It is becoming increasingly clear that a clean-slate architectural design of the network protocol stack is an essential target for next-generation IP networks and network routing applications. A major challenge in realizing the required enhanced capabilities in next-generation networks lies in overcoming the current limitations due to the rigid notion of network layering. To address the research agenda of future networking infrastructures, our goal is to achieve a cross-layer communication infrastructure to provide bidirectional information exchange between layers. Enabling programmable interaction with the optical substrate will allow the higher layers dynamic access to the full optical bandwidth. Our goal is to create an intelligent, dynamic, programmable, network and application layer aware optical substrate, where data introspection and optical performance monitoring measurement data can be leveraged for cross-layer communications to impact network routing and performance.
Challenges facing the access and core networks stem from the rapidly growing number of users and applications that demand dynamic reconfigurability in a highly aggregated network environment. CIAN, an NSF-funded Engineering Research Center (ERC), is a multi-university collaboration to address the bottleneck in the access network. Our role as part of the networking Thrust is to create a seamless high-bandwidth optical equivalent of the access network with cross-layer capabilities. The full endeavor includes developing a programmable and flexible platform for cross-layer information exchange and optimization based on an optical network test-bed. Modifications to the basic buffer architecture have allowed for the experimental implementation of an optical network interface buffer, realizing a control plane interface that transparently processes multi-wavelength optical messages and reconfigures the optical switching fabric to instantiate the lightpath topology. The interoperability between the implemented interface buffer and network test-bed demonstrates dynamic queue management and cross-layer signaling.
Our CIAN Thrust also drives the development of networking functionalities within the CIAN test-bed, such as programmable high-bandwidth multicasting. The network test-bed architecture has been uniquely adapted to support future cross-layer communication capabilities.
Global Environment for Network Innovations (GENI) is a NSF research agenda for clean-slate Internet design, experimentation, and collaboration to support experimental research in network science and engineering. The scope of our GENI project Embedded Real-Time Measurements (ERM) specifically ensures that the future GENI network infrastructure includes the appropriate technology to support cross-layer communications. By collaborating with other control frameworks, we endeavor to realize the ability within GENI to incorporate a diverse set of real-time measurements in networking protocols. The project addresses the GENI challenge of architectural experimentations across diverse heterogeneous technologies by supporting real-time cross-layer communications and measurements. Our objective is to develop networking capabilities within the future GENI infrastructure that enable deeper exposure of cross-layer information and user access to real-time measurements.
Within this project, we have developed a set of GENI requirements for real-time measurements and defined specifications for GENI networking protocols, recommending the use of an integrated, unified measurement framework. In addition, our project involves performing discrete-event simulations of cross-layer based networks in ns-2 and OPNET. Current work involves the experimental verification of these concepts.
This effort aims to address the detrimental communications constraints imposed by bandwidth density limitations and vastly growing power consumption of current electronically interconnected systems. We aim to develop a design for the optical interconnection network architecture for a cluster scale system - leading to a datacenter interconnection network design. We leverage our existing system-level simulation environment (PhoenixSim) to obtain energy-performance data movement analysis and optimization for scalable data center systems under diverse workloads and using specific traces and benchmarks. We address the datacenter application challenge with APICs FLIP (Fully Laser Integrated Processor) and HIP(Highly Integrated Photonics) program research.