Ramon Aparicio-Pardo

Offline Impairment Aware RWA Algorithms for Cross-Layer Planning of Optical Networks

Transparent optical networks are the enabling infrastructure for converged multi-granular networks in the future Internet. The cross-layer planning of these networks considers physical impairments in the network layer design. This is complicated by the diversity of modulation formats, transmission rates, amplification and compensation equipments, or deployed fiber links. Thereby, the concept of quality of transmission (QoT) attempts to embrace the effects of the physical layer impairments, to introduce them in a multi-criterium optimization and planning process. This paper contributes in this field by the proposal and comparative evaluation of two novel offline impairment aware planning algorithms for transparent optical networks, which share a common QoT evaluation function. The first algorithm is based on an iterative global search driven by a set of binary integer linear programming formulations. Heuristic techniques are included to limit the binary programming complexity. The second algorithm performs different pre-orderings of the lightpath demand, followed by a sequential processing of the lightpath demands. The performance and the scalability of both approaches are investigated. Results reveal great scalability properties of the global search algorithm, and a performance similar to or better than the sequential schemes.

Transcoding live adaptive video streams at a massive scale in the cloud

More and more users are watching online videos produced by non-professional sources (e.g., gamers, teachers of online courses, witnesses of public events) by using an increasingly diverse set of devices to access the videos (e.g., smartphones, tablets, HDTV). Live streaming service providers can combine adaptive streaming technologies and cloud computing to satisfy this demand. In this paper, we study the problem of preparing live video streams for delivery using cloud computing infrastructure, e.g., how many representations to use and the corresponding parameters (resolution and bit-rate). We present an integer linear program (ILP) to maximize the average user quality of experience (QoE) and a heuristic algorithm that can scale to large number of videos and users. We also introduce two new datasets: one characterizing a popular live streaming provider (Twitch) and another characterizing the computing resources needed to transcode a video. They are used to set up realistic test scenarios. We compare the performance of the optimal ILP solution with current industry standards, showing that the latter are sub-optimal. The solution of the ILP also shows the importance of the type of video on the optimal streaming preparation. By taking advantage of this, the proposed heuristic can efficiently satisfy a time varying demand with an almost constant amount of computing resources.

Virtual topology design and flow routing in optical networks under multihour traffic demand

This article addresses the problem of finding a static virtual topology design and flow routing in transparent optical wavelength division multiplexing networks under a time-varying (multihour) traffic demand. Four variants of the problem are considered, using fixed or dynamically adaptable (meaning variable) flow routing, which can be splittable or unsplittable. Our main objective is to minimize the number of transceivers needed which make up for the main network cost. We formulate the problem variants as exact integer linear programs (ILPs) and mixed ILPs. For larger problem instances, we also propose a family of heuristics based on the concept of domination between traffic matrices. This concept provides the theoretical foundations for a set of techniques proposed to reduce the problem complexity. We present a lower bound to the network cost for the case in which the virtual topology could be dynamically reconfigured along time. This allows us to assess the limit on the maximum possible benefit that could be achieved by using optical reconfigurable equipment. Extensive tests have been conducted, using both synthetically generated and real-traced traffic demands. In the cases studied, results show that combining variable routing with splittable flows obtains a significant, although moderate, cost reduction. The maximum cost reduction achievable with reconfigurable virtual topologies was shown to be negligible compared to the static case in medium and high loads.

Cross-layer scheduler for video streaming over MPTCP

Transport protocols that can exploit multiple paths, especially MPTCP, do not match the requirements of video streaming: high average transmission delay, too strict reliability, and frequent head-of-line phenomenons resulting in abrupt throughput drops. In this paper, we address this mismatch by introducing a cross-layer scheduler, which leverages information from both application and transport layers to re-order the transmission of data and prioritize the most significant parts of the video. Our objective is to maximize the amount of video data that is received in time at the client. We show that current technologies enable the implementation of this cross-layer scheduler without much overhead. We then demonstrate the validity of our approach by studying the performance of an optimal cross-layer scheduler. The gap between the performance of the traditional scheduler versus the optimal scheduler justifies our motivation to implement a cross-layer scheduler in practice. We propose one implementation with basic cross-layer awareness. To evaluate the performance of our proposal, we aggregate a dataset of real MPTCP sessions and we use video stream encoded with HEVC. Our results show that our cross-layer proposal outperforms the traditional scheduler. Viewers not only benefit from the inherent advantages of using MPTCP (such as a better resilience to path failure) but also get a better QoE compared to the traditional scheduler.

