Abstract
The flexible nature of elastic optical networks (EONs) effectively uses spectral resources for optical communication by allocating the minimum required bandwidth to network connections. Since the energy consumption of such networks scales with the magnitude of bandwidth demand, addressing the issue of energy wastage is important. This fact has a profound impact on the design of efficient schemes for energy aware optical networks, and adaptivity arises as one of the most important properties of these networks. Learning Automata are Artificial Intelligence tools that have been used in networking algorithms, when adaptivity to the characteristics of the network environment can result in significantly improved network performance. In this work, a new adaptive power-aware algorithm is introduced, which selectively switches off bandwidth-variable optical transponders (BVTs) under low utilization conditions, to achieve energy efficiency. A novel adaptive scheme, which makes use of Learning Automata to significantly reduce the total energy consumption, while at the same time avoiding the onset of congestion, is proposed. The proposed scheme monitors network congestion, in terms of Bandwidth Blocking Probability (BBP), and the learning mechanism finds the optimal amount of energy-saving so that congestion is avoided, while at the same time significant energy savings are achieved. The proposed Learning Energy-Saving Algorithm (LESA) is evaluated via extensive simulation results, which indicate that it achieves an energy saving of up to 50%, compared to other energy efficient solutions.
Highlights
The need for bandwidth is growing more than ever before as technology evolves [1] and high bandwidth-dependent applications have increased at unprecedented level
The elastic optical networks (EONs) implementation imposes to the Routing and Spectrum Assignment (RSA) problem two constraints: (1) the spectrum continuity constraint, that is the allocation of a connection, must follow the same spectral resources on each link along the route and (2) the spectrum contiguity constraint, that is the allocation of a connection must be on contiguous frequency slots (FS) on each link along the route
POWER CONSUMPTION ANALYSIS Three main components which can influence the amount of power consumption on an IP Over EON are considered in this study, namely IP router ports, S-bandwidth-variable optical transponders (BVTs) and erbium doped fiber amplifiers (EDFAs)
Summary
The need for bandwidth is growing more than ever before as technology evolves [1] and high bandwidth-dependent applications have increased at unprecedented level. A new adaptive power-aware algorithm is implemented, which selectively turns off BVTs, along with the corresponding IP router ports, to achieve energy efficiency under low utilisation conditions, during the network operation. RELATED WORK A multitude of published papers have considered energy efficiency in the design of IP Over WDM optical networks [13]–[16]. In [21], energy efficient traffic grooming in IP-over-elastic optical networks taking into account sliceable optical transponders is studied. Energy-aware heuristic algorithms are proposed for resource allocation both in static and dynamic scenarios with time-varying demands for the Elastic-bandwidth OFDM-based network and WDM. Should there exist any available slices to source and destination nodes, node A and node D respectively, lightpath λ2 can be optically groomed with pre established lightpaths λ1 and λ3
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