184 research outputs found

    Survivability and performance optimization in communication networks using network coding

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    The benefits of network coding are investigated in two types of communication networks: optical backbone networks and wireless networks. In backbone networks, network coding is used to improve survivability of the network against failures. In particular, network coding-based protection schemes are presented for unicast and multicast traffic models. In the unicast case, network coding was previously shown to offer near-instantaneous failure recovery at the bandwidth cost of shared backup path protection. Here, cost-effective polynomial-time heuristic algorithms are proposed for online provisioning and protection of unicast traffic. In the multicast case, network coding is used to extend the traditional live backup (1+1) unicast protection to multicast protection; hence called multicast 1+1 protection. It provides instantaneous recovery for single failures in any bi-connected network with the minimum bandwidth cost. Optimal formulation and efficient heuristic algorithms are proposed and experimentally evaluated. In wireless networks, performance benefits of network coding in multicast transmission are studied. Joint scheduling and performance optimization formulations are presented for rate, energy, and delay under routing and network coding assumptions. The scheduling component of the problem is simplified by timesharing over randomly-selected sets of non-interfering wireless links. Selecting only a linear number of such sets is shown to be rate and energy effective. While routing performs very close to network coding in terms of rate, the solution convergence time is around 1000-fold compared to network coding. It is shown that energy benefit of network coding increases as the multicast rate demand is increased. Investigation of energy-rate and delay-rate relationships shows both parameters increase non-linearly as the multicast rate is increased

    All-Optical Network Coding

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    In this paper, we investigate the application of network coding to all-optical networks from both the algorithmic and infrastructural perspectives. We study the effectiveness of using network coding for optical-layer dedicated protection of multicast traffic which provides robustness against link failures in the network. We present a heuristic for solving this problem and compare it with both inefficient optimal methods and non-network coding approaches. Our experiments show that our heuristic provides near optimal performance while significantly outperforming existing approaches for dedicated multicast protection. We also propose architectures for specialized all-optical circuits capable of performing the processing required for network coding and show how these devices can be effectively deployed in an all-optical multicast network

    Energy Efficient IP over WDM Networks Using Network Coding

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    In this thesis we propose the use of network coding to improve the energy efficiency in core networks, by reducing the resources required to process traffic flows at intermediate nodes. We study the energy efficiency of the proposed scheme through three approaches: (i) developing a mixed integer linear programme (MILP) to optimise the use of network resources. (ii) developing a heuristic based on minimum hop routing. (iii) deriving an analytical bounds and closed form expressions. The results of the MILP model show that implementing network coding over typical networks can introduce savings up to 33% compared to the conventional architectures. The results of the heuristic show that the energy efficient minimum hop routing in network coding enabled networks achieves power savings approaching those of the MILP model. The analytically calculated power savings also confirm the savings achieved by the model. Furthermore, we study the impact of network topology on the savings obtained by implementing network coding. The results show that the savings increase as the hop count of the network topology increases. Using the derived expressions, we calculated the maximum power savings for regular topologies as the number of nodes grows. The power savings asymptotically approach 45% and 23% for the ring (and line) and star topology, respectively. We also investigate the use of network coding in 1+1 survivable IP over WDM networks. We study the energy efficiency of this scheme through MILP, a heuristic with five operating options, and analytical bounds. We evaluate the MILP and the heuristics on typical and regular network topologies. Implementing network coding can produce savings up to 37% on the ring topology and 23% considering typical topologies. We also study the impact of varying the demand volumes on the network coding performance. We also develop analytical bounds for the conventional 1+1 protection and the 1+1 with network coding to verify the results of the MILP and the heuristics and study the impact of topology, focusing on the full mesh and ring topologies, providing a detailed analysis considering the impact of the network size

    Overlay networks for smart grids

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    Robustness to failures in two-layer communication networks

