The Department of Energy (DOE) supports scientific collaboration in six program areas, ranging from nuclear physics, to biological and environmental research. To enable these data intensive large scale collaborations, the Energy Sciences Network (ESnet) is used to move upwards of 50 Petabytes a month between sites within the US and Europe. Bandwidth within ESnet can be requested, reserved, and utilized through the On-demand Secure Circuits and Advance Reservation System (OSCARS), which provisions network resources with guaranteed bandwidth over a known reservation schedule. Traditionally, OSCARS has only supported simple point-to-point connections between endpoints (e.g. universities, research laboratories), which has limited how efficiently the network may be harnessed by users. This paper details recent extensive enhancements prototyped for OSCARS, to be incorporated into a future release, which enable users to select novel service types including survivability, asymmetric bandwidth or routes, and anycast/manycast. We quantitatively compare several of these enhancements to the baseline point-to-point service, and find that the new services provide not only greater flexibility for the end-user, but savings for network administrators in terms of blocking and network resource usage as well.

Optical wavelength-routed networks enable parallel transmission of massive datasets on non-overlapping wavelength channels. However, as the sizes of scientific workflows increase, the simple availability of multi-wavelength resources will fall short of supporting application needs. Rather, these resources must be allocated intelligently, efficiently, and flexibly to bear the burden of high-volume science. We propose time-slotted wavelength-switching to support modifying the wavelength that carries a lightpath throughout its lifetime, exposing flexible consumption of available resources during the request schedule. We explore the efficacy of wavelength-switching in combination with adaptive path selection flexibility and attempt to approach previously determined optimality benchmarks. Results from quantitative evaluations show tremendous savings opportunity via wavelength-switching support, and indicate that efficient invocation of spectral flexibility in this manner may even be more impactful than spatial flexibility on network-wide performance.

Recent trends in science applications call for long-range and large-scale collaboration among laboratories and super-computing sites. Long gone are the days of entering data manually into a spreadsheet on a local workstation. The world's most powerful and ground-breaking experiments generate exabytes of information, which must be distributed to multiple labs for analysis and interpretation. Such trends reveal the unwavering importance of new communication paradigms, like multicasting and manycasting, which provide point-to-multipoint data transfers. Typically, these all-important mechanisms are provided at the optical layer, where split-capable cross-connects split input signals into multiple output signals all-optically. Unfortunately, some of the world's largest and most powerful networks do not have the hardware infrastructure to support such functionality, but allow for point-to-point communication exclusively. In such split-incapable (SI) networks, multicast and manycast must be provided as a logical overlay to the pre-existing and limited unicast infrastructure. In this paper, we present two overlay models for providing manycast support in SI networks: Manycasting with Drop at Member Node (MA-DMN) and Manycasting with Drop at Any Node (MA-DAN). Through the development of integer linear programs (ILPs) and heuristics, we evaluate these models in terms of both optimal solutions and efficient approximations for both small-scale and large-scale networks and consider both static and dynamic traffic scenarios. Our results demonstrate that despite a small tradeoff in additional complexity and delay from signal conversion to the optical domain, our models provide efficient utilization of network resources and greatly surpass the standard naive approach of establishing paths to every destination.

Critical data transmissions are often scheduled hours or days in advance of the actual acquirement of network resources, allowing for efficient allocation and scheduling among a set of competing or temporally overlapping lightpath demands. Many periodic applications may not only desire service at some future time, but may further require repeatable and predictable scheduling services. Typically, such application demands are deadline-driven and therefore mutable within some sliding window depending on congestion, competition, or load. This paper considers Sliding Scheduled Lightpath Establishment (SSLE) in time-slotted optical networks and enhances scheduling by incorporating spectral flexibility at wavelength/time-slot granularity. A novel wavelength-switching integer linear program and two conservative heuristics are presented to describe and evaluate the SSLE problem under various degrees of temporal conflict and flexibility.

Resources in a network are imperfect, and equipment failure can have detrimental effects on data and transmission success rates. Attempts to improve the survivability of network communications when these failures occur focus primarily on protection against the common occurrence of link failures, while nodal failure has been largely overlooked. In data-critical infrastructures, such as cloud computing or data center networks, wherein the critical points of interest are at the nodes, a natural disaster or directed attack could have catastrophic consequences for the localized data. To overcome single points of failure, replicated multicast transmissions can be used to distribute copies of critical data to various geographically dispersed locations on the grid. We therefore explore strategies to protect against single critical node failures during multicast transmissions. We propose three novel multicast survivable heuristics and quantitatively analyze and then compare them to traditional multicast provisioning schemes through extensive simulation1.

