Abdeltouab Belbekkouche

Novel reinforcement learning-based approaches to reduce loss probability in buffer-less OBS networks

Optical Burst Switching (OBS) is a promising switching paradigm for the next generation Internet. A buffer-less OBS network can be implemented simply and cost-effectively without the need for either wavelength converters or optical buffers which are, currently, neither cost-effective nor technologically mature. However, this type of OBS networks suffers from relatively high loss probability caused by wavelength contentions at core nodes. This could prevent or, at least, delay the adoption of OBS networks as a solution for the next generation optical Internet. To enhance the performance of buffer-less OBS networks, we propose three approaches: (a) a reactive approach, called Reinforcement Learning-Based Deflection Routing Scheme (RLDRS) that aims to resolve wavelength contentions, after they occur, using deflection routing; (b) a proactive multi-path approach, called Reinforcement Learning-Based Alternative Routing (RLAR), that aims to reduce wavelength contentions; and (c) an approach, called Integrated Reinforcement Learning-based Routing and Contention Resolution (IRLRCR), that combines RLAR and RLDRS to conjointly deal with wavelength contentions proactively and reactively. Simulation results show that both RLAR and RLDRS reduce, effectively, loss probability in buffer-less OBS networks and outperform the existing multi-path and deflection routing approaches, respectively. Moreover, simulation results show that a substantial performance improvement, in terms of loss probability, is obtained using IRLRCR.

Reinforcement learning-based best path to best gateway scheme for wireless mesh networks

This paper addresses the problem of optimal routing in backbone wireless mesh networks (WMNs) where each mesh router (MR) is equipped with multiple radio interfaces and a subset of nodes serve as gateways to the Internet.

A Reinforcement Learning-Based Deflection Routing Scheme for Buffer-Less OBS Networks

Optical burst switching (OBS) is a promising switching paradigm for the next generation Internet. A buffer-less OBS network can be implemented simply and cost-effectively without the need for either wavelength converters or optical buffers which are, currently, neither cost-effective nor technologically mature. However, this type of OBS networks suffers from relatively high loss probability caused by wavelength contentions at core nodes. This issue could prevent or, at least, delay the adoption of OBS networks as a solution for the next generation optical Internet. Deflection routing is one of the contention resolution approaches that have been proposed to tackle this problem. In addition to be cost-effective, it is also efficient in reducing loss probability, especially with low and moderate traffic loads. In this paper, we propose an adaptive reinforcement learning-based deflection routing scheme (RLDRS) which focuses on the route selection issue by choosing the optimal alternative output port in terms of both loss probability and delay when deflection is performed. Moreover, RLDRS limits the number of authorized deflections of each burst in order to reduce the additional traffic caused by deflection routing and to prohibit excessive deflections. Simulation results show that RLDRS reduces effectively loss probability and outperforms shortest path deflection routing (SPDR).

An Adaptive Reinforcement Learning-based Approach to Reduce Blocking Probability in Bufferless OBS Networks

Optical burst switching (OBS) is an optical switching paradigm which offers a good tradeoff between the traditional optical circuit switching (OCS) and optical packet switching (OPS) since it has the relatively easy implementation of the first and the efficient bandwidth utilization of the second. Hence, OBS is a promising technology for the next generation optical Internet. A buffer-less OBS network can be implemented using ordinary optical communication equipment without the need for either wavelength converters or optical memories. However, OBS networks suffer from a relatively high blocking probability, a primary metric of interest, because of contention. In this paper we propose a new contention resolution scheme for buffer-less OBS networks using deflection routing and reinforcement learning agents to dynamically assign an appropriate offset time (OT) to each burst in order to reduce losses caused, for example, by insufficient offset time (IOT) in case only deflection is used. Simulation results demonstrate that our approach reduces effectively blocking probability, whereas it maintains a reasonable end-to-end delay for each burst. Hence, it establishes an appropriate tradeoff between loss rate and delay.

Reinforcement learning based routing in wireless mesh networks

This paper addresses the problem of efficient routing in backbone wireless mesh networks (WMNs) where each mesh router is equipped with multiple radio interfaces and a subset of nodes serve as gateways to the Internet. Most routing schemes have been designed to reduce routing costs by optimizing one metric, e.g., hop count and interference ratio. However, when considering these metrics together, the complexity of the routing problem increases drastically. Thus, an efficient and adaptive routing scheme that takes into account several metrics simultaneously and considers traffic congestion around the gateways is needed. In this paper, we propose an adaptive scheme for routing traffic in WMNs, called Reinforcement Learning-based Distributed Routing (RLBDR), that (1) considers the critical areas around the gateways where mesh routers are much more likely to become congested and (2) adaptively learns an optimal routing policy taking into account multiple metrics, such as loss ratio, interference ratio, load at the gateways and end-to end delay. Simulation results show that RLBDR can significantly improve the overall network performance compared to schemes using either Metric of Interference and Channel switching, Best Path to Best Gateway, Expected Transmission count, nearest gateway (i.e., shortest path to gateway) or load at gateways as a metric for path selection.

