info-computation and knowledge are throwing light on how we should build software systems in the digital universe which mimic and interact with intelligent, sentient and resilient beings in the physical universe. Recent attempts to infuse cognition into computing systems to push the boundaries of Church-Turing thesis have led to new computing models that mimic biological systems in encoding knowledge structures using both algorithms executed in stored program control machines and neural networks. This paper presents a new model and implements an application as hierarchical named network composed of microservices to create a managed process workflow by enabling dynamic configuration and reconfiguration of the microservice network. We demonstrate the resiliency, efficiency and scaling of the named microservice network using a novel edge cloud platform by Platina Systems. The platform eliminates the need for Virtual Machine overlay and provides high performance and low-latency with L3 based 100 GbE network and SSD support with RDMA and NVMeoE. The hierarchical named microservice network using Kubernetes provisioning stack provides all the cloud features such as elasticity, autoscaling, self-repair and live-migration without reboot. The model is derived from a recent theoretical framework for unification of different models of computation using "Structural Machines.'' They are shown to simulate Turing machines, inductive Turing machines and also are proved to be more efficient than Turing machines. The structural machine framework with a hierarchy of controllers managing the named service connections provides dynamic reconfiguration of the service network from browsers to database to address rapid fluctuations in the demand for or the availability of resources without having to reconfigure IP address base networks.

URLhttps://ieeexplore.ieee.org/document/8795415
DOI10.1109/WETICE.2019.00024
Citation Keymikkilineni_post-turing_2019