Changes between Version 27 and Version 28 of GEC11PosterDescriptions


Ignore:
Timestamp:
07/19/11 15:25:49 (8 years ago)
Author:
jtaylor@bbn.com
Comment:

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  • GEC11PosterDescriptions

    v27 v28  
    33[[PageOutline(2, Poster Titles)]]
    44
    5 == Secure Content Centric Mobile Network (SECON) ==
    6 
    7 Mooi Choo Chuah, Lehigh University [[br]]
    8 Xiong Xiong, Lehigh University
    9 
    10 '''Abstract'''
    11     New wireless technologies allow mobile users to have easy access to real time data, and stay connected with friends, colleagues, & business partners. However emerging applications are usually data-centric but existing IP oriented paradigms are not flexible enough to support this. To support emerging mobile applications, we are developing a next generation mobile network that supports mobile content centric networking features, namely (a) intentional named message delivery, (b) content-centric security, (c) push-pull based data disseminations.
    12 
    13     In our new  SECON network, users can send User Interest (UI) packets to Content Resolution Server (CRS) to request for content data (CD) packets associated with a particular URI. The UIs will be forwarded by the receiving CRS to other CRSes that know who will be publishing content packets related to that URI. The UIs can also have intentional-named destinations e.g. all CRSes within a certain geographical area. In addition content publishers can send content publish announcements to CRSes before they forward content data packets to these CRSes.  We have a preliminary prototype that supports UI, CPA & CD features. More features will be added in the near future.
    14 
    15 
    16 More Information: [[br]]
    17    http://www.cse.lehigh.edu/~chuah/public_secon.html [[br]]
    18    http://www.cse.lehigh.edu/~chuah/secon.html
    19 
    20 ----
    21 
     5== A New Generation Network Architecture to Accommodate Virtual Network Application Service Providers ==
     6
     7Eiji Kawai, National Institute of Information and Communications Technology (NICT), Japan [[br]]
     8Shuji Ishii, National Institute of Information and Communications Technology (NICT), Japan [[br]]
     9Hiroaki Yamanaka, National Institute of Information and Communications Technology (NICT), Japan [[br]]
     10Katsuyoshi Iida, Tokyo Institute of Technology, Japan [[br]]
     11Masayoshi Shimamura, Tokyo Institute of Technology, Japan [[br]]
     12Takuya Omizo, Tokyo Institute of Technology, Japan [[br]]
     13Masato Tsuru, Kyushu Institute of Technology, Japan [[br]]
     14
     15'''Abstract'''
     16   An essential issue in the future Internet is how to efficiently manage the network and computational resources shared by a variety of application services with different QoS requirements over multiple diverse infrastructural networks. Network virtualization is a promising approach but further studies to develop an effective and practical architecture are required. Our poster presents an outline of a proposed architecture aiming to efficiently accommodate heterogeneous and numerous virtual network application service providers assuming the use of !OpenFlow-based technology. In particular, the architecture focuses on the following features: (1) !OpenFlow network virtualization in a large-scale testbed environment, (2) management of resources by a meta-resource provider to accommodate diverse QoS requirements and dynamic resource status over infrastructural network domains, and (3) distributed information management of network and computational resources based on perfSONAR technology.
     17
     18   Keywords:
     19     *  Future Internet
     20     *  New generation network architecture
     21     *  Network Virtualization
     22     *  !OpenFlow
     23     *  perfSONAR
     24
     25----
     26== Applying a Distributed Security Sensor Network to GENI (!HiveMind) ==
     27
     28Sean Peisert, University of California, Davis (PI)[[br]]
     29Matt Bishop, University of California, Davis [[br]]
     30Steven Templeton, University of California, Davis [[br]]
     31Carrie Gates, CA Labs (CoPI) [[br]]
     32
     33GENI Project: [[br]]
     34   [wiki:HiveMind] [[br]]
     35
     36More Information: [[br]]
     37   http://hivemind.cs.udavis.edu/
     38
     39----
     40
     41== DDoS Attack Detection & DoS Attacks Exploiting WiMAX System Parameters ==
     42
     43Ilker Ozcelik, Holcombe Department of Electrical & Computer Engineering [[br]]
     44Lu Yu, Clemson University
     45
     46'''Abstract'''
     47 
     48    The poster comprises two parts. In part one, we are collecting  the Internet traffic signature on !OpenFlow to use as backgroutnd  traffic. By using the real background traffic, we are investigating the effectiveness of theoretical DDoS attack detection techniques on GENI.  We are also trying to evaluate our proposed equation of necessary  traffic for DDoS attack. Part two focuses on analyzing DoS attacks that  exploit WiMAX system parameter settings. We concentrate on parameters  concerning bandwidth contention resolution in IEEE 802.16 standards. We  use analysis of variance (ANOVA) to find how parameter settings affect  the ability of DoS attackers to monopolize network bandwidth. We are  carrying out a DoS attack against WiMAX on GENI ORBIT and collecting  the data used for ANOVA.