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    A close look at many existing systems reveals their two- or multi-layer nature, where a number of coexisting networks interact and depend on each other. For instance, in the Internet, any application-level graph (such as a peer-to-peer network) is mapped on the underlying IP network that, in turn, is mapped on a mesh of optical fibers. This layered view sheds new light on the tolerance to errors and attacks of many complex systems. What is observed at a single layer does not necessarily reflect well the state of the entire system. On the contrary, a tiny, seemingly harmless disruption of one layer, may destroy a substantial or essential part of another layer, thus making the whole system useless in practice. In this thesis we consider such two-layer systems. We model them by two graphs at two different layers, where the upper-layer (or logical) graph is mapped onto the lower-layer (physical) graph. Our main goals are the following. First, we study the robustness to failures of existing large-scale two-layer systems. This brings us some valuable insights into the problem, e.g., by identifying common weak points in such systems. Fortunately, these two-layer problems can often be effectively alleviated by a careful system design. Therefore, our second major goal is to propose new designs that increase the robustness of two-layer systems. This thesis is organized in three main parts, where we focus on different examples and aspects of the two-layer system. In the first part, we turn our attention to the existing large-scale two-layer systems, such as peer-to-peer networks, railway networks and the human brain. Our main goal is to study the vulnerability of these systems to random errors and targeted attacks. Our simulations show that (i) two-layer systems are much more vulnerable to errors and attacks than they appear from a single layer perspective, and (ii) attacks are much more harmful than errors, especially when the logical topology is heterogeneous. These results hold across all studied systems. A natural next step consists in improving the failure robustness of two-layer systems. In particular, in the second part of this thesis, we consider the IP/WDM optical networks, where an IP backbone network is mapped on a mesh of optical fibers. The problem lies in designing a survivable mapping, such that no single physical failure disconnects the logical topology. This is an NP-complete problem. We introduce a new concept of piecewise survivability, which makes the problem much easier in practice. This leads us to an efficient and scalable algorithm called SMART, which finds a survivable mapping much faster (often by orders of magnitude) than the other approaches proposed to date. Moreover, the formal analysis of SMART allows us to prove that a given survivable mapping does or does not exist. Finally, this approach helps us to find vulnerable areas in the system, and to effectively reinforce them, e.g., by adding new links. In the third part of this thesis, we shift our attention one layer higher, to the application-over-IP setting. In particular, we consider the design of Application-Level Multicast (ALM) for interactive applications, where a single source sends a delay-constrained data stream to a number of destinations. Interactive ALM should (i) respect stringent delay requirements, and (ii) proactively protect the system against overlay node failures and against (iii) the packet losses at the IP layer. We propose a two-layer-aware approach to this problem. First, we prove that the average packet loss rate observed at the destinations can be effectively approximated by a purely topological metric that, in turn, drops with the amount of IP-level and overlay-level path diversity available in the system. Therefore, we propose a framework that accommodates and generalizes various techniques to increase the path diversity in the system. Within this framework we optimize the structure of ALM. As a result, we reduce the effective loss rate of real Internet topologies by typically 30%-70%, compared to the state of the art. Finally, in addition to the three main parts of the thesis, we also present a set of results inspired by the study of ALM systems, but not directly related to the 'two-layer' paradigm (and thus moved to the Appendix). In particular, we consider a transmission of a delay-sensitive data stream from a single source to a single destination, where the data packets are protected by a Forward Error Correction (FEC) code and sent over multiple paths. We show that the performance of such a scheme can often be further improved. Our key observation is that the propagation times on the available paths often significantly differ, typically by 10-100ms. We propose to exploit these differences by appropriate packet scheduling, which results in a two- to five-fold improvement (reduction) in the effective loss rate

    Joint dimensioning of server and network infrastructure for resilient optical grids/clouds

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    We address the dimensioning of infrastructure, comprising both network and server resources, for large-scale decentralized distributed systems such as grids or clouds. We design the resulting grid/cloud to be resilient against network link or server failures. To this end, we exploit relocation: Under failure conditions, a grid job or cloud virtual machine may be served at an alternate destination (i.e., different from the one under failure-free conditions). We thus consider grid/cloud requests to have a known origin, but assume a degree of freedom as to where they end up being served, which is the case for grid applications of the bag-of-tasks (BoT) type or hosted virtual machines in the cloud case. We present a generic methodology based on integer linear programming (ILP) that: 1) chooses a given number of sites in a given network topology where to install server infrastructure; and 2) determines the amount of both network and server capacity to cater for both the failure-free scenario and failures of links or nodes. For the latter, we consider either failure-independent (FID) or failure-dependent (FD) recovery. Case studies on European-scale networks show that relocation allows considerable reduction of the total amount of network and server resources, especially in sparse topologies and for higher numbers of server sites. Adopting a failure-dependent backup routing strategy does lead to lower resource dimensions, but only when we adopt relocation (especially for a high number of server sites): Without exploiting relocation, potential savings of FD versus FID are not meaningful
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