Maurice Gagnaire

Routing and wavelength assignment of scheduled lightpath demands

We present algorithms that compute the routing and wavelength assignment (RWA) for scheduled lightpath demands in a wavelength-switching mesh network without wavelength conversion functionality. Scheduled lightpath demands are connection demands for which the setup and teardown times are known in advance. We formulate separately the routing problem and the wavelength assignment problem as spatio-temporal combinatorial optimization problems. For the former, we propose a branch and bound algorithm for exact resolution and an alternative tabu search algorithm for approximate resolution. A generalized graph coloring approach is used to solve the wavelength assignment problem. We compared the proposed algorithms to an RWA algorithm that sequentially computes the route and wavelength assignment for the scheduled lightpath demands.

Experimental Demonstration of an Impairment Aware Network Planning and Operation Tool for Transparent/Translucent Optical Networks

Core optical networks using reconfigurable optical switches and tunable lasers appear to be on the road towards widespread deployment and could evolve to all-optical mesh networks in the coming future. Considering the impact of physical layer impairments in the planning and operation of all-optical (and translucent) networks is the main focus of the Dynamic Impairment Constraint Optical Networking (DICONET) project. The impairment aware network planning and operation tool (NPOT) is the main outcome of DICONET project, which is explained in detail in this paper. The key building blocks of the NPOT, consisting of network description repositories, the physical layer performance evaluator, the impairment aware routing and wavelength assignment engines, the component placement modules, failure handling, and the integration of NPOT in the control plane are the main contributions of this study. Besides, the experimental result of DICONET proposal for centralized and distributed control plane integration schemes and the performance of the failure handling in terms of restoration time is presented in this study.

LERP: a Quality of Transmission Dependent Heuristic for Routing and Wavelength Assignment in Hybrid WDM Networks

Over the last decade, numerous routing and wavelength assignment (RWA) algorithms have been developed for WDM optical networks planning. Most of these algorithms neglect the feasibility of the obtained lightpaths. In this paper, we propose a new algorithm, called LERP (Lightpath Establishment with Regenerator Placement), that enables to solve the problem of RWA in guaranteeing the feasibility of the obtained solution. A lightpath is said admissible if the BER (Bit Error Rate) at its destination node remains acceptable (remains under a given threshold). In the case of BER non-admissibility, one or more electrical regenerators may be placed along the lightpath. The LERP algorithm aims at minimizing the number of regenerators necessary to guarantee the quality of transmission along the lightpath. The originality of the our approach consists in considering simultaneously four physical layer impairments, namely, chromatic dispersion, polarization mode dispersion, amplified spontaneous emission and non-linear phase shift. The efficiency of the LERP algorithm is demonstrated via a numerical comparison with one of the alternative solutions proposed in the literature. Numerical simulations have been carried out in the context of the 18-node NSF network.

Analytical model for the IPACT dynamic bandwidth allocation algorithm for EPONs

Feature Issue on Passive Optical Network Architectures and TechnologiesWe describe the research that has been performed in the field of the dynamic bandwidth allocation algorithm, interleaved polling with adaptive cycle time (IPACT), for Ethernet passive optical networks (EPON). The main focus has been on modeling packet delay analytically. To derive the packet delay, an important part of the analysis will also focus on the cycle time. It is assumed that the traffic load is symmetric, that packet arrivals are Poisson distributed, and that packets have fixed size. Simulations were performed to prove the accuracy of the analytical model. Some extensions and limitations of the model are treated, including asymmetric traffic load, packet size distribution, self-similar traffic, and differentiated services.

An overview of broad-band access technologies

The provision of broad-band services based on either the Internet or the asynchronous transfer mode (ATM) technique requires a new generation of access networks. In the short term, solutions such as x-digital subscriber line (DSL) and hybrid fiber coaxial (HFC), allowing the reuse of existing infrastructures look very promising. For the longer term, new infrastructures based either on radio or on optical access links seem preferable. Three x-DSL techniques aiming at high-bit-rate transmission over twisted pairs are presented: high-bit-rate DSL, asymmetrical DSL, and very-high-bit-rate DSL. An extension of existing cable television networks known as HFC is also described. Two other prospective approaches, wireless in the loop (WITL) and fiber in the loop (FITL), are then presented. Several techniques are considered for WITL: digital enhanced cordless telecommunication local multipoint distribution service, wireless ATM, and low Earth orbit satellite constellations. The various architectural alternatives for the FITL approach are discussed, a special interest being dedicated to the synchronous digital hierarchy self-healing loop and the ATM over a passive optical network. We mention the main experiments and the standardization activities inherent to the domain.

Diverse routing of scheduled lightpath demands in an optical transport network

This article addresses the problem of defining working and protection paths for scheduled lightpath demands (SLDs) in an optical transport network. An SLD is a demand for a set of lightpaths (connections), defined by a tuple (s, d, n, /spl alpha/, /spl omega/), where s and d are the source and destination nodes of the lightpaths, n is the number of requested lightpaths and /spl alpha/, /spl omega/ are the set-up and tear-down dates of the lightpaths. The problem is formulated as a combinatorial optimization problem where the objective is to minimize the number of channels required to instantiate the lightpaths. Two techniques are used to achieve this goal: channel reuse and backup-multiplexing. The former consists of assigning the same channel (either working or spare) to several lightpaths, provided that these lightpaths are not simultaneous in time. The latter consists of sharing a spare channel among multiple lightpaths. A spare channel cannot be shared if two conditions hold: a) the working paths of these lightpaths have at least one span in common and b) these lightpaths are simultaneous in time. In the other cases, the spare channel can be shared. We propose a simulated annealing (SA) based algorithm to find approximate solutions to this optimization problem since finding exact solutions is computationally intractable. The results show that backup-multiplexing improves the utilization of channels but requires significant computing capacity. Under a fixed computing capacity budget, the technique is useful in cases where there is little time disjointness among SLDs.

