Changes between Version 29 and Version 30 of GEC22Agenda/EveningDemoSession


Ignore:
Timestamp:
01/30/15 16:17:33 (9 years ago)
Author:
peter.stickney@bbn.com
Comment:

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  • GEC22Agenda/EveningDemoSession

    v29 v30  
    7979==== GENI Cinema ====
    8080
     81This demo shows how OpenFlow can be used in GENI to create a live video streaming service for the reception, hosting, routing, and transmission of live video streams.
     82
     83Who should see this demo?
     84
     85Attendees interested in OpenFlow/SDN use-cases and those interested in video streaming and content delivery.
     86
    8187Video streaming over the Internet, be it static or live streaming, is rapidly increasing in popularity. Many video streaming services exist to serve a variety of needs, such as video conferencing, entertainment, education, and the broadcast of live events. These services rely heavily on the server application to adapt to increasing and decreasing demand for a particular video resource. Furthermore, they require the reallocation of resources and the restart of the stream when a client stops, starts, and/or switches to a different stream. SDN (Software-Defined Networking) and specifically OpenFlow can be creatively used to reallocate some of these tasks to the network and link layers.
    8288
     
    102108==== PrimoGENI ====
    103109
     110This demo shows a working prototype of MyExperiment?, a full-functioning public online model repository for PrimoGENI.
     111
     112Who should see this demo?
     113
     114Attendees interested in conducting network experiments combining simulation and emulation on GENI.
     115
    104116PrimoGENI allows hybrid network experiments consisting of simulated and emulated network entities. Each PrimoGENI experiment consists of a model of a virtual network, which includes the specification of the network topology with detailed configuration of network entities, and possible specification of background network traffic. !MyExperiment is an online repository, where experimenters can create, view, and modify network models; one can also publish network models and share experiment results with the user community. !MyExperiment contains plugins for various network topology and traffic generators. !MyExperiment manages network models created by each user and supports translation between different formats. Users can publish their models and share experiment results to facilitate model reuse and validation.
    105117
     
    108120
    109121==== Enhancing an OpenFlow Network with Service Insertion and Payload Inspection ====
     122
     123This demo shows a working prototype of an application aware video reconditioning service.
     124
     125Who should see this demo?
     126
     127Attendees interested in introducing a variety of value-added network services into their networks, such as context-sensitive service for prioritizing public safety applications or a security service that detects and eliminates malware embedded in unwary user traffic.
    110128
    111129Today, due to volatile and exploding traffic demands, ISPs need to update their deployed network resources almost continuously, but it is costly to provision increasingly faster and specialized network devices. The impact of a given resource change on the performance of traffic in terms of improving user experience or utility is also hard to predict. Network middle boxes with Deep Packet Inspection (DPI) capabilities have become a necessity for improving the intelligence of networks. OpenFlow, the de facto early standard for Software-Defined Network, encourages multi-vendor openness but only allows traffic engineering on an integrated basis for L2-L4. To introduce DPI functionality, we propose and prototype an enhancement to OpenFlow based on the idea of an External Processing Box (EPB) optionally attached to forwarding engines; however, when attached the EPB is seen as an integrated part of the OpenFlow datapath. With an EPB, a network operator can program L7-based policies within an OpenFlow Controller to control service insertion and traffic engineering. The EPB enables the operator the capability to: - modify traffic behavior based on payload content (i.e. expedite specific traffic) - inject/remove information from the payload - encrypt traffic on the fly
     
    118136
    119137==== Experimentation of SDN-Supported Collaborative DDoS Attack Detection and Containment ====
     138
     139This demo shows a collaborative monitoring and correlation approach to mitigate the effects of the surge in network traffic of a flooding Denial of Service attack that can cause loss of service for legitimate sites.
     140
     141Who should see this demo?
     142
     143Attendees interested in Cybersecurity attack detection, and mitigation techniques.
    120144
    121145Software-defined networking (SDN) and OpenFlow offer great support to dynamically adapt a network and to access data on different network layers as needed. Such advantages have been driving recent research efforts to develop new security applications and services. However, most studies on attack detection and containment have not really differentiated their solutions from the traditional ones, without fully taking advantage of the unique capabilities provided by SDN. Moreover, even if some of these studies provide interesting visions of what can be achieved, they stop short of presenting realistic application scenarios and experimental results. We present a novel attack detection and containment approach that is coordinated by distributed network monitors and controllers/correlators centralized on an SDN OpenFlow Virtual Switch (OVS). With different views and information availability, these elements collaboratively detect signature constituents of an attack that possess different characteristics of scale and detail. Therefore, this approach is able to not only quickly issue an alert against potential threats followed by careful verification for high accuracy, but also balance the workload on the OVS. We apply the proposed approach to TCP SYN flood attacks using Global Environment for Network Innovations (GENI). This realistic experimentation has provided us with insightful findings helpful to our goal toward a systematic methodology of SDN-supported attack detection and containment. First, we have demonstrated through experimentation the scalability of our collaborative scheme. Second, we have studied how the combination of alerts by the monitor and deep packet inspection by the correlator, can increase the speed and accuracy of attack identification. Our experiments, in the context of a small to medium corporate network, have demonstrated the effectiveness and scalability of the SDN-supported detection and containment approach.
     