     49
     50----
     51== Developing GENI Aggregates for Real-TIme Large-Scale Network Simulation (PrimoGENI) ==
     52
     53Nathanael Van Vorst, School of Computing and Information Sciences, Florida International University [[br]]
     54Miguel Erazo, School of Computing and Information Sciences, Florida International University [[br]]
     55Hao Jiang, School of Computing and Information Sciences, Florida International University [[br]]
     56Ting Li, School of Computing and Information Sciences, Florida International University [[br]]
     57Jason Liu, School of Computing and Information Sciences, Florida International University [[br]]
     58
     59'''Abstract'''
     60   The goal of PrimoGENI is to incorporate real-time network simulation into the GENI "ecosystem". We have extended PRIME, our existing real-time large-scale network simulator, to become part of the GENI federation. PrimoGENI will support large-scale GENI experiments with millions of simulated network entities (hosts, routers, and links) and thousands of emulated elements running unmodified network protocols and applications.
     61
     62GENI Project: [[br]]
     63   [wiki:PrimoGENI] [[br]]
     64
     65More Information: [[br]]
     66   https://www.primessf.net/pub/Public/PrimoGENIProject/gec11.pdf [[br]]
     67   http://www.primessf.net/PrimoGENI
     68
     69----
     70== Evaluating Schemes for Adapting to Cloud Dynamics using GENI ==
     71
     72Ashiwan Sivakumar, Purdue University [[br]]
     73Shankaranarayanan PN, Purdue University [[br]]
     74Mohammad Hajjat, Purdue University [[br]]
     75Dr. Sanjay Rao, Purdue University [[br]]
     76
     77'''Abstract'''
     78    Enterprises are increasingly deploying their applications in the cloud given the cost-saving advantages, and the potential to geo-distribute applications to ensure resilience and better service experience. Latency and availability are critical with such performance sensitive applications. A key problem then is to meet the stringent response time requirements of enterprise applications in the cloud. We build a system that we term Dealer which for each component, dynamically splits transactions among its replicas in different data-centers.  It adapts to sudden changes in delay across components and routes requests to replicas of the components in a different data-center. In doing so, Dealer seeks to minimize user response times, and takes component performance, as well as intra-data- center and inter-data-center communication latencies into account. We have integrated the system with a performance sensitive trading application called Daytrader in GENI. [[br]]
     79    Our approach to evaluate the system makes use of the controlled and repeatable environment provided by GENI. The experiments that we have conducted on GENI aim at emulating sudden spikes in delay between components. We have studied the dynamic response time of Dealer by subjecting it to a Step Up input reference waveform. We have also compared the user response times in a Multi cloud environment on ProtoGENI with and without dealer. We present the results of the evaluation experiments conducted on GENI.
     80
     81More Information: [[br]]
     82   http://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1415&context=ecetr
     83
     84----
    2285== GENI Experiments on P2P and MANET Networks ==
    2386
     
    2992
    3093'''Abstract'''
    31    Today’s society is witnessing a tremendous increase in digital information. Myriads of applications call for the pooling and sharing of massive amounts of widely-scattered data at ever increasing scales that require a commensurate infrastructure of powerful networked distributed systems across wide and diverse areas. We will implement two existing data sharing algorithms, Cycloid and LORD, on the P2P and MANET networks, and thus identify and investigate potential issues in data sharing applications in these different heterogeneous networks.  We are using GENI as the testbed for simulating the P2P and MANET network environments.  Also, we will conduct a multi-system GENI experiment to demonstrate how each domain should have its own routing solutions while all the domains are federated through !OpenFlow gateways.
    32 
    33 ----
    34 
    35 == Developing GENI Aggregates for Real-TIme Large-Scale Network Simulation (PrimoGENI) ==
    36 
    37 Nathanael Van Vorst, School of Computing and Information Sciences, Florida International University [[br]]
    38 Miguel Erazo, School of Computing and Information Sciences, Florida International University [[br]]
    39 Hao Jiang, School of Computing and Information Sciences, Florida International University [[br]]
    40 Ting Li, School of Computing and Information Sciences, Florida International University [[br]]
    41 Jason Liu, School of Computing and Information Sciences, Florida International University [[br]]
    42 
    43 '''Abstract'''
    44    The goal of PrimoGENI is to incorporate real-time network simulation into the GENI "ecosystem". We have extended PRIME, our existing real-time large-scale network simulator, to become part of the GENI federation. PrimoGENI will support large-scale GENI experiments with millions of simulated network entities (hosts, routers, and links) and thousands of emulated elements running unmodified network protocols and applications.