Network Dimensioning under Scheduled and Random Lightpath Demands in All-Optical WDM Networks

In WDM optical networks connection requests can be classified into three different types: Permanent Lightpath Demands (PLDs), Scheduled Lightpath Demands (SLDs), and Random Lightpath Demands (RLDs). These three types of traffic demands are considered for network planning, network engineering and traffic engineering respectively. In this paper we investigate the Routing and Wavelength Assignment (RWA) problem in all-optical WDM networks operating under the wavelength continuity constraint by jointly considering PLDs, SLDs and RLDs. We aim to model a realistic situation where an operator wishes to employ its optical network initially designed for PLDs and/or SLDs to offer on the fly lightpath provisioning. To the best of our knowledge, our global approach has not already been investigated in the literature. According to the considered timescale, various types of optimization tools are used. Numerous numerical results are presented and discussed to outline the benefits of such a global perspective.

Resource Provisioning for Enriched Services in Cloud Environment

Cloud services are based on the provisioning of computing, storage, and networking resources in order to satisfy requests generated by remote end-users. High speed Internet access and multi-core Virtual Machines (VMs) enable today the provisioning of diversified and enriched types of services in Cloud environment. In this paper, we consider several types of basic services and show how their orchestration may lead to the provisioning of more sophisticated services. For this purpose, we define four types of requests that cover the wide spectrum of possible services. We then formulate the resource provisioning problem as a Mixed Integer Linear Program (MILP). We assume that the underlying infrastructure is based on a set of end-to-end connections with guaranteed sustainable bandwidth such as Carrier-Grade Ethernet (CGE) circuits. We investigate the impact of two innovative services on resource allocation carried out by a Cloud Service Provider (CSP). These services correspond to distributed data storage and to multicast data transfer. For the former service, we consider the possibility of splitting a storage request onto different remote storage nodes. The latter service aims to distribute a same data sequence from one server towards multiple remote nodes assuming a limited number of network nodes have multicast capacities. These two innovative services provide a gain of 7% in terms of accepted requests when applied to the 18-node NSFnet backbone network.

Lightpath Rerouting Strategies in WDM All-Optical Networks Under Scheduled and Random Traffic

In WDM all-optical networks without wavelength conversion, traffic rerouting is motivated either by an optimization of resource utilization or by network survivability. In this paper, we use rerouting to optimize network resources allocation in order to set up an incoming lightpath demand to be blocked for lack of resources. Rerouting aims at reassigning the wavelength and/or the path of one or several established connections in order to free enough wavelengths to satisfy the incoming demand. Rerouting refers implicitly to dynamic traffic. In most previous studies related to rerouting, only random (dynamic) traffic is considered. In this paper, we propose a new lightpath rerouting scheme considering three types of traffic demands, referred to as permanent lightpath demands (PLDs), scheduled lightpath demands (SLDs), and random lightpath demands (RLDs). PLDs are static, whereas SLDs and RLDs are dynamic. SLDs are preplanned, whereas RLDs are stochastic. PLDs may be seen as a particular case of SLDs. PLDs and SLDs correspond to guaranteed services, whereas RLDs correspond to best-effort services. Thus, PLDs and SLDs cannot be rerouted. We here describe two new routing and wavelength assignment (RWA) strategies applying rerouting. Both strategies assume that PLDs are routed offline during the network planning phase. The first strategy computes the RWA for SLDs and RLDs on the fly. The second strategy proceeds in two separate phases. It first computes offline the RWA for SLDs before considering RLDs on the fly on the remaining network resources. Our rerouting schemes aim at minimizing the number of RLDs or the number of optical channels to be rerouted. Through numerical examples and experimental simulations, we outline that routing SLDs offline and RLDs online instead of routing SLDs and RLDs online enables lower rejection ratios. We also compare our proposed rerouting algorithms with other approaches from the literature in terms of complexity.

Dynamic Resource Allocation in Cloud Environment Under Time-variant Job Requests

In Cloud environments, efficient resource provisioning and management present today a challenging issue because of the dynamic nature of the Cloud on one hand, and the need to satisfy heterogeneous resource requirements on the other hand. In such dynamic environments where end-users can arrive and leave the Cloud at any time, a Cloud service provider (CSP) should be able to make accurate decisions for scaling up or down its data-centers while taking into account several utility criteria, e.g., the delay of virtual resources setup, the migration of existing processes, the resource utilization, etc. In order to satisfy both parties (the CSP and the end-users), an efficient and dynamic resource allocation strategy is mandatory. In this paper, we propose an original approach for dynamic resource allocation in a Cloud environment. Our proposal considers computing job requests that are characterized by their arrival and teardown times, as well as a predictive profile of their computing requirements during their activity period. Assuming a prior knowledge of the predicted computing resources required by end-users, we propose and investigate several algorithms with different optimization criteria. However, prediction errors may occur resulting in some cases in the drop of one or several computing requests. Our proposed algorithms are compared in terms of various performance parameters including the rejection ratio, the dropping ratio, as well as the satisfaction of the endusers and the CSP.