Zuqing Zhu

Efficient resource allocation for all-optical multicasting over spectrum-sliced elastic optical networks

Recently, optical orthogonal frequency-division multiplexing technology has attracted intensive research interest because spectrum-sliced elastic optical networks (EONs) can be constructed based on it. In this paper, we investigate how to serve multicast requests over EONs with multicast-capable routing, modulation level, and spectrum assignment (RMSA). Both EON planning with static multicast traffic and EON provisioning with dynamic traffic are studied. For static EON planning, we formulate two integer linear programming (ILP) models, i.e., the joint ILP and the separate ILP. The joint ILP optimizes all multicast requests together, while the separate ILP optimizes one request each time in a sequential way. We also propose a highly efficient heuristic that is based on an adaptive genetic algorithm (GA) with minimum solution revisits. The simulation results indicate that the ILPs and the GA provide more efficient EON planning than the existing multicast-capable RMSA algorithms that use the shortest path tree (SPT) and the minimal spanning tree (MST). The results also show that the GA obtains more efficient EON planning results than the separate ILP with much less running time, as it can optimize all multicast requests together in a highly efficient manner. For the dynamic EON provisioning, we demonstrate that the GA is also applicable, and it achieves lower request blocking probabilities than the benchmark algorithms using SPTand MST.

Spectral and spatial 2D fragmentation-aware routing and spectrum assignment algorithms in elastic optical networks [invited]

This paper investigates the spectrum fragmentation issue, which undermines the bandwidth efficiency in elastic optical networks. After categorizing the two-dimensional fragmentation problem as the fragmentation and misalignment subproblems, this paper proposes joint routing and spectrum assignment (RSA) algorithms to alleviate the spectral fragmentation in the lightpath provisioning process. The time complexity of the two proposed algorithms are analyzed in detail, and both algorithms can run in 0(kdnC log C) time, where k is the number of the shortest path in the routing algorithm, d is the maximum node degree in the network, n is the number of nodes in the network, and C is the link capacity expressed as the number of spectral slots. Simulation results indicate that the proposed fragmentation-aware (FA) RSA algorithm and the FA algorithm with congestion avoidance (CA) outperform the existing schemes in terms of blocking probability (BP) reduction. Compared with the benchmark K-shortest-path routing and first-fit assignment (KSP-FF) algorithm, the proposed FA and FA-CA algorithms can achieve a BP reduction of [100%, 4.43%] and [100%, 6.45%], respectively, according to the traffic load in a sample NSFNET topology.

A Two-Population Based Evolutionary Approach for Optimizing Routing, Modulation and Spectrum Assignments (RMSA) in O-OFDM Networks

We propose a novel two-population genetic algorithm (MPGA) to optimize the routing, modulation and spectrum assignments (RMSA) in optical orthogonal frequency-division multiplexing (O-OFDM) networks. The proposed MPGA makes two populations evolve in parallel with different selection and mutation strategies, and incorporates a migration operation to exchange individuals between them. Performance evaluations show that the MPGA outperforms several existing algorithms.

Toward profit-seeking virtual network embedding algorithm via global resource capacity

In this paper, after proposing a novel metric, i.e., global resource capacity (GRC), to quantify the embedding potential of each substrate node, we propose an efficient heuristic virtual network embedding (VNE) algorithm, called as GRC-VNE. The proposed algorithm aims to maximize the revenue and to minimize the cost of the infrastructure provider (InP). Based on GRC, the proposed algorithm applies a greedy load-balance manner to embed each virtual node sequentially, and then adopts the shortest path routing to embed each virtual link. Simulation results demonstrate that our proposed GRC-VNE algorithm achieves lower request blocking probability and higher revenue due to the more appropriate consideration of the resource distribution of the entire network, when compared to the two lastest VNE algorithms that also consider the resources of entire substrate network. Then, we introduce a classical reserved cloud revenue model, which consists of fixed revenue and variable one. Based on this revenue model, we design a novel admission control policy selectively accepting the VNR with high revenue-to-cost ratio to maximize the InPs profit based on an empirical threshold. Through extensive simulations, we observe that the optimal empirical threshold is proportional to the ratio of variable revenue to the fixed one.

RF photonics signal processing in subcarrier multiplexed optical-label switching communication systems

This paper provides theoretical and experimental studies of radio-frequency (RF) photonics processing techniques applicable in subcarrier-multiplexed optical-label switching (OLS) communications systems. The paper provides an overview of various label-coding technologies and introduces subcarrier multiplexing (SCM) as an attractive technology for OLS networks. All-optical-label extraction using optical filters, such as fiber Bragg gratings (FBGs), provides an effective means to demodulate the SCM labels without inducing RF fading effects caused by fiber dispersion. Furthermore, the role of fiber nonlinearities in the RF fading effects are theoretically and experimentally verified. The all-optical label extraction and rewriting processes constitute optical-label swapping, wherein 2R data regeneration can take place. Scalable and cascadable OLS systems are feasible by applying viable RF photonics technologies in all-optical-label processing.

