Scheduled Lightpath Demands Research Articles

Deterministic Lightpath Scheduling and Routing in Elastic Optical Networks

A huge torrent of data traffic is generated from various heterogeneous applications and services at the Internet backbone. In general, at the backbone, all such applications and services are allocated spectral resources under a shared spectrum environment within elastic optical networks (EONs). In such a fully shared environment, connection requests (CRs) belonging to different traffic profiles compete for spectral resources. Hence, it is very challenging for network operators to resolve resource conflict that occur at the time of provisioning resources to such CRs. The heterogeneous traffic profile (HTP) considered in this work includes permanent lightpath demands (PLDs) and scheduled lightpath demands (SLDs). We propose various distance adaptive routing and spectrum assignment (DA-RSA) heuristics to resolve resource conflict among these two traffic profiles in EONs under a full sharing environment. Conventionally, preemption was the only technique to resolve such resource conflict among HTPs. Since preemption involves the overhead of selecting CRs to be preempted and then deallocating the resources given to those CRs, excessive preemption adversely affects the performance of the network. Therefore, in this work, we utilized bandwidth splitting as a solution to resolve resource conflict among HTPs under such a shared environment in EONs. Moreover, an integrated solution consisting of splitting and preemption is also proposed. We refer to this new integration as flow-based preemption. Our simulation results demonstrate that bandwidth splitting-based heuristics yield significant improvement in terms of the amount of bandwidth accepted in the network, link and node utilization ratio, number of transponders utilized and the amount of bandwidth dropped due to preemption. Moreover, the flow-based preemption approach is proved to be superior in performance amongst all proposed strategies.

Minimizing Inter-Core Crosstalk Jointly in Spatial, Frequency, and Time Domains for Scheduled Lightpath Demands in Multi-Core Fiber-based Elastic Optical Network

Elastic optical networks (EON) technology in combination with space division multiplexing (SDM) is considered as having the potential to expand the transmission capacity of optical transport networks. However, inter-core crosstalk may cause serious signal impairment in a multi-core fiber (MCF) links. At the same time, scheduled lightpath demands, for which the expected setup and teardown times are known in advance, are considered as an important type of traffic demand for future networks. In this article, we develop approaches to schedule simultaneous lightpaths onto non-adjacent MCF cores so as to reduce inter-core crosstalk between these lightpaths. To this end, we first define a new metric to estimate the inter-core crosstalk jointly considering the spatial, frequency, and time domains. We then tackle the routing, spectrum, core, and time assignment (RSCTA) problem for the MCF-based EON by developing an integer linear programming (ILP) model, as well as an auxiliary graph (AG) based heuristic algorithm, which jointly optimize spectrum resource utilization and reduce the lightpath inter-core crosstalk. Simulation studies show the effectiveness of the proposed approach in terms of both performance aspects. In addition, the performance of the proposed heuristic algorithm is shown to be close to that of the ILP model in small networks.

A biased random-key genetic algorithm for routing and wavelength assignment under a sliding scheduled traffic model

The problem of routing and wavelength assignment in optical networks consists in minimizing the number of wavelengths that are needed to route a set of demands, such that demands routed using lightpaths that share common links are assigned to different wavelengths. We present a biased random-key genetic algorithm for approximately solving the problem of routing and wavelength assignment of sliding scheduled lightpath demands in optical networks. In this problem variant, each demand is characterized not only by a source and a destination, but also by a duration and a time window in which it has to be met. Computational experiments show that the numerical results obtained by the proposed heuristic improved upon those obtained by a multistart constructive heuristic. In addition, the biased random-key genetic algorithm obtained much better results than an existing algorithm for the problem, finding solutions that use roughly 50% of the number of wavelengths determined by the latter.

Optimal attack-aware RWA for scheduled lightpath demands

In Transparent optical networks (TONs), the data signals remain in the optical domain for the entire transmission path, creating a virtual topology over the physical connections of optical fibers. Due to the increasingly high data rates and the vulnerabilities related to the transparency of optical networks, TONs are susceptible to different physical layer attacks, including high-power jamming attacks. Developing strategies to handle such attacks and mitigating their impact on network performance is becoming an important design problem for TONs. Some approaches for handling physical layer attacks for static and dynamic traffic in TONs have been presented in recent years. In this work, we propose an integer linear program (ILP) formulation to control the propagation of such attacks in TONs for scheduled lightpath demands, which need periodic bandwidth usage at certain predefined times. We consider both the fixed window model, where the start and end timings of the demand are known in advance, and the sliding window model, where exact start and end times are unknown but fall within a larger window. We consider a number of potential objectives for attack-aware RWA and show how the flexibility to schedule demands in time can impact these objectives, compared to both attack-unaware and fixed window models.

