A TRUST REGION ALGORITHM VIA BILEVEL LINEAR PROGRAMMING FOR SOLVING THE GENERAL MULTICOMMODITY MINIMAL COST FLOW PROBLEMS

This paper proposes a nonmonotonic backtracking trust region algorithm via bilevel linear programming for solving the general multicommodity minimal cost flow problems.Using the duality theory of the linear programming and convex theory,the generalized directional derivative of the general multicommodity minimal cost flow problems is derived.The global convergence and superlinear convergence rate of the proposed algorithm are established under some mild conditions.

Multicommodity Flow Modeling for the Data Transmission Scheduling Problem in Navigation Satellite Systems

Introducing InterSatellite Links(ISLs)is a major trend in new-generation Global Navigation Satellite Systems(GNSSs).Data transmission scheduling is a crucial problem in the study of ISL management.The existing research on intersatellite data transmission has not considered the capacities of ISL bandwidth.Thus,the current study is the first to describe the intersatellite data transmission scheduling problem with capacity restrictions in GNSSs.A model conversion strategy is designed to model the aforementioned problem as a length-bounded single-path multicommodity flow problem.An integer programming model is constructed to minimize the maximal sum of flows on each intersatellite edge;this minimization is equivalent to minimizing the maximal occupied ISL bandwidth.An iterated tree search algorithm is proposed to resolve the problem,and two ranking rules are designed to guide the search.Experiments based on the BeiDou satellite constellation are designed,and results demonstrate the effectiveness of the proposed model and algorithm.

Topology Abstraction Service for IP VPNs: Core Network Partitioning for Resource Sharing

VPN service providers (VSP) and IP-VPN customers have traditionally maintained service demarcation boundaries between their routing and signaling entities. This has resulted in the VPNs viewing the VSP network as an opaque entity and therefore limiting any meaningful interaction between the VSP and the VPNs. A key challenge is to expose each VPN to information about available network resources through an abstraction (TA) [1] which is both accurate and fair. In [2] we proposed three decentralized schemes assuming that all the border nodes performing the abstraction have access to the entire core network topology. This assumption likely leads to over- or under-subscription. In this paper we develop centralized schemes to partition the core network capacities, and assign each partition to a specific VPN for applying the decentralized abstraction schemes presented in [2]. First, we present two schemes based on the maximum concurrent flow and the maximum multicommodity flow (MMCF) formulations. We then propose approaches to address the fairness concerns that arise when MMCF formulation is used. We present results based on extensive simulations on several topologies, and provide a comparative evaluation of the different schemes in terms of abstraction efficiency, fairness to VPNs and call performance characteristics achieved.