    45 
    46 GENI Project: [[br]]
    47    [wiki:PrimoGENI] [[br]]
    48 
    49 More Information: [[br]]
    50    https://www.primessf.net/pub/Public/PrimoGENIProject/gec11.pdf [[br]]
    51    http://www.primessf.net/PrimoGENI
    52 
    53 ----
    54 
    55 == TUNIE: A Flexible and Programmable Virtualized Network Innovation Environment in China ==
    56 
    57 Yong Li, Electronic Engineering, Tsinghua University [[br]]
    58 
    59 '''Abstract'''
    60     Network community needs a flexible platform for network experiment of new architectures, algorithms and protocols in the research of network innovation. However, building such a platform faces lots of challenges due to its complicate requirements. In this poster, we present TUNIE, a network testbed for rapid concurrent experiment of network innovation on virtualized programmable infrastructure in China. !ExpoNet provides end-to-end slice including wired and wireless components, which integrates both software- and hardware-based router virtualization technologies to provide a flexible approach to configure and customize both the control plane and data plane while satisfying various experiment requirements. In the wireless part, we have a sensor testbed including 100 wireless sensor nodes, and a !WiFi testbed. In the wired part, we have setup one !OpenFlow network, and two virtualization testbed based on multi-core servers and FPGA data plane. In our current platform implementation, we have four sites, two sites in Tsinghua University, one another university of BUPT, and one in China Union, one of the largest Service Providers in China. We have setup a Federation plan to extend our platform with other Universities and companies like HUST, Huawei, etc.
    61 
    62 More Information: [[br]]
    63    http://166.111.66.197:81/Main/LabTeams
    64 
    65 ----
    66 
    67 == Applying a Distributed Security Sensor Network to GENI (!HiveMind) ==
    68 
    69 Sean Peisert, University of California, Davis (PI)[[br]]
    70 Matt Bishop, University of California, Davis [[br]]
    71 Steven Templeton, University of California, Davis [[br]]
    72 Carrie Gates, CA Labs (CoPI) [[br]]
     94   Today’s society is witnessing a tremendous increase in digital information. Myriads of applications call for the pooling and sharing of massive amounts of widely-scattered data at ever increasing scales that require a commensurate infrastructure of powerful networked distributed systems across wide and diverse areas. We will implement two existing data sharing algorithms, Cycloid and LORD, on the P2P and MANET networks, and thus identify and investigate potential issues in data sharing applications in these different heterogeneous networks.  We are using GENI as the testbed for simulating the P2P and MANET network environments.  Also, we will conduct a multi-system GENI experiment to demonstrate how each domain should have its own routing solutions while all the domains are federated through !OpenFlow gateways.
     95
     96----
     97== GENI Meta Operation Center (GMOC) ==
     98
     99Camilo Viecco, Indiana University, Global Research NOC [[br]]
     100
     101'''Abstract'''
     102    GMOC is now providing more operations support, including tickekting, documentation, measurements and a protected database. We have also done another emergency shutdown drill and are working to improve the process.
     103
     104GENI Project: [[br]]
     105    [wiki:GENIMetaOps]
     106
     107More Information: [[br]]
     108    http://gmoc-db.grnoc.iu.edu/protected [[br]]
     109    http://gmoc.grnoc.iu.edu/ [[br]]
     110    https://tick.globalnoc.iu.edu/fp_tools/public_ticket_viewer/ [[br]]
     111
     112----
     113== GENI Monitoring Slice: Enabling Network Visibility in the GENI !OpenFlow Core Network (LAMP) ==
     114
     115Ali Sydney, Raytheon BBN Technologies [[br]]
     116
     117'''Abstract'''
     118
     119One fundamental requirement of any research or production network architecture is visibility: the ability to observe the performance of a network over time. This fact becomes even more evident when abnormalities in a network become prevalent. These can include classic broadcast storms from an operator's perspective or irresponsiveness of nodes within a slice from an experimenter's point of view.  To date, a plethora of network tools including iperf, nuttcap, ping, Ganglia, and Nagios are available to provide much needed insights into a network's performance.  However, these tools are tailored for "barebone" network components. In GENI, users are provided "slices" which will contain some subset of virtualized, programmable computing resources. For this reason, there exist an emerging class of "visibility" tools dedicated towards monitoring, within a slice context.  Among other tools, we use LAMP, adapted from perfSONAR, to manage and visualize I&M services and data. In particular, we create a reference slice which spans the GENI !OpenFlow backbone to provide experimenters a somewhat "ideal" view of the network's health. Among other uses, we envision that in such cases as network connectivity irregularities within a user's slice, they can quickly refer to the reference slice as a troubleshooting guide.
     120
     121GENI Project: [[br]]
     122    [wiki:LAMP], [wiki:OFBBN], [wiki:ProtoGENI], and [wiki:PlanetLab]
     123
     124More Information: [[br]]
     125    http://groups.geni.net/geni/wiki/LAMP/Tutorial [[br]]
     126    http://psps.perfsonar.net/
     127   
     128----
     129== !GridStat on GENI : Simulating a Smart Power Grid Infrastructure over GENI (PlanetLab) ==
     130
     131Divya Giri, Washington State University [[br]]
     132Ruma Rani Paul, Washington State University
     133
     134'''Abstract'''
     135    Developments in power grid measurement and monitoring technology have enabled precise and frequent measurement of the state of the power grid.  Modern power grid control infrastructure are insufficient to the effective forwarding of this information to the necessary control facilities.  The GridStat framework offers an efficient, low-latency data forwarding framework that can provide the necessary Quality of Service for control facilities to maintain sub-second status of monitored power grid substations.  However, the current GridStat prototypes have not been tested outside local clusters.  The GENI infrastructure provide the platform through which it is possible to test GridStat at scale and identify problems with the current framework.
