Optimal joint path computation and rate allocation for real-time traffic

Computing network paths under worst-case delay constraints has been the subject of abundant literature in the past two decades. Assuming Weighted Fair Queueing scheduling at the nodes, this translates to computing paths and reserving rates at each link. The problem is NP-hard in general, even for a single path; hence polynomial-time heuristics have been proposed in the past, that either assume equal rates at each node, or compute the path heuristically and then allocate the rates optimally on the given path. In this paper we show that the above heuristics, albeit finding optimal solutions quite often, can lead to failing of paths at very low loads, and that this could be avoided by solving the problem, i.e., path computation and rate allocation, jointly at optimality. This is possible by modeling the problem as a mixed-integer second-order cone program and solving it optimally in split-second times for relatively large networks on commodity hardware; this approach can also be easily turned into a heuristic one, trading a negligible increase in blocking probability for one order of magnitude of computation time. Extensive simulations show that these methods are feasible in today's ISPs networks and they significantly outperform the existing schemes in terms of blocking probability

Delay-aware Link Scheduling and Routing in Wireless Mesh Networks

Resource allocation is a critical task in computer networks because of their capital-intensive nature. In this thesis we apply operations research tools and technologies to model, solve and analyze resource allocation problems in computer networks with real-time traffic. We first study Wireless Mesh Networks, addressing the problem of link scheduling with end-to-end delay constraints. Exploiting results obtained with the Network Calculus framework, we formulate the problem as an integer non-linear optimization problem. We show that the feasibility of a link schedule does depend on the aggregation framework. We also address the problem of jointly solving the routing and link scheduling problem optimally, taking into account end-to-end delay guarantees. We provide guidelines and heuristics. As a second contribution, we propose a time division approach in CSMA MAC protocols in the context of 802.11 WLANs. By grouping wireless clients and scheduling time slots to these groups, not only the delay of packet transmission can be decreased, but also the goodput of multiple WLANs can be largely increased. Finally, we address a resource allocation problem in wired networks for guaranteed-delay traffic engineering. We formulate and solve the problem under different latency models. Global optimization let feasible schedules to be computed with instances where local resource allocation schemes would fail. We show that this is the case even with a case-study network, and at surprisingly low average loads

Optimal and Heuristic Algorithms for Quality-of-Service Routing with Multiple Constraints

The multi-constrained path (MCP) selection problem occurs when the quality-of-services (QoS) are supported for point-topoint connections in the distributed multimedia applications deployed on the Internet. This NP-complete problem is concerned about how to determine a feasible path between two given end-points, so that a set of QoS path constraints can be satisfied simultaneously. Based on the branch-and-bound technique and tabu-searching strategy, an optimal algorithm and a tabu-search based heuristic are developed in this paper for solving the MCP problem with multiple constraints. The experimental results show that our tabu-search based heuristic not only outperforms the previous method published in literature, but also demonstrates that it is indeed a highly efficient method for solving the MCP problem in large-scale networks