Abstract
The recent decade has witnessed a tremendous growth of Internet traffic, which is expected to continue climbing for the foreseeable future. As a new paradigm, Spectrum-sliced Elastic Optical Path (SLICE) networks promise abundant (elastic) bandwidth to address the traffic explosion, while bearing other inherent advantages including enhanced signal quality and extended reachability. The fundamental problem in SLICE networks is to route each traffic demand along a lightpath with continuously and consecutively available sub-carriers, which is known as the Routing and Spectrum Allocation (RSA) problem. Given its NP-Hardness, the solutions to the RSA problem can be classified into two categories: optimal solutions using link-based, path-based, and channel-based Integer Linear Programming (ILP) models, which require extensive computational time; and sub-optimal heuristic and meta-heuristic algorithms, which have no guarantee on the solution quality. In this work, inspired by a channel-based ILP model, we propose a novel primal-dual framework to address the RSA problem, which can obtain a near-optimal solution with guaranteed per-instance closeness to the optimal solution.
Highlights
sliced Elastic Optical Path (SLICE) networks have other inherent advantages such as enhanced signal quality and extended reachability [2]. It remains a challenging but fundamental problem to efficiently allocate lightpaths in SLICE networks to accommodate traffic demands, which is known as the Routing and Spectrum Allocation (RSA) problem [4]
Inspired by a compact channel-based Integer Linear Programming (ILP) solution, we explore the relaxation and decomposition of the model based on the dual variables or Lagrange multipliers of complex coupling constraints, which leads to an upper bound (UB) of the problem
A SLICE network is modeled as a graph G (V, E, S): V consists of nodes of the network; E contains the set of directional fibers connecting nodes in V; and S is the group of subcarriers on each fiber
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. In SLICE networks, a traffic demand is accommodated with a group of consecutive sub-carriers, and neighboring sub-carriers can overlap partially in the spectrum domain [1,2,3]. SLICE networks have other inherent advantages such as enhanced signal quality and extended reachability [2] It remains a challenging but fundamental problem to efficiently allocate lightpaths in SLICE networks to accommodate traffic demands, which is known as the Routing and Spectrum Allocation (RSA) problem [4]. Inspired by a compact channel-based ILP solution, we explore the relaxation and decomposition of the model based on the dual variables or Lagrange multipliers of complex coupling constraints, which leads to an upper bound (UB) of the problem. We present the network model, problem definition and complexity, and a channel-based ILP model of the studied problem
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