     136
     137GENI Project: [[br]]
     138    [wiki:PlanetLab]
     139
     140----
     141
     142== Infinity: In-Network Storage for Mobile Devices ==
     143
     144Yudong Gao, University of Michigan [[br]]
     145
     146'''Abstract'''
     147
     148    Data accessed on the mobile devices is exploding, but current mobile applications do a poor job in conserving energy while ensuring good performance, to satisfy the rapid increase in the frequency and volume of data access. The cloud services accessed by these applications consider neither the role of mobile operator’s network nor the mobile device state, leading to poor application performance and wastage of network resources. Today’s mobile operator (MO)’s networks are no longer “dumb pipes” but are connected to data centers with large amount of resources. We argue that this disruptive change makes MO’s network increasingly resemble a cloud computing infrastructure. We propose a storage platform called Infinity that can be used by service providers to effectively exploit the mobile operator’s network, while saving energy on the mobile devices.
     149
     150GENI Project: [[br]]
     151   EAGER: Enabling Mobile Services through In-network Storage and Computation - Evaluation using the GENI Infrastructure.
     152
     153----
     154
     155== Integration for GENI Experiments and Measurement Archive (!OnTimeMeasure) ==
     156
     157Prasad Calyam, OSC/OARnet, Ohio State University [[br]]
     158Yingxiao Xu, OSC, Ohio State University [[br]]
     159Alex Berryman, OARnet, Ohio State University [[br]]
     160Ashiwan Sivakumar, Purdue University [[br]]
     161Giridhar Manepalli, CNRI [[br]]
     162
     163'''Abstract''' [[br]]
     164    Our poster describes the !OnTimeMeasure measurement service integration with two GENI Experiments viz., “Resource allocation in virtual desktop clouds” led by The Ohio State University, and “Emulating cloud dynamics for performance sensitive applications” led by Purdue University. Based on these two experiment integration case studies, a general framework for “new metric” integration in !OnTimeMeasure that is relevant for any GENI Experiment is presented. Lastly, the poster describes the use cases and features for archiving experiment slice measurement datasets along with meta-data collected by !OnTimeMeasure into the GENI Measurement Data Archive being developed/hosted by “Digital Object Registry” led by CNRI.
     165
     166GENI Project: [[br]]
     167    [wiki:OnTimeMeasure]
     168----
     169
     170== Integration of LEARN with GENI Infrastructures using ORCA: VLAN Assignments and Cluster Deployment Plans - Collaborative Efforts on Measurements: IF-MAP for GENI and Collaboration with IMF ==
     171
     172Deniz Gurkan, University of Houston [[br]]
     173Karthik Ram Narumanchi, University of Houston [[br]]
     174Anand Arun Daga, University of Houston [[br]]
     175Ilia Baldine, RENCI [[br]]
     176Rick Kagan, Infoblox [[br]]
     177Ben Warren, Infoblox [[br]]
     178
     179'''Abstract'''
     180   LEARN regional optical network in Texas has been demonstrated with VLAN assignments to reach four major institutions during GEC10 (University of Houston, University of Texas at Austin, Texas A&M University, and Rice University). Planned deployment of clusters to two end points is presented (at University of Houston and Rice University). In addition, the feasibility and applicability of IF-MAP (Trusted Network Computing's Interface Metadata Access Point architecture) to the I&M services in GENI has been presented. A collaborative initiative to deploy IMF's optical physical layer monitoring software in perfSONAR to the LEARN nodes is in progress.
     181
     182GENI Project: [[br]]
     183   ORCA and [wiki:IMF]
     184
     185More Information: [[br]]
     186   http://groups.geni.net/geni/wiki/LEARN
     187
     188----
     189
     190== Leveraging and Abstracting Measurements with PerfSONAR (LAMP) ==
     191
     192Guilherme Fernandes, University of Delaware [[br]]
     193Ezra Kissel, University of Delaware [[br]]
     194Matthew Jaffee, University of Delaware [[br]]
     195Martin Swany, University of Delaware [[br]]
     196Jason Zurawski, Internet2 [[br]]
     197Matt Zekauskas, Internet2 [[br]]
     198Eric Boyd, Internet2 [[br]]
     199
     200GENI Project: [[br]]
     201   [wiki:LAMP]
     202
     203----
     204== MAX GENI Aggregate Federation and Stitching ==
     205
     206Tom Lehman, University of Southern California [[br]]
     207Xi Yang, Information Sciences Institute, Virginia [[br]]
     208Abella  Battou, Mid-Atlantic Crossroads GigaPOP [[br]]
     209Balu Pillai, University of Maryland [[br]]
     210
     211'''Abstract'''
     212   The MAX project has constructed the "Mid-Atlantic Crossroads GENI (MAX GENI) Facility" which enables the MAX Regional Network resources to be made available for GENI experiments.   This includes development of a MAX Aggregate Manager which integrates the dynamic provision of network and host based resources. The host based resources include !PlanetLab node virtual slices.  MAX Network Stitching capabilities allow the host resources to be stitched together with Ethernet VLANs.  The MAX AM is also federated with !PlanetLab Princeton and ProtoGENI.   In addition, a separate instance of a MAX Aggregate Manager has been deployed to "cover" the Internet2 ION Network.This combination of these capabilities now allows us to provide multi-aggregate sliver creation and stitching operations in response to Experimenters requests.
