Efficiently solving the Routing and Spectrum Allocation (RSA) problem in optical communication networks is crucial for maximizing resource utilization, improving quality of service, and reducing operational costs. By allocating spectrum and routing optimally, these networks can handle increasing traffic demands, support emerging technologies, and ensure reliable and high-speed communication services for users. Effective solutions to the RSA problem enable optical networks to scale efficiently, minimize congestion, and support the continued growth of digital communication infrastructure.
The objective is to maximize the utilization of optical resources across the network. Let $c(e)$ denote the capacity of a link $e$. When we represent the occupied slots at time $t$ on a link $e$ as $o(e)$, the utilization $u_t$ of the link $e$ at time $t$ can be computed by: $$u_t(e) := \dfrac{o_t(e)}{c(e)}.$$
Therefore, the average utilization $U(e)$ of a link $e$ over $T$ episodes (equivalent to $T$ arrivals of requests) is $$U(e) := \dfrac{1}{T}\sum_{t = 0}^{T-1}\dfrac{ot(e)}{c(e)}.$$ The formal objective is to achieve maximum network-wide utilization. We define the network-wide utilization $U$ as the average of the edge total utility: $$\text{Maximize } U := \dfrac{1}{|E|}\sum{e\in E}U(e)$$
nsfnet.gml
is the optical network topologySan Diego Supercomputer Center
to Jon Von Neumann Center, Princeton, NJ
)np.random.randint(min_ht, max_ht)
min_ht = 10
and max_ht = 20
-1
if the request is blockedht
value for the request if it is accomodatedGiven that a holding time for any request can range from 10
to 19
and that there are 100
rounds, the expected return from an episode should be 1,450
if no blocking is experienced. We see in Case II that DQN converges to this value. Our routing algorithm performs similarly to the simple shortest path algorithm because there is not an overload of requests with the same source and destination pair as seen in Case I.
In Case I, however, our algorithm significantly outperforms the shortest path approach. Obviously, when the number of edges and, subsequently, links are constrained in the network, our algorithm would be a smarter choice to use.
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