Dynamic realization of miscellaneous profile services in elastic optical networks using spectrum partitioning

TL;DR

This work addresses dynamic provisioning of miscellaneous profile services in elastic optical networks by combining probabilistic spectrum partitioning with profile-based routing and two multistage spectrum assignment strategies. The proposed framework uses partition-specific contribution probabilities and two SPR methods—Decision Points Method (DPM) and Average Tracking Method (ATM)—to realize requests with minimum, average, and maximum bandwidth constraints over their holding times, while employing Least Loaded Routing or Profile-Based Routing for path selection. Simulation on a realistic backbone topology demonstrates substantial reductions in blocking probability and improved spectrum utilization, with ATM outperforming DPM due to more flexible resource reallocation that tracks the target average. The approach enables inherent sharing among partitions and offers a practical path toward dynamic, profile-driven optical services, albeit with higher computational complexity. All mathematical notation is presented within $...$ delimiters.

Abstract

Optical backbone networks are required to be highly dynamic in supporting requests with flexible bandwidth granularities to cope with the demands of new broadband wireless and fixed access networks. To provide this flexibility, services are offered by taking requested bandwidth profile into consideration, instead of assigning a fixed amount of bandwidth to each request. New techniques are developed for the resource management of the elastic optical networks to realize services with a specified bandwidth profile, consisting of minimum, average, and maximum required number of spectrum slots, in addition to holding time. In this work, two new schemes are proposed to realize such services, exploiting a probabilistic spectrum partitioning approach. This new probabilistic spectrum partitioning scheme is devised to enhance the chance of accommodating requests and consequently lower request blocking probability. It enforces different probabilities to contributing spectrum partitions in a certain service realization. Taking advantage of this probabilistic spectrum partitioning and a profile-based routing, we introduce two multistage spectrum assignment methods to make a certain lightpath meet the requested service profile constraints, considering the time-weighted average of the assigned spectrum slots. The results indicate that our algorithms can successfully realize the requests with the probability of 0.993 for the offered loads less than 400 erlang.

Figures (13)

• Figure 1: The exploited flexible node structure using BVT, flexible add/drop and flexible optical switch technologies.
• Figure 2: The five connection requests, $S_1 (A \rightarrow B)$, $S_2 (A \rightarrow B)$, $S_3 (A \rightarrow D)$, $S_4 (B \rightarrow D)$, and $S_5(C \rightarrow D)$, are determined by north-west red lines, blue dots, green crosshatches, black north-east lines, and purple horizontal lines, respectively. A new connection request, $S_6=\{2,3,4,90\}$, arrives at node C and gets blocked since the two left free slots on $C\rightarrow D$ do not fulfill the contiguity constraint.
• Figure 3: The whole spectrum is divided into three partitions, utilizing the SIP scheme. The first partition has two bins, each composed of two slots; the second and the third partitions have one bin, consisting of three and four slots, respectively. The blocked connection request in Fig. \ref{['fig: not utilizing SP']}, $S_6$, determined by the yellow color, is accommodated with two spectrum slots.
• Figure 4: If a request belongs to $b_{AS}\textless b_{Ave}$ group and $t\leq DP_M$, every $t_0$ second the partitions, which can be used in realizing the requested average are investigated, e.g., the partitions on the blue line are examined before $DP_{Ave+2}$.
• Figure 5: The flow chart of the SIP-PBR-ATM algorithm.