US Ignite

Distributed smart and connected community applications of the present and future will continuously sense perishable data on which they make decisions. We say the data are perishable when they represent information sensed at a past point in time, possibly at a distant part of the distributed application, and for which the ground truth could have since changed. This paper discusses actions the sensing source, the network, and the controller can take to make the best possible decisions given that we know only a delayed version of the truth. Some of these actions to preserve freshness of data are based on known real-time techniques such as Time Sensitive Networking. To these we add Information Theory applied on a message-by-message basis and cross-layer coordination between content and network handling. Both the unexpectedness (surprisal) and timeliness (freshness) properties of perishable information can be encoded using a Shannon information entropy framework. Examples of smart community systems of the future for which these concepts are relevant are given.

EdgeNet has been informed by the advances of cloud computing and the successes of such distributed systems as PlanetLab, GENI, G-Lab, SAVI, and V-Node: a large number of small points-of-presence, designed for the deployment of highly distributed experiments and applications. EdgeNet differs from its predecessors in two significant areas: first, it is a software-only infrastructure, where each worker node is designed to run part-or full-time on existing hardware at the local site; and, second, it uses modern, industry-standard software both as the node agent and the control framework. The first innovation permits rapid and unlimited scaling: whereas GENI and PlanetLab required the installation and maintenance of dedicated hardware at each site, EdgeNet requires only a software download, and a node can be added to the EdgeNet infrastructure in 15 minutes. The second offers performance, maintenance, and training benefits; rather than maintaining bespoke kernels and control frameworks, and developing training materials on using the latter, we are able to ride the wave of open-source and industry development, and the plethora of industry and community tutorial materials developed for industry standard control frameworks. The result is a global Kubernetes cluster, where pods of Docker containers form the service instances at each point of presence.

We describe OpenFlow, a first step on the road to networks which are fully integrated into the IT infrastructure ecosystem. We review the history of OpenFlow, its precursors, its design and initial implementations. We discuss its use within the GENI project and the applications and services developers have built on the OpenFlow platform. Finally, we review the implementation issues with OpenFlow, and consider extensions and the next generation of Software-Defined Networking.

We describe the GENI Experiment Engine, a Distributed-Platform-as-a-Service facility designed to be implemented on a distributed testbed or infrastructure. The GEE is intended to provide rapid and convenient access to a distributed infrastructure for simple, easy-to-configure experiments and applications. Specifically, the design goal of the GEE is to permit experimenters and application writers to: (a) allocate a GEE slicelet; (b) deploy a simple experiment or application; (c) run the experiment; (d) collect the results; and (e) tear down the experiment, starting from scratch, within five minutes. The GEE consists of four cooperating services over the GENI infrastructure, which together with pre-allocated slicelets and a pre-allocated network offers a complete, ready to use, sliceable platform over the GENI Infrastructure.

US Ignite is catalyzing the development of 60 next-generation applications that take advantage of advanced network services such as ultra-fast broadband. This paper discusses relevant advanced network services and gives examples of new applications they make feasible.