Time-sharing of Quantum Key Distribution (QKD) transceivers with the help of optical switches and a central Software-Defined Networking (SDN) controller is a promising technique to better amortize the large investments required to build a Quantum Key Distribution Network (QKDN). In this work, we investigate the implications of introducing Time-Division Multiplexing (TDM) in trusted-relay QKDNs at the wide-area network scale in terms of performance and cost-saving. To this end, we developed both a Mixed Integer Linear Programming (qTDM-MILP) model and a Heuristic Algorithm (qTDM-HA) to solve the allocation of QKD transceivers and network resources for a novel switched QKDN operating scheme: qTDM-QKDN. Our heuristic method provides a close-to-optimal resource planning for the offline problem that computes the minimum number of QKD transceivers and optical switch ports at each node, as well as the number of quantum channels on each link required to satisfy a target set of end-to-end secret-keyrate demands. Moreover, both the model and the heuristic provide the time fractions that each QKD transceiver needs to peer with each neighbor QKD transceiver. We compared our proposed model and heuristic algorithm for cost minimization with non-time sharing QKD transceivers (nTDM) as baseline. The results show that qTDM can achieve substantial cost-savings in the range of 10%–40% compared to nTDM. Furthermore, this work sheds light on the selection of the value for the working cycle T and its influence on network performance. • TDM optimizes QKD networks, enhancing efficiency and cost-effectiveness. • A MILP model and the qTDM-HA ease resource allocation in large-scale QKD networks. • The tools provide outstanding solutions from 10% to 40% in terms of cost-savings. • TDM minimizes the number of dedicated QKD transceivers by using shared ones wisely.

The extension of elastic optical network (EON) technologies to multi-band transmission (MB-EON) promises enhanced spectral efficiency, greater throughput, and long-term cost benefits for telecom operators. However, designing such networks presents challenges, particularly in optimizing physical parameters like optical power and quality of transmission (QoT) across different frequency bands. This paper introduces a methodology for optimal span-by-span power allocation using two hyper-accelerated power optimization (HPO) modes: flat launch power (FLP) and flat received power (FRP). This methodology significantly accelerate network power optimization while ensuring service stability in scenarios such as changes in network parameters, QoT degradation due to aging, and network re-optimization or upgrading. Through a comprehensive comparison, we find that FRP notably improves signal flatness and GSNR/OSNR, particularly in the S-band, contributing to a network-wide throughput increase in the order of 12% to 75%. Additionally, we demonstrate that HPO applied to global power optimization is simpler and more cost-effective than when applied to local methods for large-scale networks.

Monitoring and analysis of network traffic with proper accuracy and efficiency are paramount in computer networks management and security. An example of function required for this type of applications is per-flow packet accounting. Having an efficient data structure that provides such functionality while maintaining good performance can become challenging. In this paper, we propose an integrated data structure that combines the ability of the xor filter to detect packets from selected flows and the Count-Min sketch (CMS) to efficiently estimate the frequencies. The results show that the integrated filter improves performance compared to keeping both structures separate, achieving a reduction of up to 23% in the probability of false positives, fewer memory access per operation, and a reduction of the Average Relative Error in the CMS as more packets are analyzed.

As probabilistic data structures are widely adopted in computing systems, their privacy is a major issue. Recent works have shown that even though the values stored in these structures look random, information can be extracted from them in some settings. In this paper, we consider the privacy of adaptive cuckoo filters, a probabilistic data structure that implements approximate membership checking. The main novelty and benefit of these filters are that they can adapt to removing false-positives. Unfortunately, our analysis shows that adaptation can dramatically reduce the privacy of the filters, allowing an attacker to extract the set of elements stored in the filter. Indeed, in some settings, the attacker can identify 100% of the elements stored in the filter. This means that the protection of the privacy of adaptive cuckoo filters should be considered. To that end, we propose preprocessing reduction (PR), a scheme that prevents an attacker from extracting the set of elements stored in the filter at the cost of increasing the false-positive probability of the filter. In many settings, the impact on false-positives will be negligible. For example, in a case study with 32-bit universes, the increase in the false-positive probability was smaller than 8% in all the configurations tested. Interestingly, PR is applicable not only to adaptive filters but also to approximate membership check filters in general and thus can be used to protect, for example, Bloom filters.

