266,604 research outputs found

    On Signaling-Free Failure Dependent Restoration in All-Optical Mesh Networks

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    Failure dependent protection (FDP) is known to achieve optimal capacity efficiency among all types of protection, at the expense of longer recovery time and more complicated signaling overhead. This particularly hinders the usage of FDP in all-optical mesh networks. As a remedy, the paper investigates a new restoration framework that enables all-optical fault management and device configuration via state-of-the-art failure localization techniques, such that the FDP restoration process. It can be implemented without relying on any control plane signaling. With the proposed restoration framework, a novel spare capacity allocation problem is defined, and is further analyzed on circulant topologies for any single link failure, aiming to gain a solid understanding of the problem. By allowing reuse of monitoring resources for restoration capacity, we are particularly interested in the monitoring resource hidden property where less or even no monitoring resources are consumed as more working traffic is in place. To deal with general topologies, we introduce a novel heuristic approach to the proposed spare capacity allocation problem, which comprises a generic FDP survivable routing scheme followed by a novel monitoring resource allocation method. Extensive simulation is conducted to examine the proposed scheme and verify the proposed restoration framework

    Network-based telemetry to facilitate the programmable management plane for optical transport infrastructure

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    Large network operator environments are composed of thousands of nodes and devices capable of performing multiple roles. This network infrastructure is multi-layered, multi-vendor and underpinned by a high capacity and complex optical transport network. Managing this network requires millions of lines of configuration files and hundreds of Operational Support Systems. Typically, the management data structure uses a hierarchical namespace containing tens of thousands of object identifiers (OID). Each OID identifies a variable that can be read, modified or set via management protocol. The British Telecom network collects many millions of OIDs every 10 minutes, and executes many thousands of configuration changes per month via many tools, and multiple generations of protocols, data models and software components. Blending Software Defined Network (SDN) model-driven management and Network Functions Virtualisation (NFV), for on-demand (scale-in and scale-out) virtual network functions (Big Data nodes, network heuristics and analytics), provides an exciting opportunity for significant operational savings: reduced outage impact, simplification of management stack, fault correlation and network healing, and network usage trending for efficient resource allocation and scaling. This paper and talk outlines the management plane challenges and use cases for complex tier-1 optical environments. It discusses how we need to rethink network analytics and embrace streaming telemetry for real-time resource adaptation. It outlines a guiding network telemetry framework being developed by leading operators and the enabling community-driven technologies, and how they may be used to facilitate the programmable management plane for optical transport infrastructure

    Load Balancing and Virtual Machine Allocation in Cloud-based Data Centers

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    As cloud services see an exponential increase in consumers, the demand for faster processing of data and a reliable delivery of services becomes a pressing concern. This puts a lot of pressure on the cloud-based data centers, where the consumers’ data is stored, processed and serviced. The rising demand for high quality services and the constrained environment, make load balancing within the cloud data centers a vital concern. This project aims to achieve load balancing within the data centers by means of implementing a Virtual Machine allocation policy, based on consensus algorithm technique. The cloud-based data center system, consisting of Virtual Machines has been simulated on CloudSim – a Java based cloud simulator
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