José Ramón Piney

In recent years, there has been an increasing trend towards extending the coverage of passive optical networks (PONs) over large geographical areas. Long-reach PONs (LRPONs) are capable of extending the distance covered by PONs from 20 km to 100 km, leading to cost savings in the network operation by reducing the number of central offices. They have become widely deployed due to their ability to provide high-speed, long-distance data transmission over optical fibers. In addition, the next generation of optical access networks are expected to provide high-capacity mobile and wireless backhauling over a wide coverage area. However, this extended reach also requires the design of efficient dynamic bandwidth allocation (DBA) schemes to address the performance degradation caused by the increased propagation delay in LRPONs. The DBA schemes commonly used for upstream traffic transmission in traditional PONs are not well-suited for use in LRPONs due to their inefficiency in bandwidth utilization due to the increased round-trip time (RTT) between the optical line terminal (OLT) and the optical network unit (ONU). In this study, we present an efficient DBA algorithm, the Distance-Weighted Bandwidth Allocation DWDBA Algorithm, specifically enhanced for multi-wavelength LRPONs. Our DBA algorithm utilizes a scheduling policy that assigns weight vectors to Optical Network Units (ONUs) based on their distance from the Optical Line Terminal (OLT), sorting them accordingly without penalizing any ONU due to their distance. The DWDBA takes the laser tuning time into consideration. We conducted extensive simulations to evaluate the performance of the proposed algorithm under various scenarios and compared it to the IPACT algorithm. The results of the simulations show that the proposed algorithm outperformed the IPACT algorithm in terms of bandwidth utilization and queue delay.

The deployment of new 5G services and future demands for 6G make it necessary to increase the performance of access networks. This challenge has prompted the development of new standardization proposals for Passive Optical access Networks (PONs) that offer greater bandwidth, greater reach and a higher rate of aggregation of users per fiber, being Time- and Wavelength-Division Multiplexing (TWDM) a promising technological solution for increasing the capacity by up to 40 Gbps by using several wavelengths. This solution introduces tunable transceivers into the Optical Network Units (ONUs) for switching from one wavelength to the other, thus addressing the ever-increasing bandwidth demands in residential broadband and mobile fronthaul networks based on Fiber to the Home (FTTH) technology. This adds complexity and sources of inefficiency, such as the laser tuning time (LTT) delay, which is often ignored when evaluating the performance of Dynamic Bandwidth Allocation (DBA) mechanisms. We present a novel DBA algorithm that dynamically handles the allocation of bandwidth and switches the ONUs’ lasers from one wavelength to the other while taking LTT into consideration. To optimize the packet delay, we introduce a scheduling mechanism that follows the Longest Processing Time first (LPT) scheduling discipline, which is implemented over the Interleaved Polling with Adaptive Cycle Time (IPACT) DBA. We also provide quality of service (QoS) differentiation by introducing the Max-Min Weighted Fair Share Queuing principle (WFQ) into the algorithm. The performance of our algorithm is evaluated through simulations against the original IPACT algorithm, which we have extended to support multi-wavelengths. With the introduction of LPT, we obtain an improved performance of up to 73% reduction in queue delay over IPACT while achieving QoS differentiation with WFQ.

Future networks starting from 5G will depend on network slicing to meet a wide range of network services (NSs) with various quality of service (QoS) requirements. With the powerful Network Function Virtualization (NFV) technology available, network slices can be rapidly deployed and centrally managed, giving rise to simplified management, high resource utilization, and cost-efficiency. This is achieved by realizing NSs on general-purpose hardware, hence, replacing traditional middleboxes. However, realizing fast deployment of end-to-end network slices still requires intelligent resource allocation algorithms to efficiently use the network resources and ensure QoS among different slice categories during congestion cases. This is especially important at the links of the network because of the scarcity of their resources. Consequently, this paper proposes a paradigm based on NFV architecture aimed at providing the massive computational capacity required in the NSs and supporting the resource allocation strategy proposed for multiple slice networks based on resources utilization optimization using a proposed and analyzed Squatting-Kicking model (SKM). SKM is a suitable algorithm for dynamically allocating network resources to different priority slices along paths and improving resource utilization under congested scenarios. Simulation results show that the proposed service deployment algorithm achieves 100% in terms of both overall resource utilization and admission for higher priority slices in some scenarios in bandwidth-constrained contexts, which cannot be achieved by other existing schemes due to priority constraints.