    216240
    217241==== International Federation ( US, Japan, Europe ) ====
     242
     243This demo shows federation mechamism which enable virtual network between heterogenious virtualization platforms to be created / operated easily..
     244
     245Who should see this demo?
     246
     247Attendees interested in international collaboration should see this demo.
    218248
    219249In this demo slice spread across three different virtualization platforms (VNode, GENI, Fed4Fire) are created. We will show how federated slice is created using the Slice Exchange Point mechanism, which enables whole slice to be managed by the network manager of any single virtualization platform.
     
    227257
    228258==== Enhancing Network Applications on VNode and GENI ====
     259
     260This demo shows enhanced video streaming and big data applications via federation slice between VNode and GENI.
     261
     262Who should see this demo?
     263
     264Attendees interested in application providers and network providers should see this demo. We'll show how to enhance applications by programmable network such as VNode and GENI.
    229265
    230266In this demo, we show enhanced video streaming and big data applications via federation slice between VNode and GENI. In video streaming applications, we deploy multi-casting and transcoding functions dynamically into slice nodes according to the demands. Users can receive high quality video via limited bandwidth. In big data application, we try to transmit big data efficiently and safety via federation slice with US Ignite members.
     
    243279==== Application-driven Programmable Networking by FLARE ====
    244280
     281This demo shows multiple application-driven slices leveraging FLARE DPN for smartphone users as well as Internet of Things (IoT) tiny sensor devices.
     282
     283Who should see this demo?
     284
     285Smartphone users not satisfied in the current application performance should see this demo.
     286
    245287In this demo, the application driven networking for smartphone services will be shown in multiple application specific slices created in FLARE nodes. We can apply the different network policy such as QoS to each slice in accordance with applications. We can also demonstrate the slice tailored to IoT devices such as micro-computer based tiny sensor devices which generate different size of packets from that of the current Internet traffic.
    246288
     
    253295==== SDXs: Software Define Network Exchanges at StarLight and Partner Sites ====
    254296
     297This demo shows a working prototype of SDXs at the !StarLight International / National Communications Exchange Facility and partner sites, which enable the exchange research traffic among different types of Software Define Networks (SDNs) and legacy networks.
     298
     299Who should see this demo?
     300
     301Attendees interested in:
     302 1. Identifying the current challenges in managing SDN networks in production exchanges
     303 2. Proposals for addressing these challenges and the prototype demonstrations
     304 3. Creating virtual exchange prototypes for specialized communities: SDXs for Genomics Data
     305 4. Creating virtual exchange prototypes for specialized communities: SDXs for Cloud testbeds
     306
    255307The challenges in connecting and exchanging different types of network traffic for research and education communities are not well known topics outside of the network exchange communities. The recent proliferation of SDN/OpenFlow technology brings this challenge to the attention of all the interested parties.
    256308
     
    261313
    262314==== Demand-driven Network Management with ProtoRINA ====
     315
     316This demo shows how video can be efficiently multicast to many clients on demand by dynamically creating a delivery tree using ProtoRINA, our prototype of the Recursive InterNetwork Architecture (RINA).
     317
     318Who should see this demo? Attendees interested in future network architectures, and demand-driven network management and its application to software-defined virtual networking.
    263319
    264320We demonstrate how video can be efficiently multicast to many clients on demand by dynamically creating a delivery tree using ProtoRINA, our prototype of the Recursive !InterNetwork Architecture (RINA). Under RINA, multicast can be enabled through a secure communication container that is dynamically formed to support video transport either through application proxies or via relay IPC processes. The former represents application-level management, while the latter represents communication layer management, both forms are part of RINA’s repeating management structure. RINA supports demand-driven network management, where mechanisms (including registration, authentication, enrollment, addressing, etc.) are policy-instantiated to allow the dynamic formation of private communication layers in support of various requirements. This demo highlights RINA's inherent support for envisioned software-defined virtual networking scenarios.