(Non-)reconfigurable virtual topology design under multihour traffic in optical networks

This paper investigates offline virtual topology design in transparent optical networks under a multihour traffic demand. The main problem variant addressed here designs a reconfigurable virtual topology that evolves over time to more efficiently utilize network resources (the MH-VTD-R problem). The case of designing a static non-reconfigurable virtual topology that can accommodate the time-varying traffic (the MH-VTD-NR problem) is also considered. The objectives are to minimize: 1) the number of transceivers, which make up for the main network cost; and 2) the frequency of reconfiguration (for MH-VTD-R), which incurs additional overhead and potential service disruption. We formulate this multiobjective problem as an exact mixed integer linear program (MILP). Due to its high complexity, we propose a very efficient heuristic algorithm called Greedy Approach with Reconfiguration Flattening (GARF). GARF not only solves both (non-)reconfigurable problem variants, but it allows for tuning of the relative importance of the two objectives. Exhaustive experiments on real and synthetic traffic and comparison to previous proposals and bounds reveal the merits of GARF with respect to both solution quality and execution time. Furthermore, the obtained results indicate that the maximal transceiver cost savings achieved by the fully reconfigurable case may not be enough to justify the associated increase in reconfiguration cost. However, results show that an advantageous tradeoff between transceiver cost savings and reconfiguration cost can be achieved by a allowing a small number of virtual topology reconfigurations over time.

MatPlanWDM: an educational tool for network planning in wavelength-routing networks

This paper presents the MatPlanWDM tool, an educational network planning tool for wavelength-routing WDM networks. It includes a set of heuristic algorithms for solving the virtual topology design, and the routing and grooming of traffic flows on top of it. In addition, an implementation of the linear programming problem to obtain the optimal solution of the complete design is included for comparison. The input parameters to the planning problem are the network physical topology, the traffic matrix, and technological constraints like the number of transmitters, receivers, optical converters and wavelengths available. The tool is implemented as a MATLAB toolbox. The set of heuristic algorithms can be easily extended. A graphical interface is provided to plot the results obtained from different heuristics and compare them with the optimal solution in small-scale topologies.

Scheduled Virtual Topology Design under periodic traffic in transparent optical networks

This paper investigates offline planning and scheduling in transparent optical networks for a given periodic traffic demand. The main objective is to minimize the number of transceivers needed which make up for the main network cost. We call this problem “Scheduled Virtual Topology Design” and consider two variants: non-reconfigurable and reconfigurable equipment. We formulate both problems as exact MILPs (Mixed Integer Linear Programs). Due to their high complexity, we propose a more scalable tabu search heuristic approach, in conjunction with smaller MILP formulations for the associated subproblems. The main motivation of our research efforts is to assess the benefits of using reconfigurable equipment, realized as a reduction in the number of required transceivers. Our results show that the achieved reductions are not very significant, except for cases with large network loads and high traffic variability.

MILP formulations for scheduling lightpaths under periodic traffic

This paper addresses offline virtual topology design in transparent optical networks under given periodic traffic. We call this planning problem “Scheduled Virtual Topology Design”. Two problem variants are considered: for a network based on non-reconfigurable equipment and for a network based on reconfigurable equipment. Two MILP (Mixed Integer Linear Program) formulations are proposed, one for each alternative. The number of transceivers in the network is the selected cost figure to minimize. Tests are performed to evaluate the benefits of using reconfigurable equipment under different traffic conditions and network sizes. The reduction in the number of transceivers obtained by allowing temporal variations in the virtual topology seems low in all cases, indicating that using reconfigurable equipment may not be cost-effective for periodic traffic.

Multi-hour network planning based on domination between sets of traffic matrices

In multi-hour network design, periodic traffic variations along time are considered in the dimensioning process. Then, the non coincidence of traffic peaks along the day or the week can be exploited. This paper investigates the application of the traffic domination relation between sets of traffic matrices to multi-hour network planning. Two problem variants are considered: a network with a static, and with a dynamic traffic routing. We derive a set of techniques for, given a multi-hour traffic demand potentially composed of hundreds of matrices, obtaining a traffic series with a smaller number of matrices. The traffic domination relation guarantees that the network designed for the simplified series is suitable for the original one. Also, we apply the domination relation to derive lower bounds to the network cost, and upper bounds to the suboptimality incurred by simplifying the traffic demand. The algorithms proposed are tested in a case of study with the Abilene network. In our tests, a long traffic series could be reduced to a small number of traffic matrices, and be effective for network planning.

Robust upgrade in optical networks under traffic uncertainty

Optical network operators face the challenge of upgrading the WDM network capacity to adapt to estimated traffic growths. Network upgrades are commonly carried out in scheduled intervals (i.e. every six months), using traffic forecasts. The uncertainty in the forecasts is a major issue in the capacity upgrading process. If it is not handled appropriately, the network is exposed to service degradation caused by an unexpected traffic progression. Despite of its relevance, the effects of uncertainty in the forecasts is a factor that has not been well studied in the literature. In this paper, we apply the robust optimization paradigm to incorporate this uncertainty into the network upgrade problem. Under this robust network upgrade model, we can dimension the network by tuning the tradeoff between network cost and robustness level. This proposal is applied to a case study where several experiments are conducted comparing different levels of robustness and different WDM technologies, namely pure 10G (single line rate), pure 40G SLR, pure 100G SLR and 10/40/100G MLR (mixed line rate).