93,298 research outputs found
Software defined networking: meeting carrier grade requirements
Software Defined Networking is a networking paradigm which allows network operators to manage networking elements using software running on an external server. This is accomplished by a split in the architecture between the forwarding element and the control element. Two technologies which allow this split for packet networks are ForCES and Openflow. We present energy efficiency and resilience aspects of carrier grade networks which can be met by Openflow. We implement flow restoration and run extensive experiments in an emulated carrier grade network. We show that Openflow can restore traffic quite fast, but its dependency on a centralized controller means that it will be hard to achieve 50 ms restoration in large networks serving many flows. In order to achieve 50 ms recovery, protection will be required in carrier grade networks
Cloud Storage and Bioinformatics in a private cloud deployment: Lessons for Data Intensive research
This paper describes service portability for a private cloud deployment, including a detailed case study about Cloud Storage and bioinformatics services developed as part of the Cloud Computing Adoption Framework (CCAF). Our Cloud Storage design and deployment is based on Storage Area Network (SAN) technologies, details of which include functionalities, technical implementation, architecture and user support. Experiments for data services (backup automation, data recovery and data migration) are performed and results confirm backup automation is completed swiftly and is reliable for data-intensive research. The data recovery result confirms that execution time is in proportion to quantity of recovered data, but the failure rate increases in an exponential manner. The data migration result confirms execution time is in proportion to disk volume of migrated data, but again the failure rate increases in an exponential manner. In addition, benefits of CCAF are illustrated using several bioinformatics examples such as tumour modelling, brain imaging, insulin molecules and simulations for medical training. Our Cloud Storage solution described here offers cost reduction, time-saving and user friendliness
Prototype of Fault Adaptive Embedded Software for Large-Scale Real-Time Systems
This paper describes a comprehensive prototype of large-scale fault adaptive
embedded software developed for the proposed Fermilab BTeV high energy physics
experiment. Lightweight self-optimizing agents embedded within Level 1 of the
prototype are responsible for proactive and reactive monitoring and mitigation
based on specified layers of competence. The agents are self-protecting,
detecting cascading failures using a distributed approach. Adaptive,
reconfigurable, and mobile objects for reliablility are designed to be
self-configuring to adapt automatically to dynamically changing environments.
These objects provide a self-healing layer with the ability to discover,
diagnose, and react to discontinuities in real-time processing. A generic
modeling environment was developed to facilitate design and implementation of
hardware resource specifications, application data flow, and failure mitigation
strategies. Level 1 of the planned BTeV trigger system alone will consist of
2500 DSPs, so the number of components and intractable fault scenarios involved
make it impossible to design an `expert system' that applies traditional
centralized mitigative strategies based on rules capturing every possible
system state. Instead, a distributed reactive approach is implemented using the
tools and methodologies developed by the Real-Time Embedded Systems group.Comment: 2nd Workshop on Engineering of Autonomic Systems (EASe), in the 12th
Annual IEEE International Conference and Workshop on the Engineering of
Computer Based Systems (ECBS), Washington, DC, April, 200
A Data Distribution Service in a hierarchical SDN architecture: implementation and evaluation
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Software-defined networks (SDNs) have caused a paradigm shift in communication networks as they enable network programmability using either centralized or distributed controllers. With the development of the industry and society, new verticals have emerged, such as Industry 4.0, cooperative sensing and augmented reality. These verticals require network robustness and availability, which forces the use of distributed domains to improve network scalability and resilience. To this aim, this paper proposes a new solution to distribute SDN domains by using Data Distribution Services (DDS). The DDS allows the exchange of network information, synchronization among controllers and auto-discovery. Moreover, it increases the control plane robustness, an important characteristic in 5G networks (e.g., if a controller fails, its resources and devices can be managed by other controllers in a short amount of time as they already know this information). To verify the effectiveness of the DDS, we design a testbed by integrating the DDS in SDN controllers and deploying these controllers in different regions of Spain. The communication among the controllers was evaluated in terms of latency and overhead.Postprint (author's final draft
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