Immediate reservation (IR) and advance reservation (AR) are the two main reservation mechanisms currently implemented on large-scale scientific optical networks. They can be used to satisfy both provisioning delay and low blocking for delay-tolerant applications. Therefore, it seems reasonable that future optical network provisioning systems will provide both mechanisms in hybrid IR/AR scenarios. Nonetheless, such scenarios can increase the blocking of IR if no quality-of-service (QoS) policies are implemented. A solution could be to quantify such blocking performance based on the current network load and implement mechanisms that would act accordingly. However, current blocking analytical models are not able to deal with both IR and AR. In this paper, we propose an analytical model to compute the network-wide blocking performance of different IR/AR classes within the scope of a multiservice framework for optical wavelength-division multiplexing (WDM) networks. Specifically, we calculate the blocking on two common optical network scenarios using the fixed-point approximation analysis: on wavelength conversion capable and wavelength-continuity constrained networks. Performance results show that our model provides good accuracy compared to simulation results, even in a scenario with multiple reservation classes defined by different book-ahead times.

Current Internet and large-scale experimentation applications need to satisfy short provisioning delay and low blocking demands. Both can be guaranteed by using immediate reservation (IR) and advance reservation (AR), respectively. However, the scheduling of both reservation types in the same network can especially degrade the performance of IR if no extra policies are applied. In order to enhance such class-based policies, we need to quantify the future performance of the system, thus requiring to model its behavior. In this paper, we propose the use of a two-fold probability transition Markov chain successfully applied in the past in offset-based reservation systems. Results show the good accuracy of the model to simulation results, even in an scenario with multiple traffic classes defined by different book-ahead times. Such a performance validates its applicability to a wide range of immediate and advance reservation systems.

Ant colony optimization (ACO) is a probabilistic technique used for solving complex computational problems, such as finding optimal routes in networks. It has been proved to perform better than simulated annealing and genetic algorithm approaches for solving dynamic problems. ACO algorithms can quickly adapt to real-time changes in the system. In this paper, we propose an ACO-based algorithm to solve the dynamic anycast routing and wavelength assignment (RWA) problem in wavelength-routed WDM networks. Using extensive simulations, we show that ACO-based anycast RWA significantly reduces blocking probability compared to the fixed shortest-path first (SPF) and other dynamic algorithms.

Some current Internet applications (e.g., Grid/Cloud computing storage, video-conference) demand service differentiation, not only in terms of packet forwarding, but also at the connection level. To satisfy the demands for delay-sensitive and low-blocking applications, immediate reservation (IR) and advance reservation (AR) can be performed. Independent resource reservation of each type of network resources is well-investigated. Nevertheless, it is very likely that both types of requests will need to share network resources. There is also significant demand for a service framework that is able to provide application-aware quality of service (QoS). By using existing scheduling algorithms for IR/AR, we develop a service framework to guarantee relative QoS among different application requests, with and without tolerance to delay and service blocking. Simulation results demonstrate the feasibility of our approach and provide a basis for future development of enhanced IR/AR QoS policies within the control plane of future high-speed networks.

Future optical communication networks are expected to change radically during the next decade. To meet the demanded bandwidth requirements, more dynamism, scalability and automatism will need to be provided. This will also require addressing issues such as the design of highly distributed control plane systems and their associated algorithms to respond to network changes very rapidly. In this work, we propose the use of an ant colony optimization (ACO) algorithm to solve the intrinsic problem of the routing and wavelength assignment (RWA) on wavelength continuity constraint optical networks. The main advantage of the protocol is its distributed nature, which provides higher survivability to network failures or traffic congestion. The protocol has been applied to a specific type of future optical network based on the optical switching of bursts. It has been evaluated through extensive simulations with very promising results, particularly on highly congested scenarios where the load balancing capabilities of the protocol become especially efficient. Results on a partially meshed network like NSFNET show that the ant-based protocol outperforms other RWA algorithms under test in terms of blocking probability without worsening other metrics such as mean route length.

The amount of bursty Internet traffic leads to develop new architectures and technologies, such as Optical Burst Switching (OBS), to efficiently satisfy future bandwidth requirements. Burst loss probability is an important quality of service metric for OBS due to its bufferless characteristic, even