Approximate membership check filters are widely used in networking applications to resolve membership queries at high speed with a low memory cost. Due to their extensive use, many filter types have been proposed. Two recent and interesting alternatives are the xor filter and the binary fuse filter, which in certain configurations have one of the lowest false positive rates, are faster and use less memory than other filters. However, one of the main drawbacks of xor and binary fuse filters is that it is not possible to add keys once the filter has been built. This limits their use in many network related applications where keys have to be added dynamically. This paper presents the Integrated xor-Bloom filter (IXOR) and the Integrated binary fuse-Bloom filter (IBIF), both schemes allow dynamic insertions in xor and binary fuse filters without the need to reconstruct the filters. The schemes have been implemented and evaluated showing that a large number of dynamic insertions can be supported with a limited memory overhead and a small impact on the false positive probability and lookup speed. Therefore, the proposed filters can bring the benefits of xor and binary fuse filters to networking applications that need to support dynamic insertions.

In this paper, we have generated and examined three different datasets based on the symbol rate and traffic load of the link states to estimate the quality of transmission (QoT) in terms of Generalized Signal to the Noise Ratio (GSNR) for an optical span. The results reveal that in datasets generated for different symbol rates and traffic loads, the outlier data degrades the accuracy in estimating the GSNR. The results show that nearly 99% of the mismatchings had less than 0.3 dB of error for a synthesised dataset in which the symbol rate and traffic load considered fixed.

This paper proposes a shared precomputed restoration (SPR) mechanism for link failures in translucent elastic optical networks (EONs). We present SPR with a heuristic algorithm that aims to minimize a cost function. The cost function depends on the number of transceivers and frequency slots (FSs) used to establish a working/protection lightpath (LP) with a tunable parameter that determines the weight of the number of transceivers and FSs in the cost function. SPR precalculates a protection LP for all links of each working LP. As a result, non-link-disjoint working LPs can share protection spectrum and transceivers on newly eased conditions. Like shared backup path protection (SBPP) and dedicated protection (1+1), SPR guarantees single link failure recovery. Our simulation results reveal that SPR outperforms SBPP in terms of recovered bandwidth in multiple link failures. Furthermore, SPR uses fewer transceivers compared to SBPP and 1+1 protection.

Bloom filters are widely used to perform fast approximate membership checking in networking applications. The main limitation of Bloom filters is that they suffer from false positives that can only be reduced by using more memory. We suggest to take advantage of a common repetition in the identity of queried elements to adapt Bloom filters for avoiding false positives for elements that repeat upon queries. In this paper, one memory access Bloom filters are used to design an adaptation scheme that can effectively remove false positives while completing all queries in a single memory access. The proposed filters are well suited for scenarios on which the number of memory bits per element is low and thus complement existing adaptive cuckoo filters that are not efficient in that case. The evaluation results using packet traces show that the proposed adaptive Bloom filters can significantly reduce the false positive rate in networking applications with the single memory access. In particular, when using as few as four bits per element, false positive rates below 5% are achieved.

Bloom filters are used to perform approximate membership checking in a wide range of applications in both computing and networking, but the recently introduced cuckoo filter is also gaining popularity. Therefore, it is of interest to compare both filters and provide insights into their features so that designers can make an informed decision when implementing approximate membership checking in a given application. This article first compares Bloom and cuckoo filters focusing on a packet classification application. The analysis identifies a shortcoming of cuckoo filters in terms of false positive rate when they do not operate close to full occupancy. Based on that observation, this article also proposes the use of a configurable bucket to improve the scaling of the false positive rate of the cuckoo filter with occupancy.