     213
     214More Information: [[br]]
     215    geni.maxgigapop.net/twiki/pub/GENI/Publications/max-geni-gec11-poster.pdf [[br]]
     216    geni.maxgigapop.net
     217
     218----
     219
     220== Measurement Data Archive (!DigitalObjectRegistry) ==
     221
     222Giridhar Manepalli, CNRI [[br]]
     223Prasad Calyam, Ohio Supercomputing Center [[br]]
     224
     225'''Abstract'''
     226   Corporation for National Research Initiatives (CNRI) will be demonstrating the functionality of the proposed Measurement Data Archive, which is implemented using the Digital Object Architecture.
     227
     228   The Measurement Data Archive prototype system consists of two components: 1) User Workspace and 2) Object Archive. The User Workspace component is an entry point for users (e.g., experimenters, instrumentation researchers, etc.) to store and transfer measurement data, which could be in a variety of forms (e.g., formatted datasets, raw files, etc.). Data and metadata files managed in the user workspace can be archived for long-term storage in an Object Archive. Once data is archived, a persistent and unique identifier is created.
     229
     230GENI Project: [[br]]
     231   [wiki:DigitalObjectRegistry]
     232
     233More Information: [[br]]
     234   http://mda.doregistry.org/
     235
     236----
     237== !OpenFlow Campus Trial at Clemson: An !OpenFlow Service for Seamless Enhancement of Data Transport Throughput (OFCLEM) ==
     238
     239Aaron Rosen, Clemson University [[br]]
     240Kuang-Ching Wang, Clemson University [[br]]
     241Jim Pepin, Clemson University [[br]]
     242Daniel Schmiedt, Clemson University [[br]]
     243
     244'''Abstract'''
     245    In a software defined network, packet forwarding methods can be changed on the fly to suit the needs of different traffic types. Not only can such a network redirect traffic's path, but it can also inject software agents in the forwarding path to provide additional services. At Clemson, we developed a solution to seamlessly enhance end-to-end data transport throughput across wide area networks. By decoupling end user and the core network's choice of transport protocols, the network provider can seamlessly enhance end users' experienced performance without requiring them to upgrade to unfamiliar new transport protocols.
     246
     247GENI Project: [[br]]
     248   [wiki:OFCLEM] [[br]]
     249
     250More Information: [[br]]
     251   http://openflow.clemson.edu/gec11-poster.pdf [[br]]
     252   http://openflow.clemson.edu/
     253
     254----
     255
     256== Scalable Sensing Service (S3MONITOR) ==
     257
     258Sonia Fahmy, Purdue University [[br]]
     259Ethan Blanton, Purdue University [[br]]
     260Sumit Kala, HP Labs
     261
     262'''Abstract'''
     263
     264    The Scalable Sensing Service (S3 Monitor) provides basic management services for users to take controlled measurements, e.g., available bandwidth or packet loss, between GENI nodes.  A web interface is provided to the user for scheduling and initiating measurements, managing ongoing measurements, and retrieving measurement results.
    73265
    74266GENI Project: [[br]]
    75    [wiki:HiveMind] [[br]]
    76 
    77 More Information: [[br]]
    78    http://hivemind.cs.udavis.edu/
     267    Scalable, Extensible, and Safe Monitoring of GENI: [wiki:ScalableMonitoring]
     268
     269More Information: [[br]]
     270    http://groups.geni.net/geni/attachment/wiki/ScalableMonitoring/gec11-onepage.pdf
     271
     272----
     273== Secure Content Centric Mobile Network (SECON) ==
     274
     275Mooi Choo Chuah, Lehigh University [[br]]
     276Xiong Xiong, Lehigh University
     277
     278'''Abstract'''
     279    New wireless technologies allow mobile users to have easy access to real time data, and stay connected with friends, colleagues, & business partners. However emerging applications are usually data-centric but existing IP oriented paradigms are not flexible enough to support this. To support emerging mobile applications, we are developing a next generation mobile network that supports mobile content centric networking features, namely (a) intentional named message delivery, (b) content-centric security, (c) push-pull based data disseminations.
     280
     281    In our new  SECON network, users can send User Interest (UI) packets to Content Resolution Server (CRS) to request for content data (CD) packets associated with a particular URI. The UIs will be forwarded by the receiving CRS to other CRSes that know who will be publishing content packets related to that URI. The UIs can also have intentional-named destinations e.g. all CRSes within a certain geographical area. In addition content publishers can send content publish announcements to CRSes before they forward content data packets to these CRSes.  We have a preliminary prototype that supports UI, CPA & CD features. More features will be added in the near future.
