964 research outputs found

    Heuristic Solution to Protect Communications in WDM Networks using P-cycles

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    Optical WDM mesh networks are able to transport huge amount of information. The use of such technology however poses the problem of protection against failures such as fibre cuts. One of the principal methods for link protection used in optical WDM networks is pre-configured protection cycle (p-cycle). The major problem of this method of protection resides in finding the optimal set of p-cycles which protect the network for a given distribution of working capacity. Existing heuristics generate a large set of p-cycle candidates which are entirely independent of the network state, and from then the good sub-set of p-cycles which will protect the network is selected. In this paper, we propose a new algorithm of generation of p-cycles based on the incremental aggregation of the shortest cycles. Our generation of p-cycles depends on the state of the network. This enables us to choose an efficient set of p-cycles which will protect the network. The set of p-cycles that we generate is the final set which will protect the network, in other words our heuristic does not go through the additional step of p-cycle selectio

    Design of survivable WDM network based on pre-configured protection cycle

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    Wavelength Division Multiplexing (WDM) is an important technique which allows the trans- port of large quantities of data over optical networks. All optical WDM-based networks have been used to improve overall communication capacity and provide an excellent choice for the design of backbone networks. However, due to the high traffic load that each link can carry in a WDM network, survivability against failures becomes very important. Survivability in this context is the ability of the network to maintain continuity of service against failures, since a failure can lead to huge data losses. In recent years, many survivability mechanisms have been studied and their performance assessed through capacity efficiency, restoration time and restorability. Survivability mechanisms for ring and mesh topologies have received particular attention

    Optimized Design of Survivable MPLS over Optical Transport Networks. Optical Switching and Networking

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    In this paper we study different options for the survivability implementation in MPLS over Optical Transport Networks in terms of network resource usage and configuration cost. We investigate two approaches to the survivability deployment: single layer and multilayer survivability and present various methods for spare capacity allocation (SCA) to reroute disrupted traffic. The comparative analysis shows the influence of the traffic granularity on the survivability cost: for high bandwidth LSPs, close to the optical channel capacity, the multilayer survivability outperforms the single layer one, whereas for low bandwidth LSPs the single layer survivability is more cost-efficient. For the multilayer survivability we demonstrate that by mapping efficiently the spare capacity of the MPLS layer onto the resources of the optical layer one can achieve up to 22% savings in the total configuration cost and up to 37% in the optical layer cost. Further savings (up to 9 %) in the wavelength use can be obtained with the integrated approach to network configuration over the sequential one, however, at the increase in the optimization problem complexity. These results are based on a cost model with actual technology pricing and were obtained for networks targeted to a nationwide coverage

    Design and operation of mesh-restorable WDM networks

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    The explosive growth of Web-related services over the Internet is bringing millions of new users online, thus creating a growing demand for bandwidth. Wavelength Division Multiplexed (WDM) networks, employing wavelength routing has emerged as the dominant technology to satisfy this growing demand for bandwidth. As the amount of traffic carried is larger, any single failure can be catastrophic. Survivability becomes indispensable in such networks. Therefore, it is imperative to design networks that can quickly and efficiently recover from failures.;In this dissertation, we explore the design and operation of survivable optical networks. We study several survivability paradigms for surviving single link failures. A restoration model is developed based on a combination of these paradigms. We propose an optimal design and upgrade scheme for WDM backbone networks. We formulate an integer programming-based design problem to minimize the total facility cost. This framework provides a cost effective way of upgrading the network by identifying how much resources to budget at each stage of network evolution. This results in significant cost reductions for the network service provider.;As part of network operation, we capture multiple operational phases in survivable network operation as a single integer programming formulation. This common framework incorporates service disruption and includes a service differentiation model based on lightpath protection. However, the complexity of the optimization problem makes the formulation applicable only for network provisioning and o2ine reconfiguration. The direct use of such methods for online reconfiguration remains limited to small networks with few tens of wavelengths. We develop a heuristic algorithm based on LP relaxation technique for fast, near optimal, online reconfiguration. Since the ILP variables are relaxed, we provide a way to derive a feasible solution from the relaxed problem. Most of the current approaches assume centralized information. They do not scale well as they rely on per-flow information. This motivates the need for developing dynamic algorithms based on partial information. The partial information we use can be easily obtained from traffic engineering extensions to routing protocols. Finally, the performance of partial information routing algorithms is compared through simulation studies