Path-Based QoS Provisioning for Optical Burst Switching Networks

Quality-of-service (QoS) provisioning is an essential feature in next-generation networks. In this paper, we investigate the ability of optical burst switching (OBS) networks to guarantee loss-free transmission inside the network for guaranteed bursts. More specifically, we propose a QoS approach, called path-based QoS provisioning (PQP), to provide absolute QoS provisioning for OBS networks. PQP relies on: 1) routing and wavelength assignment to establish, whenever possible, nonoverlapping paths between each pair of OBS edge nodes and 2) a synchronization scheme to guarantee QoS when the solution in 1) contains overlapping paths because of the limited number of wavelengths. For 1), we propose a routing and wavelength assignment approach, which uses an efficient integer linear programming (ILP) model to determine routing paths and a tabu search algorithm to assign wavelengths to these paths. For 2), we propose a path synchronization scheme, called path-based synchronous transmission scheme (PST). PST synchronizes the transmissions in each set of overlapping paths while maximizing the capacity of each path to transmit guaranteed traffic and guaranteeing fairness when allocating bandwidth to conflicting paths; this is performed using efficient ILP formulations. To improve the performance of best effort traffic and preserve statistical multiplexing gain and high resource utilization of the OBS network, we propose a wavelength selection scheme, called path-based best effort wavelength selection scheme, to send best effort bursts. Simulation results using ns-2 simulator show that PQP successfully provides absolute QoS provisioning for guaranteed traffic and improves significantly the performance of best effort traffic.

A Novel Formulation for Routing and Wavelength Assignment Problem in OBS Networks

Optical Burst Switching (OBS) networks are candidate to play an important role in next generation optical networks. Routing and wavelength assignment may have a decisive impact on the performance of these all-optical networks. We propose a novel Integer Linear Programming (ILP) formulation for the routing problem which is, at the contrast of existing models, specific to the nature of OBS networks and is based on the network topology. To resolve efficiently this model, we propose a genetic algorithm. Also, we propose a wavelength assignment heuristic which uses the solution of the routing optimization model. Simulation results show the effectiveness of our model in improving the performance of OBS networks.

Topology-aware wavelength partitioning for DWDM OBS networks: A novel approach for absolute QoS provisioning

Optical Burst Switching (OBS) is a promising switching technology for the next generation all-optical networks. An OBS network without wavelength converters and fiber delay lines can be implemented simply and cost-effectively using the existing technology. However, this kind of networks suffers from a relatively high burst loss probability at the OBS core nodes. To overcome this issue and consolidate OBS networks with QoS provisioning capabilities, we propose a wavelength partitioning approach, called Optimization-based Topology-aware Wavelength Partitioning approach (OTWP). OTWP formulates the wavelength partitioning problem, based on the topology of the network, as an Integer Linear Programming (ILP) model and uses a tabu search algorithm (TS) to resolve large instances efficiently. We use OTWP to develop an absolute QoS differentiation scheme, called Absolute Fair Quality of service Differentiation scheme (AFQD). AFQD is the first absolute QoS provisioning scheme that guarantees loss-free transmission for high priority traffic, inside the OBS network, regardless of its topology. Also, we use OTWP to develop a wavelength assignment scheme, called Best Effort Traffic Wavelength Assignment scheme (BETWA). BETWA aims to reduce loss probability for best effort traffic. To make AFQD adaptive to non-uniform traffic, we develop a wavelength borrowing protocol, called Wavelength Borrowing Protocol (WBP). Numerical results show the effectiveness of the proposed tabu search algorithm to resolve large instances of the partitioning problem. Also, simulation results, using ns-2, show that: (a) AFQD provides an excellent quality of service differentiation; (b) BETWA substantially decreases the loss probability of best effort traffic to a remarkably low level for the OBS network under study; and (c) WBP makes AFQD adaptive to non-uniform traffic by reducing efficiently blocking probability for high priority traffic.

An Absolute and Fair QoS Differentiation Scheme for DWDM OBS Networks

Optical Burst Switching (OBS) is a promising switching technology for the next generation all-optical networks. An OBS network without wavelength converters and fiber delay lines can be implemented simply and cost-effectively using the existing technology. However, this kind of networks suffers from a relatively high burst loss probability at the OBS core nodes. To overcome this issue and consolidate OBS networks with QoS provisioning capabilities, we propose an absolute QoS differentiation scheme, called Absolute Fair Quality of service Differentiation (AFQD), which is based on a wavelength partitioning scheme, called Optimization Topology-aware Wavelength Partitioning scheme (OTWP). AFQD is the first absolute QoS provisioning scheme that guarantees loss-free transmission for high priority traffic inside the OBS network. Simulation results show that AFQD not only guarantees loss-free transmission for high priority traffic but also substantially decreases the loss probability of best effort traffic to a remarkable level compared to the existing schemes.

QoS Provisioning for Wireless Mesh and Optical Burst Switching Convergence

Wireless Mesh Networks (WMN) have attracted increasing attention from the research community as a high-performance and low-cost solution to last-mile broadband Internet access. In the other side, Optical Burst Switching (OBS) is a promising access technology that uses optical fiber with burst switching paradigm. In this paper, we propose a novel Metropolitan Area Network (MAN) architecture called Optical Burst Wireless Mesh Architecture (OBWMA) which integrates WMN at the user access side and OBS at the core of the MAN. OBWMA aims to combine advantages of both WMNs and OBS networks, such as large coverage at low cost and bandwidth availability. We develop an analytical model to compute the end-to-end delay in OBWMA in order to support flow requests with delay constraints. Furthermore, we propose a novel QoS provisioning scheme for the WMN part (WQP), and a novel bandwidth provisioning scheme for the OBS part (WPBP). Simulation results using ns-2 demonstrate the feasibility of OBWMA, the accuracy of our analytical model and the effectiveness of WQP and WPBP to provide QoS provisioning for the converged network.