Long Gong

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.

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.

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.

Dynamic Multi-Path Service Provisioning under Differential Delay Constraint in Elastic Optical Networks

Optical orthogonal frequency-division multiplexing (O-OFDM) technology has the elastic feature of allocating spectrum resources based on subcarrier slots with bandwidths at a few GHz or even narrower. This feature enables us to utilize link capacity more efficiently by splitting a connections traffic over multiple routing paths. In this paper, we propose a novel dynamic multi-path provisioning algorithm for O-OFDM based elastic optical networks. The algorithm tries to set up dynamic connections with single-path routing in a best-effort manner. When a connection cannot be served with a single routing path, the algorithm uses an auxiliary-graph based approach to calculate a multi-path provisioning scheme based on two parameters, i.e., the differential delay upper-bound and the bandwidth allocation granularity. Simulation results indicate that compared with several existing single-path provisioning algorithms, the proposed algorithm provides lower bandwidth blocking probability and achieves 10-18% improvement on average network throughput.

Dynamic transparent virtual network embedding over elastic optical infrastructures

We propose a novel dynamic transparent virtual network embedding (VNE) algorithm, which considers node mapping and link mapping jointly, for network virtualization over optical orthogonal frequency-division multiplexing (O-OFDM) based elastic optical infrastructures. For each virtual optical network (VON) request, the algorithm first transfers the substrate optical network into a layered-auxiliary-graph according to the spectrum usage of each fiber link, then applies a node mapping approach that considers the local information of all substrate nodes, and accomplishes the link mapping, in a single layer of the auxiliary graph. The simulation results verify that the proposed algorithm considers the uniqueness of O-OFDM networks and outperforms two reference algorithms that directly apply the VNE schemes developed for Layer 2/3 or WDM network virtualization, by providing lower VON blocking probability. The simulations with a realistic topology also demonstrate that the average lengths of embedded substrate paths are well-controlled within the typical transmission reaches of O-OFDM signals. To the best of our knowledge, this is the first proposal that includes both link mapping and node mapping to address dynamic transparent VNE over elastic optical infrastructures.

Dynamic RMSA in elastic optical networks with an adaptive genetic algorithm

We develop an adaptive and efficient genetic algorithm (GA) to solve the dynamic routing, modulation and spectrum assignments (RMSA) for elastic O-OFDM networks. The algorithm offers an efficient way of serving the dynamic lightpath requests based on the current network status at each service provision time. The GA is designed for multi-objective optimization. For low traffic cases when there is no blocking, the GA minimizes the maximum number of slots required on any fiber in the network; otherwise, it minimizes the blocking probability. The performance of the proposed GA is evaluated in dynamic RMSA simulations with the 14-node NSFNET and the 28-node US Backbone topologies, and the results show that it converges within 25 generations. The simulation results also verify that the GA-RMSA outperforms several existing algorithms by providing more load-balanced network provisioning solutions with lower blocking probabilities. Specifically, when the traffic load is same, the GA can achieve more than one order-of-magnitude reduction on blocking probability. To the best of our knowledge, this is the first attempt to solve dynamic RMSA in elastic O-OFDM networks with a GA.

Joint defragmentation of optical spectrum and IT resources in elastic optical datacenter interconnections

With its agile spectrum management in the optical layer, the flexible-grid elastic optical network can become a promising physical infrastructure to efficiently support the highly dynamic traffic in future datacenter interconnections (DCIs). While the resulting elastic optical DCIs (EO-DCIs) need to serve requests that not only require bandwidth resources on fiber links but also require multidimensional IT resources in the DCs, multidimensional resource fragmentation can occur during dynamic network operations and deteriorate the network performance. To address this issue, this paper investigates the problem of joint defragmentation (DF) for the spectrum and IT resources in EO-DCIs. Specifically, we reoptimize the allocations of multidimensional resources jointly with complexity-controlled network reconfigurations. For the DFoperation, we first study the request selection process and propose a joint selection strategy that can perform the spectrum- and IT-oriented selections adaptively according to the network status. Then, we formulate a mixed integer linear programming model and design several heuristics to tackle the problem of network reconfiguration in the joint DF. The proposed algorithms are evaluated with extensive simulations. Simulation results demonstrate that the proposed joint DF algorithms can significantly reduce the blocking probability in EO-DCIs by consolidating the spectrum and IT resource usages effectively.

On Fast and Coordinated Data Backup in Geo-Distributed Optical Inter-Datacenter Networks

In an optical inter-datacenter (inter-DC) network, for preventing data loss, a cloud system usually leverages multiple DCs for obtaining sufficient data redundancy. In order to improve the data-transfer efficiency of the regular DC backup, this paper investigates fast and coordinated data backup in geographically distributed (geo-distributed) optical inter-DC networks. By considering a mutual backup model, in which DCs can serve as the backup sites of each other, we study how to finish the regular DC backup within the shortest time duration (i.e., DC backup window (DC-B-Wnd)). Specifically, we try to minimize DC-B-Wnd with joint optimization of the backup site selection and the data-transfer paths. An integer linear programming (ILP) model is first formulated, and then we propose several heuristics to reduce the time complexity. Moreover, in order to explore the tradeoff between DC-B-Wnd and operational complexity, we propose heuristics based on adaptive reconfiguration (AR). Extensive simulations indicate that among all the proposed heuristics, AR-TwoStep-ILP achieves the best tradeoff between DC-B-Wnd and operational complexity and it is also the most time-efficient one.

Design integrated RSA for multicast in elastic optical networks with a layered approach

In this paper, we incorporate a layered approach to design integrated multicast-capable routing and spectrum assignment (MC-RSA) algorithms for achieving efficient all-optical multicasting in spectrum-sliced elastic optical networks (EONs), which are based on the optical orthogonal frequency-division multiplexing (O-OFDM) technology. For each multicast request, the proposed algorithms decompose the physical topology into several layered auxiliary graphs according to the network spectrum utilization. Then, based on the requests bandwidth requirement, we select a proper layer and calculate a multicast light-tree within it. With these procedures, the routing and spectrum assignment (RSA) for each multicast request is done in an integrated way. We evaluate the proposed algorithms in simulations of static network planning and dynamic network provisioning. The simulation results demonstrate that compared to the existing MC-RSA algorithms, our approaches achieve more efficient network planning in terms of spectrum utilization, and provide lower blocking probabilities in network provisioning.