The survivable virtual topology routing problem is to route a virtual topology graph on a optical fiber physical topology such that the virtual topology remains connected when failures occur in the physical topology. In this work we study the problem of survivable virtual topology routing under single node/SRLG (Shared Risk Link Group) failure model. We prove that the survivable virtual topology routing problem under node/SRLG failures is NP-complete. We present an improved integer linear programming (ILP) formulation for computing the survivable routing of a virtual topology graph. However, ILP is not scalable when the network size scales more than a few tens of nodes. In this work, we present sub-classes of graphs which more accurately model an actual network and for which a survivable routing can be easily computed solving an ILP. We successfully computed the survivable routing of virtual topologies belonging to these sub-classes against link/SRLG failures for topologies of size up to 24 nodes.
Abstract-survivable routing of a connection involves computation of a pair of diverse routes such that at most one mute fails when failures occur in the network topology. A subset of links in the network that share the risk of failure at the same time are said to belong to a Shared Risk Link Gmup (SRLG) [3]. A network with shared risk link groups defined over its links is an SRLG network. A failure of an SRLG is equivalent to the failure of all the links in the SRLG. For a connection to he survivahle in an SRLG network its working and protection paths must he routed on SRLG diverse paths. SRLG diverse routing problem has been proved to he NP-complete in [l] According to the quality of service requirement of a survivable connection request, dedicated protection or shared protection can be used to establish the connection request.With dedicated protection, the connection is established on both the SRLG diverse working and protection paths. The simplest heuristic for computing SRLG diverse path pair is the two-step approach, hut it suffers from the trap topology problem. In [Z] an iterative heuristic (ITSH) using the two-step approach was proposed to compute least cost SRLG diverse path pair. Suurhalle's algorithm computes a pair of least cost linkdisjoint paths between a node pair. In this work we present a modified Suurhalle's heuristic for computing the SRLG diverse routes between a node pair. We then propose an iterative heuristic (IMSH) which uses the modified Suurballe's heuristic for computing the least cost SRLG diverse routes. We also present an 1/2-cost-improvement optimality check criterion for dedicated protection.
Network survivability is one of the most important issues in the design of optical WDM networks. In this work we study the problem of survivable routing of a virtual topology on a physical topology with Shared Risk Link Groups (SRLG). The survivable virtual topology routing problem against single-link failures in the physical topology is proved to be NP-complete in [1]. We prove that survivable virtual topology routing problem against SRLG/node failures is also NP-complete. We present an improved integer linear programming (ILP) formulation (in comparison to [1]) for computing the survivable routing under SRLG/node failures. Using an ILP solver, we computed the survivable virtual topology routing against link and SRLG failures for small and medium sized networks efficiently. As even our improved ILP formulation becomes intractable for large networks, we present a congestion-based heuristic and a tabu search heuristic (which uses the congestion-based heuristic solution as the initial solution) for computing survivable routing of a virtual topology. Our experimental results show that tabu search heuristic coupled with the congestion based heuristic (used as initial solution) provides fast and near-optimal solutions.
-Lightpath scheduling is an important capability in next-generation wavelength-division multiplexing (WDM) optical networks to reserve resources in advance for a specified time period while provisioning end-to-end lightpaths. In a dynamic environment, the end user requests for dynamic scheduled lightpath demands (D-SLDs) need to be serviced without the knowledge of future requests. Even though the starting time of the request may be hours or days from the current time, the end-user however expects a quick response as to whether the request could be satisfied. We propose a twophase approach to dynamically schedule and provision D-SLDs. In the first phase, termed the deterministic lightpath scheduling phase, upon arrival of a lightpath request, the network control plane schedules a path with guaranteed resources so that the user can get a quick response with a deterministic lightpath schedule. In the second phase, termed the lightpath re-optimization phase, we re-provision some already scheduled lightpaths to re-optimize for improving network performance. We study two reoptimization scenarios to reallocate network resources while maintaining the existing lightpath schedules. Experimental results show that our proposed two-phase dynamic lightpath scheduling approach can greatly reduce network blocking.
VillageNet is a wireless mesh network that aims to provide low-cost broadband Internet access for rural regions. The cost of building the network is kept low by using off-the-shelf gateway IEEE 802.11 equipment and optimizing the network topology to directional nodes minimize cost. In this paper we describe the over-all operation links of VillageNet and discuss two fundamental problems in building such a network.Nodes in VillageNet communicate using long-distance pointto-point wireless links that are established using high-gain directional antenna. VillageNet uses the 2P MAC protocol [?], that is suited for the interference pattern within such a network. However, the 2P protocol requires the underlying mesh graph (for each 802.11 channel) to be bi-partite. Thus, if K channels villages (nodes) are available, then an important consideration is how to select K bi-partite subgraphs to activate, such that the demands of the nodes are best met. We formally pose this problem and present some initial results.Second, we observe that the dominant cost of constructing such a mesh network is the cost of constructing antenna towers A. Architecture at nodes. The cost of a tower depends on its height, which in turn A typical rural mesh network is depicted in Figure 1. It depends on the length of its links, and the physical obstructions along those links. Thus to minimize cost, we pose the problem of ould cn is toof c tof villages connected wilth each deciding which links should be established, such that all villages other through point-to-point wireless links. Some special nodes are connected and the cost of constructing antenna towers to in this mesh, called gateway nodes, will be connected to the establish the selected links is minimized. wired internet. Other mesh nodes will connect to the gateway node (and thus, to the rest of the internet) through one or more
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