An improved scheduled traffic model utilizing bandwidth splitting in elastic optical networks

Abstract The surge of traffic in today’s networks gave birth to elastic optical networking paradigm. In this paper, first we propose to use the scheduled traffic model (STM) in elastic optical networks (EONs) to ensure guaranteed availability of resources to demands which enter into the network with a predetermined start and end times. In optical networks, such demands are referred to as scheduled lightpath demands (SLDs). To increase the amount of bandwidth accepted in network, next we introduce a time aware routing and spectrum assignment (TA-RSA) approach. We observed that provisioning of bulky SLDs has become more challenging in EONs due to enforcement of RSA constraints. To address this challenge, we improve the proposed STM and designed three heuristics for its implementation in EONs. In this work, we collectively refer to these heuristics as bandwidth segmented RSA (BSRSA). The improved STM (iSTM) allows splitting of SLDs in bandwidth dimension by utilizing the knowledge of attributes viz. demand holding time, overlapping in time and bandwidth requested by SLDs. Our numerical results show that BSRSA consistently outperformed over TA-RSA under all distinctive experimental cases that we considered and achieved fairness in serving heterogeneous bandwidth SLDs. The impact of splitting on the number and capacity of transponders at nodes is also gauged. It is observed that ingenious splitting of demands increases the number of resources (on links and nodes) used, and their utilization, leading to an increase in bandwidth accepted in the network.

A post-optimization method for the routing and wavelength assignment problem applied to scheduled lightpath demands

We consider here a NP-hard problem related to the Routing and Wavelength Assignment (RWA) problem in optical networks, dealing with Scheduled Lightpath Demands (SLDs). An SLD is a connection demand between two nodes of the network, during a certain time. Given a set of SLDs, we want to assign a lightpath, i.e. a routing path and a wavelength, to each SLD, so that the total number of required wavelengths is minimized. The constraints are the following: a same wavelength must be assigned all along the edges of the routing path of any SLD; at any time, a given wavelength on a given edge of the network cannot be used to satisfy more than one SLD. To solve this problem, we design a post-optimization method improving the solutions provided by a heuristic. The experimental results show that this post-optimization method is quite efficient to reduce the number of necessary wavelengths.

A heuristic algorithm for lightpath scheduling in next-generation WDM optical networks

We study the routing and wavelength assignment (RWA) problem of scheduled lightpath demands (SLDs) in all-optical wavelength division multiplexing networks with no wavelength conversion capability. We consider the deterministic lightpath scheduling problem in which the whole set of lightpath demands is completely known in advance. The objective is to maximize the number of established lightpaths for a given number of wavelengths. Since this problem has been shown to be NP complete, various heuristic algorithms have been developed to solve it suboptimally. In this paper, we propose a novel heuristic RWA algorithm for SLDs based on the bee colony optimization (BCO) metaheuristic. BCO is a newborn swarm intelligence metaheuristic approach recently proposed to solve complex combinatorial optimization problems. We compare the efficiency of the proposed algorithm with three simple greedy algorithms for the same problem. Numerical results obtained by numerous simulations performed on the widely used realistic European Optical Network topology indicate that the proposed algorithm produces better-quality solutions compared to those obtained by greedy algorithms. In addition, we compare the results of the BCO---RWA---SLD algorithm with four other heuristic/metaheuristic algorithms proposed in literature to solve the RWA problem in the case of permanent (static) traffic demands.

A new model for allocating resources to scheduled lightpath demands

Recent research has clearly established that holding-time-aware routing-and-wavelength-assignment (RWA) schemes lead to significant improvements in resource utilization for scheduled traffic. Two different models have been proposed for scheduled traffic in the literature – (i) the fixed window model, where the setup and the teardown times of the scheduled demands are known in advance and (ii) the sliding window model, where a demand can be allocated anytime within a larger time-window. In this paper, we introduce a new model, the segmented sliding window model, where a demand may be decomposed into two or more components and each component can be sent separately. We present an integer linear program (ILP) formulation for resource allocation under the proposed segmented sliding window model and show that both the fixed and the traditional sliding window models can be treated as a special case of our generalized segmented sliding window model. We consider networks both with and without wavelength converters, and include the option of path protection for each lightpath. For larger networks, we also present a heuristic algorithm for allocating resources. Finally, we show through simulations that our approach leads to significantly higher throughput, even compared to the recent holding-time-aware RWA schemes, which have already been shown to outperform holding-time-unaware models.