     282
     283
     284More Information: [[br]]
     285   http://www.cse.lehigh.edu/~chuah/public_secon.html [[br]]
     286   http://www.cse.lehigh.edu/~chuah/secon.html
     287
     288----
     289== Socially Aware Single System Image ==
     290
     291Prof. Chunming Qiao (PI), SUNY Buffalo [[br]]
     292Lokesh Mandvekar, SUNY Buffalo
     293
     294'''Abstract'''
     295   A single system image (SSI) is the property of a system that hides the heterogeneous and distributed nature of the available resources and presents them to users and applications as a single unified computing resource. The current GENI infrastructure allows users to select and configure resources at geographically dispersed deployments and thus create their own “slice”. Our proposed experiment will allow a user to augment his resources into a single unified system by leasing/sharing resources with his friends/social contacts (along the lines of a social networking model). An SSI will thus be different from a GENI end-to-end slice in that the SSI effectively appears as a single system to the user and not as a heterogeneous end-to-end connected set of resources. An SSI cluster provides the following benefits:
     296        1. single entry point
     297        2. single user interface
     298        3. single process space
     299        4. single memory space
     300        5. single i/o space
     301        6. single file hierarchy
     302        7. single job management system
     303        8. single control point and management
     304   The other most important benefit of using an SSI is security and data privacy. By forming an SSI with trusted resources an user can get the computing power needed to run his/her application without the fear of the application being compromised by using a third party service.
     305
     306----
     307
     308== SPP Deployment and Named Data Networking Research ==
     309
     310
     311Patrick Crowley (PI), Washington University [[br]]
     312Jon Turner (PI), Washington University [[br]]
     313John !DeHart, Washington University [[br]]
     314Mart Haitjema, Washington University [[br]]
     315Shakir James, Washington University [[br]]
     316Jyoti Parwatikar, Washington University [[br]]
     317Michael Wilson, Washington University [[br]]
     318Haowei Yuan, Washington University [[br]]
     319
     320'''Abstract'''
     321
     322    Washington University Internet Scale Overlay Hosting/SPP Deployment
     323
     324More Information: [[br]]
     325   http://wiki.arl.wustl.edu/index.php/Internet_Scale_Overlay_Hosting
    79326
    80327----
     
    106353----
    107354
    108 == Trema; An Open Source OpenFlow Controller Platform ==
    109 
    110 Hideyuki Shimonishi, System Platforms Research Laboratories, NEC Corporation [[br]]
    111 Yasunobu Chiba, System Platforms Research Laboratories, NEC Corporation [[br]]
    112 Yasuhito Takamiya, System Platforms Research Laboratories, NEC Corporation [[br]]
    113 Kazushi Sugyo, System Platforms Research Laboratories, NEC Corporation [[br]]
    114 
    115 '''Abstract'''
    116  * Trema is a free !OpenFlow controller platform (GPL v2)
    117     * Assists anyone who wants to develop his/her own !OpenFlow controller
    118     * Not targeted for any specific !OpenFlow controller implementation
    119  * Trema allows to implement !OpenFlow controllers in C and Ruby
    120  * Trema provides:
    121     * Various basic libraries on which you can build your own !OpenFlow controller
    122     * Integrated network emulator and developing environment
    123  * Contact
    124     * Mailing list: trema-dev@googlegroups.com  /  twitter: @trema_news [[br]]
    125 
    126 More Information: [[br]]
    127    http://trema.github.com/trema/doc/Trema_GEC11_poster.pdf [[br]]
    128    http://trema.github.com/trema/ [[br]]
    129    https://github.com/trema/trema/wiki [[br]]
    130 
    131 ----
    132 
     355
     356== The Performance Evaluation of Bandwidth Allocation Algorithms in Multi-domain Networks ==
     357
     358Jiten Patel, Rochester Institute of Technology [[br]]
     359Kaiqi Xiong, Rochester Institute of Technology [[br]]
     360
     361'''Abstract'''
     362    This project is concerned with dynamic bandwidth allocation in multi-domain networks. We have been designing and developing the algorithms to minimize the total cost of network bandwidth when satisfying the requirements of Quality of Service (QoS) predefined in the Service Level Agreement (SLA). An SLA is a contract negotiated between a network service provider and customers. The goal of this research is to evaluate the performance of these bandwidth allocation algorithms by a use of the GENI infrastructure. We have conducted experiments for the validation of percentile delay calculations as well as the evaluation of Additive Increase/Multiplicative Decrease (AIMD)-based bandwidth allocation algorithms. Furthermore, by using the research experiments of this project, we have designed GENI educational experiments that have been used in networking courses at RIT.
     363
     364----
    133365== !TransCloud (GENICloud) ==
    134366
     
    157389----
    158390
    159 == Measurement Data Archive (!DigitalObjectRegistry) ==
    160 
    161 Giridhar Manepalli, CNRI [[br]]
    162 Prasad Calyam, Ohio Supercomputing Center [[br]]
    163 
    164 '''Abstract'''
    165    Corporation for National Research Initiatives (CNRI) will be demonstrating the functionality of the proposed Measurement Data Archive, which is implemented using the Digital Object Architecture.
