10,684 research outputs found

    New tree-based algorithms for network spare capacity design

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    Survivable network design has become increasingly important due to the need for reliable communication service. One of its important components is the spare capacity design. Its main purpose is to provide cost-efficient spare capacity reservation at certain survivability level in case of predicted failures. In this thesis, we study various kinds of network survivability techniques and the corresponding algorithms. Subsequently; we introduce our two pre-planned path restoration algorithms for spare capacity design in mesh-like networks. They can get higher utilization of spare capacity and reasonable reaction time. First one is a spanning tree based algorithm with backup parents, which needs much less spare capacity than the well known hierarchical tree algorithm while the restorability is slightly higher or lower. The second algorithm is a cycle tree based algorithm with backup parents and some extra cycle edges. Simulation results show that this algorithm works much better on restorability than the other two algorithms. The time complexities of the two new algorithms are: O ( n 4 ), where n is the total number of nodes in the network. The space complexities are the same too: O ( n 3

    Optimal Algorithms for Near-Hitless Network Restoration via Diversity Coding

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    Diversity coding is a network restoration technique which offers near-hitless restoration, while other state-of-the art techniques are significantly slower. Furthermore, the extra spare capacity requirement of diversity coding is competitive with the others. Previously, we developed heuristic algorithms to employ diversity coding structures in networks with arbitrary topology. This paper presents two algorithms to solve the network design problems using diversity coding in an optimal manner. The first technique pre-provisions static traffic whereas the second technique carries out the dynamic provisioning of the traffic on-demand. In both cases, diversity coding results in smaller restoration time, simpler synchronization, and much reduced signaling complexity than the existing techniques in the literature. A Mixed Integer Programming (MIP) formulation and an algorithm based on Integer Linear Programming (ILP) are developed for pre-provisioning and dynamic provisioning, respectively. Simulation results indicate that diversity coding has significantly higher restoration speed than Shared Path Protection (SPP) and p-cycle techniques. It requires more extra capacity than the p-cycle technique and SPP. However, the increase in the total capacity is negligible compared to the increase in the restoration speed.Comment: An old version of this paper is submitted to IEEE Globecom 2012 conferenc

    On the Optimality of Virtualized Security Function Placement in Multi-Tenant Data Centers

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    Security and service protection against cyber attacks remain among the primary challenges for virtualized, multi-tenant Data Centres (DCs), for reasons that vary from lack of resource isolation to the monolithic nature of legacy middleboxes. Although security is currently considered a property of the underlying infrastructure, diverse services require protection against different threats and at timescales which are on par with those of service deployment and elastic resource provisioning. We address the resource allocation problem of deploying customised security services over a virtualized, multi-tenant DC. We formulate the problem in Integral Linear Programming (ILP) as an instance of the NP-hard variable size variable cost bin packing problem with the objective of maximising the residual resources after allocation. We propose a modified version of the Best Fit Decreasing algorithm (BFD) to solve the problem in polynomial time and we show that BFD optimises the objective function up to 80% more than other algorithms

    Optimization in Telecommunication Networks

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    Network design and network synthesis have been the classical optimization problems intelecommunication for a long time. In the recent past, there have been many technologicaldevelopments such as digitization of information, optical networks, internet, and wirelessnetworks. These developments have led to a series of new optimization problems. Thismanuscript gives an overview of the developments in solving both classical and moderntelecom optimization problems.We start with a short historical overview of the technological developments. Then,the classical (still actual) network design and synthesis problems are described with anemphasis on the latest developments on modelling and solving them. Classical results suchas Mengerā€™s disjoint paths theorem, and Ford-Fulkersonā€™s max-flow-min-cut theorem, butalso Gomory-Hu trees and the Okamura-Seymour cut-condition, will be related to themodels described. Finally, we describe recent optimization problems such as routing andwavelength assignment, and grooming in optical networks.operations research and management science;

    Multipoint-to-multipoint network communication

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    We have formulated an exact ILP model for the problem of communicating on a virtual network. While this ILP model was successful in solving small problems, it is not recommended to handle larger instances, due to the fact that the number of variables in the model grows exponentially as the graph size grows. However, this ILP model can provide a benchmark for heuristic algorithms developed for this problem. We have also described a heuristic approach, and explored several variants of the algorithm. We found a solution that seems to perform well with reasonable computation time. The heuristic is able to find solutions that respect the degree constraints, but show a small number of violations of the desired time constraints. Tests on small problems show that heuristic is not always able to find feasible solutions, even though the exact method has shown they exist. It would be interesting in the future to look at whether insights gained by looking at exact solutions can be used to improve the heuristic

    WiLiTV: A Low-Cost Wireless Framework for Live TV Services

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    With the evolution of HDTV and Ultra HDTV, the bandwidth requirement for IP-based TV content is rapidly increasing. Consumers demand uninterrupted service with a high Quality of Experience (QoE). Service providers are constantly trying to differentiate themselves by innovating new ways of distributing content more efficiently with lower cost and higher penetration. In this work, we propose a cost-efficient wireless framework (WiLiTV) for delivering live TV services, consisting of a mix of wireless access technologies (e.g. Satellite, WiFi and LTE overlay links). In the proposed architecture, live TV content is injected into the network at a few residential locations using satellite dishes. The content is then further distributed to other homes using a house-to-house WiFi network or via an overlay LTE network. Our problem is to construct an optimal TV distribution network with the minimum number of satellite injection points, while preserving the highest QoE, for different neighborhood densities. We evaluate the framework using realistic time-varying demand patterns and a diverse set of home location data. Our study demonstrates that the architecture requires 75 - 90% fewer satellite injection points, compared to traditional architectures. Furthermore, we show that most cost savings can be obtained using simple and practical relay routing solutions

    Enabling Work-conserving Bandwidth Guarantees for Multi-tenant Datacenters via Dynamic Tenant-Queue Binding

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    Today's cloud networks are shared among many tenants. Bandwidth guarantees and work conservation are two key properties to ensure predictable performance for tenant applications and high network utilization for providers. Despite significant efforts, very little prior work can really achieve both properties simultaneously even some of them claimed so. In this paper, we present QShare, an in-network based solution to achieve bandwidth guarantees and work conservation simultaneously. QShare leverages weighted fair queuing on commodity switches to slice network bandwidth for tenants, and solves the challenge of queue scarcity through balanced tenant placement and dynamic tenant-queue binding. QShare is readily implementable with existing switching chips. We have implemented a QShare prototype and evaluated it via both testbed experiments and simulations. Our results show that QShare ensures bandwidth guarantees while driving network utilization to over 91% even under unpredictable traffic demands.Comment: The initial work is published in IEEE INFOCOM 201
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