Dynamic and Adaptive Bandwidth Defragmentation in Spectrum-Sliced Elastic Optical Networks With Time-Varying Traffic

Elastic optical networks (EONs) enable network operators to have agile bandwidth management in the optical layer. In this paper, we investigate dynamic and adaptive bandwidth defragmentation (DF) in EONs with time-varying traffic using connection reconfigurations. We consider how to design DF procedure in a systematic way, and study the problems that have not been fully explored so far. Basically, we divide the procedure design into four subproblems: “How to reconfigure?,” “ How to migrate traffic?,” “When to reconfigure?,” and “What to reconfigure?,” and solve them sequentially. For “How to reconfigure?,” we investigate the combination of routing and spectrum assignment (RSA) algorithms for DF, i.e., the RSA algorithm that the connections are originally served with and the algorithm that they are re-optimized with. For “ How to migrate traffic?,” we propose to construct a dependency graph to represent the relations among the selected connections and to use it to assist the best-effort traffic migration. A move-to-vacancy method is also proposed to further reduce the traffic disruptions. For “When to reconfigure?” and “ What to reconfigure?,” we propose intelligent timing selection and adaptive DF ratio selection methods to tackle the tradeoff between the bandwidth blocking probability (BBP) performance and operational complexity. Simulation results show that the algorithm with both methods implemented (DF-AT-AR) achieves better tradeoff between BBP performance and operational complexity, when compared with existing algorithms.

Fragmentation-aware routing, modulation and spectrum assignment algorithms in elastic optical networks

We investigate the principle of how dynamic service provisioning fragments the spectral resources on links along a path, and propose corresponding RMSA algorithms to alleviate spectrum fragmentation in dynamic network environments.

Bandwidth defragmentation in dynamic elastic optical networks with minimum traffic disruptions

Bandwidth defragmentation, i.e., the operation to reconfigure existing connections for making the spectrum usage less fragmented and less misaligned, has recently been recognized as one of the most important features for elastic optical networks (EONs). In this paper, we propose a novel comprehensive bandwidth defragmentation algorithm that considers the problems of 1) When to defragment? 2) What for defragment? and 3) How to defragment? jointly. The proposed algorithm accomplishes defragmentation through proactive network reconfiguration that only reroutes a portion of existing connections. In each defragmentation operation, we first choose the connections to reroute using a selection strategy, then determine how to reroute them with the defragmentation based routing and spectrum assignment (DF-RSA), and finally perform rerouting with best-effort traffic migration to minimize traffic disruptions. Simulation results indicate that in order to make the bandwidth blocking probability (BBP) comparable with that from the Greenfield scenario (100% rerouting all the time), the proposed algorithm only needs to reroute ~30% existing connections. The simulations also demonstrate that the traffic disruption percentages are less than 1% for defragmentations with 30% rerouting and can be further reduced to within 0.25% by adding a move-to-vacancy (MTV) approach in the traffic migration.

Design QoS-Aware Multi-Path Provisioning Strategies for Efficient Cloud-Assisted SVC Video Streaming to Heterogeneous Clients

We layout a network infrastructure that leverages the storage and computing power of a cloud residing in the core for collecting network status and computing multi-path scalable video coding (SVC) streaming provisioning strategies. Therefore, in addition to its conventional tasks in the application layer, the cloud also gets involved in the network layer for the optimization of routing and forwarding. We call this scheme as cloud-assisted SVC streaming, and use it to further improve the performance of SVC streaming by using close cooperation between cloud and network. Compared to source-routing based provisioning, the cloud-assisted scheme can provide more cost-effective provisioning strategies by utilizing better knowledge of network environment together with more powerful computation power. We then propose several multi-path provisioning algorithms for cloud-assisted SVC streaming in heterogeneous networks. To the best of our knowledge, these are the first proposals to work on the problem of adaptive multi-path SVC streaming under the bandwidth, delay and differential delay constraints. Our design of the provisioning algorithms starts from an approach that is based on Max Flow and an Auxiliary Graph. Several extensions are then made based on this approach to address the situations such as provisioning from multiple sources and provisioning in dynamic network environments with rapid background traffic fluctuations. Simulations in both static and dynamic network environments show that the proposed algorithms can achieve effective performance improvements in terms of request blocking probability, bandwidth utilization, packet delay, packet loss rate, and video playback quality.

10 000-hop cascaded in-line all-optical 3R regeneration to achieve 1 250 000-km 10-Gb/s transmission

We demonstrate 1 250 000-km 10-Gb/s return-to-zero transmission over 10 000 stages of in-line all-optical reamplification, reshaping, and retiming (3R) regeneration spaced every 125 km. The all-optical 3R regenerator incorporates a 10-GHz all-optical clock recovery module including a Fabry-Pe/spl acute/rot filter and a semiconductor optical amplifier in a cascaded configuration for fast and stable response. Bit-error-rate (BER) performance measurements show less than 0.7-dB power penalty at the BER of 10/sup -9/ between 1 250 000- (Lap 10 000) and 125-km (Lap 1) transmission using pseudorandom bit sequence 2/sup 23/-1.