    166 
    167    The Measurement Data Archive prototype system consists of two components: 1) User Workspace and 2) Object Archive. The User Workspace component is an entry point for users (e.g., experimenters, instrumentation researchers, etc.) to store and transfer measurement data, which could be in a variety of forms (e.g., formatted datasets, raw files, etc.). Data and metadata files managed in the user workspace can be archived for long-term storage in an Object Archive. Once data is archived, a persistent and unique identifier is created.
    168 
    169 GENI Project: [[br]]
    170    [wiki:DigitalObjectRegistry]
    171 
    172 More Information: [[br]]
    173    http://mda.doregistry.org/
    174 
    175 ----
    176 
    177 == Integration of LEARN with GENI Infrastructures using ORCA: VLAN Assignments and Cluster Deployment Plans - Collaborative Efforts on Measurements: IF-MAP for GENI and Collaboration with IMF ==
    178 
    179 Deniz Gurkan, University of Houston [[br]]
    180 Karthik Ram Narumanchi, University of Houston [[br]]
    181 Anand Arun Daga, University of Houston [[br]]
    182 Ilia Baldine, RENCI [[br]]
    183 Rick Kagan, Infoblox [[br]]
    184 Ben Warren, Infoblox [[br]]
    185 
    186 '''Abstract'''
    187    LEARN regional optical network in Texas has been demonstrated with VLAN assignments to reach four major institutions during GEC10 (University of Houston, University of Texas at Austin, Texas A&M University, and Rice University). Planned deployment of clusters to two end points is presented (at University of Houston and Rice University). In addition, the feasibility and applicability of IF-MAP (Trusted Network Computing's Interface Metadata Access Point architecture) to the I&M services in GENI has been presented. A collaborative initiative to deploy IMF's optical physical layer monitoring software in perfSONAR to the LEARN nodes is in progress.
    188 
    189 GENI Project: [[br]]
    190    ORCA and [wiki:IMF]
    191 
    192 More Information: [[br]]
    193    http://groups.geni.net/geni/wiki/LEARN
    194 
    195 ----
    196 
    197 == DDoS Attack Detection & DoS Attacks Exploiting WiMAX System Parameters ==
    198 
    199 Ilker Ozcelik, Holcombe Department of Electrical & Computer Engineering [[br]]
    200 Lu Yu, Clemson University
    201 
    202 '''Abstract'''
    203  
    204     The poster comprises two parts. In part one, we are collecting  the Internet traffic signature on !OpenFlow to use as backgroutnd  traffic. By using the real background traffic, we are investigating the effectiveness of theoretical DDoS attack detection techniques on GENI.  We are also trying to evaluate our proposed equation of necessary  traffic for DDoS attack. Part two focuses on analyzing DoS attacks that  exploit WiMAX system parameter settings. We concentrate on parameters  concerning bandwidth contention resolution in IEEE 802.16 standards. We  use analysis of variance (ANOVA) to find how parameter settings affect  the ability of DoS attackers to monopolize network bandwidth. We are  carrying out a DoS attack against WiMAX on GENI ORBIT and collecting  the data used for ANOVA.
    205 
    206 ----
    207 
    208 == Evaluating Schemes for Adapting to Cloud Dynamics using GENI ==
    209 
    210 Ashiwan Sivakumar, Purdue University [[br]]
    211 Shankaranarayanan PN, Purdue University [[br]]
    212 Mohammad Hajjat, Purdue University [[br]]
    213 Dr. Sanjay Rao, Purdue University [[br]]
    214 
    215 '''Abstract'''
    216     Enterprises are increasingly deploying their applications in the cloud given the cost-saving advantages, and the potential to geo-distribute applications to ensure resilience and better service experience. Latency and availability are critical with such performance sensitive applications. A key problem then is to meet the stringent response time requirements of enterprise applications in the cloud. We build a system that we term Dealer which for each component, dynamically splits transactions among its replicas in different data-centers.  It adapts to sudden changes in delay across components and routes requests to replicas of the components in a different data-center. In doing so, Dealer seeks to minimize user response times, and takes component performance, as well as intra-data- center and inter-data-center communication latencies into account. We have integrated the system with a performance sensitive trading application called Daytrader in GENI. [[br]]
    217     Our approach to evaluate the system makes use of the controlled and repeatable environment provided by GENI. The experiments that we have conducted on GENI aim at emulating sudden spikes in delay between components. We have studied the dynamic response time of Dealer by subjecting it to a Step Up input reference waveform. We have also compared the user response times in a Multi cloud environment on ProtoGENI with and without dealer. We present the results of the evaluation experiments conducted on GENI.
