Access to fiber-optic connectivity in the Internet is traditionally offered either via lit circuits or dark fiber. Economic (capex vs. opex) and operational considerations (latency, capacity) dictate the choice between these two offerings, but neither may effectively address the specific needs of modern-day enterprises or service providers over a range of use scenarios. In this paper, we describe a new approach for fiber-optic connectivity in the Internet that we call GreyFiber. The core idea of GreyFiber is to offer flexible access to fiber-optic paths between end points (e.g., datacenters or colocation facilities) over a range of timescales. We identify and discuss operational issues and systems challenges that need to be addressed to make GreyFiber a viable and realistic option for offering flexible access to infrastructure (similar to cloud computing). We investigate the efficacy of GreyFiber with a prototype implementation deployed in the GENI and CloudLab testbeds. Our scaling experiments show that 50 circuits can be provisioned within a minute. We also show that backup paths can be provisioned 28 times faster than an OSPF-based solution during failure maintenance events. Our experiments also examine GreyFiber overhead demands and show that the time spent in circuit creation is dependent on the network infrastructure, indicating avenues for future improvements.
        Optical transport networks typically deploy dynamic restoration mechanisms in order to automatically recover optical connections disrupted by network failures. Elastic optical networks (EONs), currently emerging as the next-generation technology to be adopted in optical transport, introduce new challenges for traditional generic multiprotocol label-switching (GMPLS)-based restoration that may seriously impact the achievable recovery time. At the same time, the software-defined networking (SDN) framework is emerging as an alternative control plane. It is therefore important to investigate possible benefits provided by SDN in the implementation of restoration mechanisms for EONs. This paper proposes a dynamic restoration scheme for EONs based on the SDN framework. The proposed scheme contemporarily exploits centralized path computation and node configuration to avoid contentions during the recovery procedure with the final aim of minimizing the recovery time. The performance of the proposed scheme is evaluated by means of simulations in terms of recovery time and restoration blocking probability and compared against three reference schemes based on GMPLS and SDN. Fiber optic cables are the workhorses of today's Internet services. Operators spend millions of dollars to purchase, lease and maintain their optical backbone, making the efficiency of fiber essential to their business. In this work, we make a case for adapting the capacity of optical links based on their signal-to-noise ratio (SNR). We show two immediate benefits of this by analyzing the SNR of over 2000 links in an optical backbone over a period of 2.5 years. First, the capacity of 80 of IP links can be augmented by 75 or more, leading to an overall capacity gain of 145 Tbps in a large optical backbone in North America. Second, at least 25 of link failures are caused by SNR degradation, not complete loss-of-light, highlighting the opportunity to replace link failures by link flaps wherein the capacity is adjusted according to the new SNR. Given these benefits, we identify the disconnect between current optical and networking infrastructure which hinders the deployment of dynamic capacity links in wide area networks (WANs). To bridge this gap, we propose a graph abstraction that enables existing traffic engineering algorithms to benefit from dynamic link capacities. We evaluate the feasibility of dynamic link capacities using a small testbed and simulate the throughput gains from deploying our approach.  Software defined networking in the optical physical layer is complicated by transmission control used to both optimize performance and stabilize optical signals across multiple nodes. Different approaches are emerging to address these problems. We present the design, implementation, and evaluation of B4, a private WAN connecting Google's data centers across the planet. B4 has a number of unique characteristics: i) massive bandwidth requirements deployed to a modest number of sites, ii) elastic traffic demand that seeks to maximize average bandwidth, and iii) full control over the edge servers and network, which enables rate limiting and demand measurement at the edge. These characteristics led to a Software Defined Networking architecture using OpenFlow to control relatively simple switches built from merchant silicon. B4's centralized traffic engineering service drives links to near 100 utilization, while splitting application flows among multiple paths to balance capacity against application priority demands. We describe experience with three years of B4 production deployment, lessons learned, and areas for future work.    Paradoxically, with an ever-increasing traffic demand, today transport-network operators experience a progressive erosion of their margins. The alarms of change are set, and software define networking (SDN) is coming to the rescue with the promise of reducing capital expenditures and operational expenses. Driven by economic needs and network innovation facilities, today transport SDN (T-SDN) is a reality. It gained big momentum in the last years, however, in the networking industry, the transport network will be perhaps the last segment to embrace SDN, mainly due to the heterogeneous nature and complexity of the optical equipment composing it. This survey guides the reader through a fascinating technological adventure that provides an organic analysis of the T-SDN development and evolution considering contributions from: academic research, standardization bodies, industrial development, open source projects, and alliances among them. After creating a comprehensive picture of T-SDN, we provide an analysis of many open issues that are expected to need significant future work, and give our vision in this path toward a fully programmable and dynamic transport network.