Multicast forwarding in the context of IP-MPLS networks for services like VPLS has important scalability issues. Alternatives to per-VPLS tree construction based on aggregation of multipoint requests onto shared trees have been studied. Other works have focused on stateless forwarding based on Bloom filters. Both suffer from some type of forwarding anomalies. This paper proposes the combination of both forwarding modes: shared multicast trees and an efficient variant of stateless switching based on Bloom filters. Simulations prove that constraining the forwarding to the shared tree is an effective mechanism to prevent most side effects of Bloom filter-based forwarding, making the combined technique a good trade-off in terms of forwarding state consumption, yielding best performance in terms of overhead with respect to each technique in isolation.

The demand for multicast-capable VPN services, like Virtual Private LAN Service (VPLS), has grown quickly in the last years. In order to save bandwidth, MPLS point-to-multipoint LSPs could be used, but the VPN-specific state information to be handled inside the network may exceed the capacity of core nodes. A well-known solution for this is to aggregate the multicast/broadcast traffic of multiple VPNs into shared p2mp LSP trees. In shared trees, although some bandwidth is wasted because a fraction of the packets are delivered to non-member leaves (either not in the VPN broadcast or multicast group), there is wide working range where a good state vs. bandwidth trade-off is achieved. In this paper we enhance and improve previous works that analyze this trade-off. We propose new techniques for multicast traffic aggregation of VPNs in MPLS-based networks, with the objective of observing the behavior of the aggregation philosophy for different aggregation degrees, which should be very useful for network design and deployment purposes. We assess the aggregation heuristics over different reference networks and VPN geographic distributions. Simulations give a quantitative indication of the relevance of intelligent aggregation, of geographical distribution and group sizes.

Optical Code Division Multiple Access (OCDMA) techniques have shown outstanding capabilities in the sharing of optical media, in particular in access networks. However, OCDMA systems may suffer from Multiple Access Interference (MAI) and other kinds of noise when many users access the shared media simultaneously, increasing the BER (Bit Error Rate) to unacceptable levels, that is, a situation at which all combined signals interfere and are lost. This work proposes a mixed OCDMA and Tunable Transmitter-Fixed Receiver (TT-FR) WDM and ring architecture at which the ring is split into small-size segments to limit the probability of MAI. Essentially, every segment in the ring has got two hub nodes (on the segment's head and tail) which forwards inter-segment traffic to other hub nodes on dedicated home wavelengths, thus making use of WDM. The access media inside the segment is shared between the nodes by means of OCDMA, and code reuse is possible on different segments. Our performance analysis shows how to split a given ring into segments in order to minimise the BER due to multiple users accessing the network and allow for high bit-rates for a given traffic load. In addition, we analyse the possibility of introducing Forward Error Correction (FEC) at a moderate overhead cost to improve performance.

We present a novel cost-effective multicast capable optical cross connect (MC-OXC) node architecture which improves efficiency of optical power by constraining splitting to only two output ports, in order to reduce power losses derived from splitting into more than two output ports. This node would manage the following actions when necessary: (a) tap and binary- splitting, which consists of tapping a small percentage of the signal power to the local node (4-8%) and an w-splitting action (n=2); and (b) tap-and-continue. We call this type of node 2-STC node (binary-split-tap-continue). We compare it with other well known state-of-art proposals and analyze its benefits in terms of number of devices and power losses. An evaluation of applicability is given, showing that the binary-split restriction shows a good trade-off between power losses, bandwidth consumption and architectural simplicity. We conclude that the 2-STC node improves power efficiency and contributes to get a good trade-off between use of resources and optical power.

As stateful flow-aware services are becoming commonplace, distributed router architectures have to quickly assign packets being forwarded to service-specialized processors in order to balance flow processing and state among them. Moreover, packets belonging to the same flow must be always assigned to the same CPU, even if some of the service processors become unavailable. This paper presents two novel fast robust hashing algorithms for persistent flow-to-CPU mapping, that require less hashing operations per packet than previous robust hash algorithms, thus being able to fulfill all the above requirements to implement flow-aware services at wire-speed.