scholarly journals The Turing O-Machine and the DIME Network Architecture: Injecting the Architectural Resiliency into Distributed Computing

10.29007/44jw ◽  
2018 ◽  
Author(s):  
Rao Mikkilineni ◽  
Albert Comparini ◽  
Giovanni Morana
Keyword(s):  
Distributed Computing ◽  
Network Architecture ◽  
Ad Hoc ◽  
Virtual Machines ◽  
Internal State ◽  
Fractal Theory ◽  
Intelligent Computing ◽  
Computing Model ◽  
Transaction Security ◽  
Computing Machines

Turing’s o-machine discussed in his PhD thesis can perform all of the usual operations of a Turing machine and in addition, when it is in a certain internal state, can also query an oracle for an answer to a specific question that dictates its further evolution. In his thesis, Turing said 'We shall not go any further into the nature of this oracle apart from saying that it cannot be a machine.’ There is a host of literature discussing the role of the oracle in AI, modeling brain, computing, and hyper-computing machines. In this paper, we take a broader view of the oracle machine inspired by the genetic computing model of cellular organisms and the self-organizing fractal theory. We describe a specific software architecture implementation that circumvents the halting and un-decidability problems in a process workflow computation to introduce the architectural resiliency found in cellular organisms into distributed computing machines. A DIME (Distributed Intelligent Computing Element), recently introduced as the building block of the DIME computing model, exploits the concepts from Turing’s oracle machine and extends them to implement a recursive managed distributed computing network, which can be viewed as an interconnected group of such specialized oracle machines, referred to as a DIME network. The DIME network architecture provides the architectural resiliency through auto-failover; auto-scaling; live-migration; and end-to-end transaction security assurance in a distributed system. We demonstrate these characteristics using prototypes without the complexity introduced by hypervisors, virtual machines and other layers of ad-hoc management software in today’s distributed computing environments.

scholarly journals Service Virtualization Using a Non-von Neumann Parallel, Distributed, and Scalable Computing Model

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Rao Mikkilineni ◽  
Giovanni Morana ◽  
Daniele Zito ◽  
Marco Di Sano
Keyword(s):  
Distributed Computing ◽  
Performance Management ◽  
Virtual Machines ◽  
Dynamic Performance ◽  
Parallel Execution ◽  
Self Management ◽  
Transaction Management ◽  
Von Neumann ◽  
Computing Model ◽  
End To End

This paper describes a prototype implementing a high degree of transaction resilience in distributed software systems using a non-von Neumann computing model exploiting parallelism in computing nodes. The prototype incorporates fault, configuration, accounting, performance, and security (FCAPS) management using a signaling network overlay and allows the dynamic control of a set of distributed computing elements in a network. Each node is a computing entity endowed with self-management and signaling capabilities to collaborate with similar nodes in a network. The separation of parallel computing and management channels allows the end-to-end transaction management of computing tasks (provided by the autonomous distributed computing elements) to be implemented as network-level FCAPS management. While the new computing model is operating system agnostic, a Linux, Apache, MySQL, PHP/Perl/Python (LAMP) based services architecture is implemented in a prototype to demonstrate end-to-end transaction management with auto-scaling, self-repair, dynamic performance management and distributed transaction security assurance. The implementation is made possible by a non-von Neumann middleware library providing Linux process management through multi-threaded parallel execution of self-management and signaling abstractions. We did not use Hypervisors, Virtual machines, or layers of complex virtualization management systems in implementing this prototype.

Architectural Resiliency in Distributed Computing

2012 ◽  
Vol 4 (4) ◽  
pp. 37-51
Author(s):  
Rao Mikkilineni
Keyword(s):  
Operating System ◽  
Distributed Computing ◽  
Performance Optimization ◽  
Network Architecture ◽  
Autonomic Computing ◽  
Management Practices ◽  
Dynamic Performance ◽  
Distributed Computing Systems ◽  
Computing Model ◽  
Distributed Transaction

Cellular organisms have evolved to manage themselves and their interactions with their surroundings with a high degree of resiliency, efficiency and scalability. Signaling and collaboration of autonomous distributed computing elements accomplishing a common goal with optimal resource utilization are the differentiating characteristics that contribute to the computing model of cellular organisms. By introducing signaling and self-management abstractions in an autonomic computing element called Distributed Intelligent Managed Element (DIME), the authors improve the architectural resiliency, efficiency, and scaling in distributed computing systems. Described are two implementations of DIME network architecture to demonstrate auto-scaling, self-repair, dynamic performance optimization, and end to end distributed transaction management. By virtualizing a process (by converting it into a DIME) in the Linux operating system and also building a new native operating system called Parallax OS optimized for Intel-multi-core processors, which converts each core into a DIME, implications of the DIME computing model to future cloud computing services and datacenter infrastructure management practices and discuss the relationship of the DIME computing model to current discussions on Turing machines, Gödel’s theorems and a call for no less than a Kuhnian paradigm shift by some computer scientists.

