A Lagrangean relaxation based near-optimal algorithm for advance lightpath reservation in WDM networks

Abstract

Advance lightpath reservation is a new research topic for connecting high-speed computer servers in lambda grid applications and for dynamic lightpath provisioning in the future optical internet. In such networks, users make call requests in advance to reserve network resources for communications. The challenge of the problem comes from how to jointly determine call admission control, lightpath routing, and wavelength assignment. In this paper, we propose an efficient Lagrangean relaxation (LGR) approach to resolve advance lightpath reservation for multi-wavelength optical networks. The task is first formulated as a combinatorial optimization problem in which the revenue from accepting call requests is to be maximized. The LGR approach performs constraint relaxation and derives an upper-bound solution index according to a set of Lagrangean multipliers generated through subgradient-based iterations. In parallel, using the generated Lagrangean multipliers, the LGR approach employs a new heuristic algorithm to arrive at a near-optimal solution. By upper bounds, we assess the performance of LGR with respect to solution accuracy. We further draw comparisons between LGR and three heuristic algorithms-Greedy, First Come First Serve, and Deadline First, via experiments over the widely-used NSFNET network. Numerical results demonstrate that LGR outperforms the other three heuristic approaches in gaining more revenue by receiving more call requests.

Bee colony approach for advance resource reservation in optical based grids

“…The considered ARR problem can be formulated as follows: for a given optical network topology, each demand data (source node s , destination node d , starting time t s and ending time t e ) and given number of available wavelengths W , determine the route‐wavelength pair for each lightpath request such that the total number of established lightpaths is maximized. We used the ILP (integer linear program) mathematical formulation given in to solve the ARR problem in the case of small to medium problem instances. Usually the optimal solution of an ILP problem cannot be found in a reasonable amount of time when the data set is very large.…”

Revenue-driven Lightpaths Provisioning over Optical WDM Networks Using Bee Colony Optimization

“…By knowing the complete set of demands, a more efficient network resource usage (and consequently more revenues) could be achieved compared to on-line (dynamic) traffic case in which future demands are not known a priori. So far, various approaches to solve the revenue (profit) maximization problem in optical WDM networks have been proposed in literature [2][3][4][5][6] . In Ref.…”

“…The authors of Ref. 3 proposed an efficient near-optimal algorithm based on Lagrangean relaxation (LGR) approach to solve the lightpath provisioning problem in which the revenue from accepting call requests is to be maximized. In Ref.…”

Lightpath Scheduling and Routing for Traffic Adaptation

“…Existing methods for the lightpath scheduling, Routing and Wavelength Assignment (RWA) problems assume that a lightpath should be set up either at a given time, or within a given time window, which makes the lightpath scheduling inflexible for traffic adaptation. For example, in [3,4,5,6,7], network planning was conducted for a set of lightpath requests, each having pre-specified starting and ending time. In [8,9,10,11], static network planning was conducted for lightpath requests with fixed holding-time, each one being allowed to slide within its given time window.…”