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.

A post-optimization method to route scheduled lightpath demands with multiplicity

Abstract We consider a NP-hard problem related to the routing and wavelength assignment (RWA) problem in optical networks, dealing with scheduled lightpath demands (SLDs) with multiplicity. A SLD is a connection demand between two nodes of the network, during a certain time. Each SLD requires a given number of wavelengths (its multiplicity). Given a set of SLDs, we want to assign a lightpath (i.e. a routing path and the necessary wavelengths) to each SLD, so that the total number of required wavelengths is minimized. To solve the problem, we design a post-optimization method allowing to improve the solutions provided by a heuristic. Experimental results show that this post-optimization method is quite efficient to reduce the number of necessary wavelengths.

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.

Quality of service based resource allocation for scheduled lightpath demands

In this paper, we consider resource allocation under the scheduled traffic model, where the setup and teardown times of scheduled demands are known in advance. A number of integer linear program (ILP) solutions for this problem have been presented in the literature. Most of these ILPs minimize the number of wavelength links. A more appropriate metric, for wavelength routed, all-optical networks, is to minimize the congestion (the maximum number of lightpaths on a single fiber link) of the network. We present a new ILP formulation for routing and wavelength allocation, under the scheduled traffic model that minimizes the congestion of the network. We propose two levels of service, where idle backup resources can be used to carry low-priority traffic, under fault-free conditions. When a fault occurs, and resources for a backup path need to be reclaimed, any low-priority traffic on the affected channels is dropped. The results demonstrate that this can lead to significant improvements over single service level models. We also show that the complexity of our formulation (in terms of the number of integer variables) is lower, even compared to existing approaches, which only allow a single level of service. Therefore, we are able to generate optimal solutions for practical networks within a reasonable amount of time, whereas existing formulations often do not find the optimal solution even after 2 h. Finally, we present a simple and fast heuristic that can quickly generate good solutions for much larger networks.

Assessing the economic benefit of introducing multi-granularity switching cross-connects in optical transport networks

In this article we assess the economic gain obtained by introducing multi-granularity switching optical cross-connects (MG-OXCs) in an optical transport network. An MG-OXC is an equipment able to switch wavelengths, to aggregate (disaggregate) wavelengths into (from) groups of wavelengths called wavebands and to switch wavebands. We evaluate the economic gain by comparing the cost of instantiating (i.e., provisioning) a set of Scheduled Lightpath Demands (SLDs) in a network of wavelength-switching optical cross-connects (WXCs) against the cost of instantiating them in a network of MG-OXCs. We formulate the problems of instantiating SLDs in both a network of WXCs and a network of MG-OXCs as two combinatorial optimization problems and compute approximate solutions to these problems using Tabu Search (TS) based algorithms. Finally, we define a method to determine the conditions (traffic distribution, cost of switching matrices and ports, etc.) under which a network of MG-OXCs is more economical than a network of WXCs

Heuristic algorithms for the routing and wavelength assignment of scheduled lightpath demands in optical networks

This paper addresses the problem of routing and wavelength assignment (RWA) of scheduled lightpath demands (SLDs) in wavelength routed optical networks with no wavelength converters. The objective is to minimize the number of wavelengths used. This problem has been shown to be NP-complete so heuristic algorithms have been developed to solve it suboptimally. Suggested is a tabu search algorithm along with two simple and fast greedy algorithms for the RWA SLD problem. We compare the proposed algorithms with an existing tabu search algorithm for the same problem and with lower bounds derived in this paper. Results indicate that the suggested algorithms not only yield solutions superior in quality to those obtained by the existing algorithm, but have drastically shorter execution times

Heuristic algorithms for the routing and wavelength assignment of scheduled lightpath demands in optical networks

Heuristic algorithms for the routing and wavelength assignment of scheduled lightpath demands in optical networks

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.