741 research outputs found

    Spare capacity modelling and its applications in survivable iP-over-optical networks

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    As the interest in IP-over-optical networks are becoming the preferred core network architecture, survivability has emerged as a major concern for network service providers; a result of the potentially huge traffic volumes that will be supported by optical infrastructure. Therefore, implementing recovery strategies is critical. In addition to the traditional recovery schemes based around protection and restoration mechanisms, pre-allocated restoration represents a potential candidate to effect and maintain network resilience under failure conditions. Preallocated restoration technique is particularly interesting because it provides a trade-off in terms of recovery performance and resources between protection and restoration schemes. In this paper, the pre-allocated restoration performance is investigated under single and dual-link failures considering a distributed GMPLSbased IP/WDM mesh network. Two load-based spare capacity optimisation methods are proposed in this paper; Local Spare Capacity Optimisation (LSCO) and Global Spare Capacity Optimisation (GSCO)

    Survey on Data-Centric based Routing Protocols for Wireless Sensor Networks

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    The great concern for energy that grew with the technological advances in the field of networks and especially in sensor network has triggered various approaches and protocols that relate to sensor networks. In this context, the routing protocols were of great interest. The aim of the present paper is to discuss routing protocols for sensor networks. This paper will focus mainly on the discussion of the data-centric approach (COUGAR, rumor, SPIN, flooding and Gossiping), while shedding light on the other approaches occasionally. The functions of the nodes will be discussed as well. The methodology selected for this paper is based on a close description and discussion of the protocol. As a conclusion, open research questions and limitations are proposed to the reader at the end of this paper

    Mobility Management in beyond 3G-Environments

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    Beyond 3G-environments are typically defined as environments that integrate different wireless and fixed access network technologies. In this paper, we address IP based Mobility Management (MM) in beyond 3G-environments with a focus on wireless access networks, motivated by the current trend of WiFi, GPRS, and UMTS networks. The GPRS and UMTS networks provide countrywide network access, while the WiFi networks provide network access in local areas such as city centres and airports. As a result, mobile end-users can be always on-line and connected to their preferred network(s), these network preferences are typically stored in a user profile. For example, an end-user who wishes to be connected with highest bandwidth could be connected to a WiFi network when available and fall back to GPRS when moving outside the hotspot area.\ud In this paper, we consider a combination of MM for legacy services (like web browsing, telnet, etc.) using Mobile IP and multimedia services using SIP. We assume that the end-user makes use of multi-interface terminals with the capability of selecting one or more types of access networks\ud based on preferences. For multimedia sessions, like VoIP or streaming video, we distinguish between changes in network access when the end-user is in a session or not in a session. If the end-user is not in a session, he or she needs to be able to start new sessions and receive invitations for new sessions. If the end-user is in a session, the session needs to be handed over to the new access network as seamless as possible from the perspective of the end-user. We propose an integrated but flexible solution to these problems that facilitates MM with a customizable transparency to applications and end-users

    Route recovery schemes for link and node failure and link congestion

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    Link/Node failure occurs frequently causing service disruption in computer networks. Hardware techniques have been developed to protect the network from Link/Node failure. These techniques work in physical layer, therefore their convergence time is very small. On the other hand, many schemes have been proposed to mitigate the failure influence on the network. These schemes work in upper layers such as the network layer. However, hardware solutions faster than other schemes, but they are expensive. Link/Node failure causes all flows which were using the failed link/node are temporarily interrupted till a new path reestablished. Three recovery algorithms have been proposed that mitigate the changes occur in the network. These changes are link/node failure and link congestion. The algorithms mainly pre-compute a backup next hop for each destination in the network. This path is feasible to accommodate re-routed traffic when a failure occurs without causing congestion or loops. Simulations have been conducted to show the performance of the proposed algorithms using ns2 network simulation tool. The results show fast recovery for all flows were using the link/node failure. Furthermore, the throughput per node also increases due to decrease interruption service time

    Artificial intelligence (AI) methods in optical networks: A comprehensive survey

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    Producción CientíficaArtificial intelligence (AI) is an extensive scientific discipline which enables computer systems to solve problems by emulating complex biological processes such as learning, reasoning and self-correction. This paper presents a comprehensive review of the application of AI techniques for improving performance of optical communication systems and networks. The use of AI-based techniques is first studied in applications related to optical transmission, ranging from the characterization and operation of network components to performance monitoring, mitigation of nonlinearities, and quality of transmission estimation. Then, applications related to optical network control and management are also reviewed, including topics like optical network planning and operation in both transport and access networks. Finally, the paper also presents a summary of opportunities and challenges in optical networking where AI is expected to play a key role in the near future.Ministerio de Economía, Industria y Competitividad (Project EC2014-53071-C3-2-P, TEC2015-71932-REDT
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