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Computing infrastructure issues in distributed communications systems : a survey of operating system transport system architectures
The performance of distributed applications (such as file transfer, remote login, tele-conferencing, full-motion video, and scientific visualization) is influenced by several factors that interact in complex ways. In particular, application performance is significantly affected both by communication infrastructure factors and computing infrastructure factors. Several communication infrastructure factors include channel speed, bit-error rate, and congestion at intermediate switching nodes. Computing infrastructure factors include (among other things) both protocol processing activities (such as connection management, flow control, error detection, and retransmission) and general operating system factors (such as memory latency, CPU speed, interrupt and context switching overhead, process architecture, and message buffering). Due to a several orders of magnitude increase in network channel speed and an increase in application diversity, performance bottlenecks are shifting from the network factors to the transport system factors.This paper defines an abstraction called an "Operating System Transport System Architecture" (OSTSA) that is used to classify the major components and services in the computing infrastructure. End-to-end network protocols such as TCP, TP4, VMTP, XTP, and Delta-t typically run on general-purpose computers, where they utilize various operating system resources such as processors, virtual memory, and network controllers. The OSTSA provides services that integrate these resources to support distributed applications running on local and wide area networks.A taxonomy is presented to evaluate OSTSAs in terms of their support for protocol processing activities. We use this taxonomy to compare and contrast five general-purpose commercial and experimental operating systems including System V UNIX, BSD UNIX, the x-kernel, Choices, and Xinu
CYCLONE Unified Deployment and Management of Federated, Multi-Cloud Applications
Various Cloud layers have to work in concert in order to manage and deploy
complex multi-cloud applications, executing sophisticated workflows for Cloud
resource deployment, activation, adjustment, interaction, and monitoring. While
there are ample solutions for managing individual Cloud aspects (e.g. network
controllers, deployment tools, and application security software), there are no
well-integrated suites for managing an entire multi cloud environment with
multiple providers and deployment models. This paper presents the CYCLONE
architecture that integrates a number of existing solutions to create an open,
unified, holistic Cloud management platform for multi-cloud applications,
tailored to the needs of research organizations and SMEs. It discusses major
challenges in providing a network and security infrastructure for the
Intercloud and concludes with the demonstration how the architecture is
implemented in a real life bioinformatics use case
Matching model of flow table for networked big data
Networking for big data has to be intelligent because it will adjust data
transmission requirements adaptively during data splitting and merging.
Software-defined networking (SDN) provides a workable and practical paradigm
for designing more efficient and flexible networks. Matching strategy in the
flow table of SDN switches is most crucial. In this paper, we use a
classification approach to analyze the structure of packets based on the
tuple-space lookup mechanism, and propose a matching model of the flow table in
SDN switches by classifying packets based on a set of fields, which is called
an F-OpenFlow. The experiment results show that the proposed F-OpenFlow
effectively improves the utilization rate and matching efficiency of the flow
table in SDN switches for networked big data.Comment: 14 pages, 6 figures, 2 table
Fog Computing: A Taxonomy, Survey and Future Directions
In recent years, the number of Internet of Things (IoT) devices/sensors has
increased to a great extent. To support the computational demand of real-time
latency-sensitive applications of largely geo-distributed IoT devices/sensors,
a new computing paradigm named "Fog computing" has been introduced. Generally,
Fog computing resides closer to the IoT devices/sensors and extends the
Cloud-based computing, storage and networking facilities. In this chapter, we
comprehensively analyse the challenges in Fogs acting as an intermediate layer
between IoT devices/ sensors and Cloud datacentres and review the current
developments in this field. We present a taxonomy of Fog computing according to
the identified challenges and its key features.We also map the existing works
to the taxonomy in order to identify current research gaps in the area of Fog
computing. Moreover, based on the observations, we propose future directions
for research
Analysis domain model for shared virtual environments
The field of shared virtual environments, which also
encompasses online games and social 3D environments, has a
system landscape consisting of multiple solutions that share great functional overlap. However, there is little system interoperability between the different solutions. A shared virtual environment has an associated problem domain that is highly complex raising difficult challenges to the development process, starting with the architectural design of the underlying system. This paper has two main contributions. The first contribution is a broad domain analysis of shared virtual environments, which enables developers to have a better understanding of the whole rather than the part(s). The second contribution is a reference domain model for discussing and describing solutions - the Analysis Domain Model
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