    Resilience options for provisioning anycast cloud services with virtual optical networks

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    Optical networks are crucial to support increasingly demanding cloud services. Delivering the requested quality of services (in particular latency) is key to successfully provisioning end-to-end services in clouds. Therefore, as for traditional optical network services, it is of utter importance to guarantee that clouds are resilient to any failure of either network infrastructure (links and/or nodes) or data centers. A crucial concept in establishing cloud services is that of network virtualization: the physical infrastructure is logically partitioned in separate virtual networks. To guarantee end-to-end resilience for cloud services in such a set-up, we need to simultaneously route the services and map the virtual network, in such a way that an alternate routing in case of physical resource failures is always available. Note that combined control of the network and data center resources is exploited, and the anycast routing concept applies: we can choose the data center to provide server resources requested by the customer to optimize resource usage and/or resiliency. This paper investigates the design of scalable optimization models to perform the virtual network mapping resiliently. We compare various resilience options, and analyze their compromise between bandwidth requirements and resiliency quality

    Survivable mesh-network design & optimization to support multiple QoP service classes

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    Every second, vast amounts of data are transferred over communication systems around the world, and as a result, the demands on optical infrastructures are extending beyond the traditional, ring-based architecture. The range of content and services available from the Internet is increasing, and network operations are constantly under pressure to expand their optical networks in order to keep pace with the ever increasing demand for higher speed and more reliable links

    Exploring the benefit of rerouting multi-period traffic to multi-site data centers

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    In cloud-like scenarios, demand is served at one of multiple possible data center (DC) destinations. Usually, the exact DC that is used can be freely chosen, which leads to an anycast routing problem. Furthermore, the demand volume is expected to change over time, e.g., following a diurnal pattern. Given that virtually all application domains today rely heavily on cloud-like services, it is important that the backbone networks connecting users to the DCs are resilient against failures. In this paper, we consider the problem of resiliently routing multi-period traffic: we need to find routes to both a primary DC and a backup DC (to be used in the case of failure of the primary one, or of the network connection to it), and also account for synchronization traffic between the primary and backup DCs. We formulate this as an optimization problem and adopt column generation, using a path formulation in two sub-problems: the (restricted) master problem selects "configurations" to use for each demand in each of the time epochs it lasts, while the pricing problem (PP) constructs a new "configuration" that can lead to lower overall costs (which we express as the number of network resources, i.e., bandwidth, required to serve the demand). Here, a "configuration" is defined by the network paths followed from the demand source to each of the two selected DCs, as well as that of the synchronization traffic in between the DCs. Our decomposition allows for PPs to be solved in parallel, for which we quantitatively explore the reduction in the time required to solve the overall routing problem. The key question that we address with our model is an exploration of the potential benefits of rerouting traffic from one time epoch to the next: we compare several (re) routing strategies, allowing traffic that spans multiple time periods to i) not be rerouted in different periods, ii) only change the backup DC and routes, or iii) freely change both primary and backup DC choices and the routes toward them

    Selecting the best locations for data centers in resilient optical grid/cloud dimensioning

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    For optical grid/cloud scenarios, the dimensioning problem comprises not only deciding on the network dimensions (i.e., link bandwidths), but also choosing appropriate locations to install server infrastructure (i.e., data centers), as well as determining the amount of required server resources (for storage and/or processing). Given that users of such grid/cloud systems in general do not care about the exact physical locations of the server resources, a degree of freedom arises in choosing for each of their requests the most appropriate server location. We will exploit this anycast routing principle (i.e., source of traffic is given, but destination can be chosen rather freely) also to provide resilience: traffic may be relocated to alternate destinations in case of network/server failures. In this study, we propose to jointly optimize the link dimensioning and the location of the servers in an optical grid/cloud, where the anycast principle is applied for resiliency against either link or server node failures. While the data center location problem has some resemblance with either the classical p-center or k-means location problems, the anycast principle makes it much more difficult due to the requirement of link disjoint paths for ensuring grid resiliency
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