Manycasting allows a single source to reach multiple destinations while providing flexibility in destination selection. Our goal in this paper is to improve the cost of the manycast drop at member node (MA-DMN) overlay algorithm in terms of energy consumption and associated greenhouse gas (GHG) emissions. To reduce the environmental impact, ideally, a large percentage of the network nodes along the transmission and the chosen destinations need to be green. We present a novel energy-conservative emission-aware variant of the MA-DMN algorithm. We then propose further modifications to increase the utilization of those destinations that are powered by renewable energy sources: manycast drop at greenest nodes (MA-DGN). The potential for emission reduction by those algorithms is two-fold: The data are transported in the most efficient way and processed at the greenest available data centers. We compare the approaches by simulating realistic quantities of dynamic traffic. We assume heterogeneously distributed and time-dependent availability of renewable energy sources to power nodes throughout the network. We find that the energy-source-aware algorithms lower both energy-consumption and GHG emissions at stable network performance levels, in some cases even lowers blocking rate.

Manycasting is an emerging communication paradigm which allows a single source to reach multiple destinations while providing flexibility in the selection of which destinations to connect with. Traditional wavelength division multiplexed (WDM) networks do not support the all-optical splitting of signals to multiple output ports as required by point-to-multipoint communication schemes. Previous work has proposed an overlay approach known as Manycasting with Drop at Member Node (MA-DMN) to provide manycast support as a logical overlay to basic point-to-point lightpath connections. This approach has been studied extensively and compared to alternative overlay models, and has emerged the obvious candidate for supporting manycast overlays. Throughout its evaluation though, MA-DMN has never been scrutinized in terms of its costs for energy consumption and associated greenhouse gas (GHG) emissions. In this work, we subject MA-DMN to these evaluations, while also proposing a new more energy-conservative emission-aware variant known as MA-DMN using Least Impact Trees (MA-DMN-LIT). We compare these two approaches by simulating realistic quantities of dynamic traffic, and uniformly distributing renewable energy sources to power nodes throughout the network. We find that MA-DMN-LIT reduces energy consumption over MA-DMN by 6-10% across the network, while also reducing CO2emissions by as much as 27%. We further conclude that MA-DMN-LIT also provides lower connection blocking by not over-subscribing shorter paths in the network as its emission-blind counterpart does.

Traditionally in wavelength division multiplexed (WDM) networks, multicasting is accomplished by splitting the signals all-optically, thereby establishing a tree of lightpaths (light-tree) from the source to every destination. To provision for this functionality in a Multicast-Incapable environment, in which the switches are not capable of directing an incoming signal to more than one output interface, one must implement a logical multicast overlay to the underlying optical layer. A naive method of accomplishing this is by creating a set of unicast lightpaths from the source to each destination of the multicast request. However, for large multicast groups, this leads to a poor utilization of the network resources. To alleviate this problem, we present two multicast Steiner tree overlay alternatives: Multicast with Drop At Member Node (DAMN), in which a lightpath may only terminate at member nodes of the multicast request, and Multicast with Drop At Any Node (DAAN), in which lightpaths may terminate at any node in the physical topology. We consider a dynamic traffic model, and propose efficient heuristics to solve the DAMN and DAAN problems with a goal of minimizing the total number of wavelengths required to satisfy the request. Moreover, we present a simple heuristic to approximate the baseline unicast approach (naive method). Our results demonstrate that at various loads, both the DAMN and DAAN reduce wavelength consumption by 42 - 60% over the naive unicast approach in realistic networks.

With the increasing number of high-bandwidth applications, energy consumption of networks has become an important issue that needs to be addressed. Manycasting is a communication paradigm that finds applications in such high-bandwidth environments. To support manycasting functionality in an optical network that is Split-Incapable (SI), i.e., the optical cross connects are incapable of switching an incoming optical signal to more than one output interface, manycasting must be implemented as an overlay to the optical layer. We propose two such overlay approaches: Manycasting with Drop at Member Node (MA-DAMN) and Manycasting with Drop at Any Node (MA-DAAN) which employ Steiner tree routing. We subject these approaches to a static traffic model, and present integer linear programs (ILPs) and heuristic approximations which aim to minimize the total number of wavelengths required to service the manycast request set in an effort to reduce network-wide energy consumption. Through extensive simulation, we show that MA-DAMN and MA-DAAN achieve 25-45% wavelength reduction as compared to a baseline overlay approach which employs single-hop lightpaths to each manycast destination individually.