Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
p-Cycle Network Design with Hop Limits and Circumference Limits
BROADNETS '04 Proceedings of the First International Conference on Broadband Networks
Mesh-based Survivable Transport Networks: Options and Strategies for Optical, MPLS, SONET and ATM Networking
IEEE Communications Magazine
IP layer restoration and network planning based on virtual protection cycles
IEEE Journal on Selected Areas in Communications
Extending the p-cycle concept to path segment protection for span and node failure recovery
IEEE Journal on Selected Areas in Communications
Hamiltonian p-cycles for fiber-level protection in semi-homogeneous homogeneous and optical networks
IEEE Network: The Magazine of Global Internetworking
Preconfigured structures for survivable WDM networks
ICAIT '08 Proceedings of the 2008 International Conference on Advanced Infocomm Technology
ILP formulations for non-simple p-cycle and p-trail design in WDM mesh networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Energy saving and cost reduction in multi-granularity green optical networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Preplanned restoration of multicast demands in optical networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
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The concept of p-cycle (preconfigured protection cycle) allows fast and efficient span protection in wavelength division multiplexing (WDM) mesh networks. To design p-cycles for a given network, conventional algorithms need to enumerate cycles in the network to form a candidate set, and then use an integer linear program (ILP) to find a set of p-cycles from the candidate set. Because the size of the candidate set increases exponentially with the network size, candidate cycle enumeration introduces a huge number of ILP variables and slows down the optimization process. In this paper, we focus on p-cycle design without candidate cycle enumeration. Three ILPs for solving the problem of spare capacity placement (SCP) are first formulated. They are based on recursion, flow conservation, and cycle exclusion, respectively. We show that the number of ILP variables/constraints in our cycle exclusion approach only increases linearly with the network size. Then, based on cycle exclusion, we formulate an ILP for solving the joint capacity placement (JCP) problem. Numerical results show that our ILPs are very efficient in generating p-cycle solutions.