Implementing Distributed, Self-Managing Computing Services Infrastructure using a Scalable, Parallel and Network-Centric Computing Model

2012 ◽  
pp. 57-78 ◽  
Author(s):  
Rao Mikkilineni ◽  
Giovanni Morana ◽  
Ian Seyler
Keyword(s):  
Cloud Computing ◽  
Network Architecture ◽  
Virtual Machines ◽  
Von Neumann ◽  
Accounting Performance ◽  
Computing Model ◽  
Computing Services ◽  
Many Core ◽  
Distributed Cloud ◽  
Process Level

This chapter introduces a new network-centric computing model using Distributed Intelligent Managed Element (DIME) network architecture (DNA). A parallel signaling network overlay over a network of self-managed von Neumann computing nodes is utilized to implement dynamic fault, configuration, accounting, performance, and security management of both the nodes and the network based on business priorities, workload variations and latency constraints. Two implementations of the new computing model are described which demonstrate the feasibility of the new computing model. One implementation provides service virtualization at the Linux process level and another provides virtualization of a core in a many-core processor. Both point to an alternative way to assure end-to-end transaction reliability, availability, performance, and security in distributed Cloud computing, reducing current complexity in configuring and managing virtual machines and making the implementation of Federation of Clouds simpler.

scholarly journals An Ad Hoc Random Initialization Deep Neural Network Architecture for Discriminating Malignant Breast Cancer Lesions in Mammographic Images

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Andrea Duggento ◽  
Marco Aiello ◽  
Carlo Cavaliere ◽  
Giuseppe L. Cascella ◽  
Davide Cascella ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Network Architecture ◽  
Ad Hoc ◽  
False Negative ◽  
Selection Criterion ◽  
Current Status ◽  
Clinical Image ◽  
Imaging Data ◽  
Breast Cancer Death ◽  
Random Initialization

Breast cancer is one of the most common cancers in women, with more than 1,300,000 cases and 450,000 deaths each year worldwide. In this context, recent studies showed that early breast cancer detection, along with suitable treatment, could significantly reduce breast cancer death rates in the long term. X-ray mammography is still the instrument of choice in breast cancer screening. In this context, the false-positive and false-negative rates commonly achieved by radiologists are extremely arduous to estimate and control although some authors have estimated figures of up to 20% of total diagnoses or more. The introduction of novel artificial intelligence (AI) technologies applied to the diagnosis and, possibly, prognosis of breast cancer could revolutionize the current status of the management of the breast cancer patient by assisting the radiologist in clinical image interpretation. Lately, a breakthrough in the AI field has been brought about by the introduction of deep learning techniques in general and of convolutional neural networks in particular. Such techniques require no a priori feature space definition from the operator and are able to achieve classification performances which can even surpass human experts. In this paper, we design and validate an ad hoc CNN architecture specialized in breast lesion classification from imaging data only. We explore a total of 260 model architectures in a train-validation-test split in order to propose a model selection criterion which can pose the emphasis on reducing false negatives while still retaining acceptable accuracy. We achieve an area under the receiver operatic characteristics curve of 0.785 (accuracy 71.19%) on the test set, demonstrating how an ad hoc random initialization architecture can and should be fine tuned to a specific problem, especially in biomedical applications.

Network Architecture and Wireless Ad Hoc Routing for Airborne Internet Services

2021 ◽  
Author(s):  
Abdullah Numani ◽  
Sardar Muhammad Gulfam ◽  
Muhammad Awais Javed ◽  
Bilal Muhammad ◽  
Ramjee Prasad ◽  
...  
Keyword(s):  
Network Architecture ◽  
Ad Hoc ◽  
Internet Services ◽  
Ad Hoc Routing ◽  
Wireless Ad Hoc Routing

scholarly journals LISP Optimisation of Mobile Data Streaming in Connected Societies

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
T. Balan ◽  
D. Robu ◽  
F. Sandu
Keyword(s):  
Public Transportation ◽  
Network Architecture ◽  
Virtual Machines ◽  
Transportation Systems ◽  
Urban Environments ◽  
Data Streaming ◽  
Host Mobility ◽  
And Migration ◽  
Public Transportation Systems ◽  
Load Balanced

Mobility mechanisms are key elements of “always connected” smart environments. Since the first mobile IPv4 protocols, the IP mobility solutions have evolved from host mobility to network mobility and migration to IPv6, but there are still use-cases to be covered, especially for redundant multihomed scenarios. Also mobility does not refer only to hosts or individuals, but also to code/applications and to virtual machines. LISP (Locator/Identifier Separation Protocol) can contribute to new solutions for both host mobility and virtual machine mobility (e.g., inside enterprise data centers) by the separation of the identifier and location of a network endpoint. The aim of this paper is to propose a LISP based multihome and load-balanced network architecture for urban environments. Validation is done in an emulated environment for the case of an enterprise with distributed locations, but, furthermore, we extrapolate to other mobile urban scenarios, like the case of providing reliable load-balanced and secured Internet in Public Transportation Systems, with a proposal for an open-source implementation.

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