Survivable Networks: Algorithms for Diverse Routing provides algorithms for diverse routing to enhance the survivability of a network. It considers the common mesh-type network and describes in detail the construction of physically disjoint paths algorithms for diverse routing. The algorithms are developed in a systematic manner, starting with shortest path algorithms appropriate for disjoint paths construction. Key features of the algorithms are optimality and simplicity. Although the algorithms have been developed for survivability of communication networks, they are in a generic form, and thus applicable in other scientific and technical disciplines to problems that can be modeled as a network. A notable highlight of this book is the consideration of real-life telecommunication networks in detail. Such networks are described not only by nodes and links, but also by the actual physical elements, called span nodes and spans. The sharing of spans (the actual physical links) by the network (logical) links complicates the network, requiring new algorithms. This book is the first one to provide algorithms for such networks. Survivable Networks: Algorithms for Diverse Routing is a comprehensive work on physically disjoint paths algorithms. It is an invaluable resource and reference for practicing network designers and planners, researchers, professionals, instructors, students, and others working in computer networking, telecommunications, and related fields.

Keep your network safe from security disasters with a dependable recovery strategy Companies are finally learning that a network disaster recovery plan is mandatory in these times, and they must be prepared to make difficult choices about network security. In the information-packed pages of this book, Annlee Hines shares her unique and diverse work experience. She explains that the first thing you need, whatever your business may be, is reliable information and an idea of what you need to protect, as well as what you are protecting it from. She then dives into a discussion of how much you can expect to spend depending on what kind of security your network requires. She also delves into addressing the variables that determine why your needs will not necessarily be the needs of your closest competitor. Most importantly, Hines writes this valuable material realizing that you already know how to do your job --it's just that you now have to reconsider just how vulnerable the information nervous system of your company really is. From major terrorist attacks to natural disasters to hackers, Annlee Hines explores how to defend your network and reviews such topics as: * Probes, viruses, worms, and Trojan horses * The most common vulnerabilities networks face * Understanding and justifying costs * Lessons to be learned from successful defense strategies * Preparing for the worst and the requirements of network survival * Remedies, cyber recovery, and restoration

The problem of designing a cost-efficient network that survives the failure of one or more nodes or edges of the network is critical to modern telecommunications engineering. The method developed in this book is designed to solve such problems to optimality. In particular, a cutting plane approach is described, based on polyhedral combinatorics, that is ableto solve real-world problems of this type in short computation time. These results are of interest for practitioners in the area of communication network design. The book is addressed especially to the combinatorial optimization community, but also to those who want to learn polyhedral methods. In addition, interesting new research problemsare formulated.

These days, the nature of services and the volume of demand in the telecommu nication industry is changing radically, with the replacement of analog transmis sion and traditional copper cables by digital technology and fiber optic transmis sion equipment. Moreover, we see an increasing competition among providers of telecommunication services, and the development of a broad range of new services for users, combining voice, data, graphics and video. Telecommunication network planning has thus become an important problem area for developing and applying optimization models. Telephone companies have initiated extensive modeling and planning efforts to expand and upgrade their transmission facilities, which are, for most national telecommunication networks, divided in three main levels (see Balakrishnan et al. [5]), namely, l. the long-distance or backbone network that typically connects city pairs through gateway nodes; 2. the inter-office or switching center network within each city, that interconnects switching centers in different subdivisions (clusters of customers) and provides access to the gateway(s) node(s); 1 2 DESIGN OF SURVNABLE NETWORKS WITH BOUNDED RINGS 3. the local access network that connects individual subscribers belonging to a cluster to the corresponding switching center. These three levels differ in several ways including their design criteria. Ideally, the design of a telecommunication network should simultaneously account for these three levels. However, to simplify the planning task, the overall planning problem is decomposed by considering each level separately.

In this dissertation, a new spare capacity planning methodology is proposed utilizing path restoration. The approach is based on forcing working flows/traffic which are on paths that are disjoint to share spare backup capacity. The algorithm for determining the spare capacity assignment is based on genetic algorithms and is capable of incorporating non-linear variables such as non-linear cost function and QoS variables into the objective and constraints. The proposed methodology applies to a wider range of fault scenarios than most of the current literature. It can tolerate link-failures, node-failures, and link-and-node failures. It consists of two stages: the first stage generates a set of network topologies that maximize the sharing between backup paths by forcing them to use a subset of the original network. The second stage utilizes a genetic algorithm to optimize the set of solutions generated by the first stage to achieve an even better final solution. It can optimize the solution based on either minimizing spare capacity or minimizing the total network cost. In addition, it can incorporate QoS variables in both the objective and constraints to design a survivable network that satisfies QoS constraints. Numerical results comparing the proposed methodology to Integer Programming techniques and heuristics from the literature are presented showing the advantages of the technique. The proposed methodology was applied on 4 different size networks based on spare capacity optimization criteria and it was found that it achieved solutions that were on average 9.3% better than the optimal solution of the IP design that is based on link-restoration. It also achieved solutions that were on average 22.2 % better than the previous heuristic SLPA. The proposed methodology is very scalable. It was applied on networks with different sizes ranging from a 13-node network to a 70-node network. It was able to solve the 70-node network in less than one hour on a Pentium II PC. The curve-fitting of the empirical execution time of the methodology was found to be O(n3).

Covers these key topics: Shared-mesh protection for optical WDM networks. Survivable traffic grooming for hierarchical optical WDM networks. Survivable data over next-generation SONET/SDH with inverse multiplexing.

The advent of fiber optic transmission systems and wavelength division multiplexing (WDM) have led to a dramatic increase in the usable bandwidth of single fiber systems. This book provides detailed coverage of survivability (dealing with the risk of losing large volumes of traffic data due to a failure of a node or a single fiber span) and traffic grooming (managing the increased complexity of smaller user requests over high capacity data pipes), both of which are key issues in modern optical networks. A framework is developed to deal with these problems in wide-area networks, where the topology used to service various high-bandwidth (but still small in relation to the capacity of the fiber) systems evolves toward making use of a general mesh. Effective solutions, exploiting complex optimization techniques, and heuristic methods are presented to keep network problems tractable. Newer networking technologies and efficient design methodologies are also described.