    218 
    219 More Information: [[br]]
    220    http://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1415&context=ecetr
    221 
    222 ----
    223 
    224 == Leveraging and Abstracting Measurements with PerfSONAR (LAMP) ==
    225 
    226 Guilherme Fernandes, University of Delaware [[br]]
    227 Ezra Kissel, University of Delaware [[br]]
    228 Matthew Jaffee, University of Delaware [[br]]
    229 Martin Swany, University of Delaware [[br]]
    230 Jason Zurawski, Internet2 [[br]]
    231 Matt Zekauskas, Internet2 [[br]]
    232 Eric Boyd, Internet2 [[br]]
    233 
    234 GENI Project: [[br]]
    235    [wiki:LAMP]
    236 
    237 ----
    238 
    239 == GENI Meta Operation Center (GMOC) ==
    240 
    241 Camilo Viecco, Indiana University, Global Research NOC [[br]]
    242 
    243 '''Abstract'''
    244     GMOC is now providing more operations support, including tickekting, documentation, measurements and a protected database. We have also done another emergency shutdown drill and are working to improve the process.
    245 
    246 GENI Project: [[br]]
    247     [wiki:GENIMetaOps]
    248 
    249 More Information: [[br]]
    250     http://gmoc-db.grnoc.iu.edu/protected [[br]]
    251     http://gmoc.grnoc.iu.edu/ [[br]]
    252     https://tick.globalnoc.iu.edu/fp_tools/public_ticket_viewer/ [[br]]
    253 
    254 ----
    255 
    256 == A New Generation Network Architecture to Accommodate Virtual Network Application Service Providers ==
    257 
    258 Eiji Kawai, National Institute of Information and Communications Technology (NICT), Japan [[br]]
    259 Shuji Ishii, National Institute of Information and Communications Technology (NICT), Japan [[br]]
    260 Hiroaki Yamanaka, National Institute of Information and Communications Technology (NICT), Japan [[br]]
    261 Katsuyoshi Iida, Tokyo Institute of Technology, Japan [[br]]
    262 Masayoshi Shimamura, Tokyo Institute of Technology, Japan [[br]]
    263 Takuya Omizo, Tokyo Institute of Technology, Japan [[br]]
    264 Masato Tsuru, Kyushu Institute of Technology, Japan [[br]]
    265 
    266 '''Abstract'''
    267    An essential issue in the future Internet is how to efficiently manage the network and computational resources shared by a variety of application services with different QoS requirements over multiple diverse infrastructural networks. Network virtualization is a promising approach but further studies to develop an effective and practical architecture are required. Our poster presents an outline of a proposed architecture aiming to efficiently accommodate heterogeneous and numerous virtual network application service providers assuming the use of !OpenFlow-based technology. In particular, the architecture focuses on the following features: (1) !OpenFlow network virtualization in a large-scale testbed environment, (2) management of resources by a meta-resource provider to accommodate diverse QoS requirements and dynamic resource status over infrastructural network domains, and (3) distributed information management of network and computational resources based on perfSONAR technology.
    268 
    269    Keywords:
    270      *  Future Internet
    271      *  New generation network architecture
    272      *  Network Virtualization
    273      *  !OpenFlow
    274      *  perfSONAR
    275 
    276 ----
    277 
    278 == Infinity: In-Network Storage for Mobile Devices ==
    279 
    280 Yudong Gao, University of Michigan [[br]]
    281 
    282 '''Abstract'''
    283 
    284     Data accessed on the mobile devices is exploding, but current mobile applications do a poor job in conserving energy while ensuring good performance, to satisfy the rapid increase in the frequency and volume of data access. The cloud services accessed by these applications consider neither the role of mobile operator’s network nor the mobile device state, leading to poor application performance and wastage of network resources. Today’s mobile operator (MO)’s networks are no longer “dumb pipes” but are connected to data centers with large amount of resources. We argue that this disruptive change makes MO’s network increasingly resemble a cloud computing infrastructure. We propose a storage platform called Infinity that can be used by service providers to effectively exploit the mobile operator’s network, while saving energy on the mobile devices.
    285 
    286 GENI Project: [[br]]
    287    EAGER: Enabling Mobile Services through In-network Storage and Computation - Evaluation using the GENI Infrastructure.
    288 
    289 ----
    290 
    291 == !OpenFlow Campus Trial at Clemson: An !OpenFlow Service for Seamless Enhancement of Data Transport Throughput (OFCLEM) ==
    292 
    293 Aaron Rosen, Clemson University [[br]]
    294 Kuang-Ching Wang, Clemson University [[br]]
    295 Jim Pepin, Clemson University [[br]]
    296 Daniel Schmiedt, Clemson University [[br]]
    297 
    298 '''Abstract'''
    299     In a software defined network, packet forwarding methods can be changed on the fly to suit the needs of different traffic types. Not only can such a network redirect traffic's path, but it can also inject software agents in the forwarding path to provide additional services. At Clemson, we developed a solution to seamlessly enhance end-to-end data transport throughput across wide area networks. By decoupling end user and the core network's choice of transport protocols, the network provider can seamlessly enhance end users' experienced performance without requiring them to upgrade to unfamiliar new transport protocols.
    300 
    301 GENI Project: [[br]]
    302    [wiki:OFCLEM] [[br]]
    303 
    304 More Information: [[br]]
    305    http://openflow.clemson.edu/gec11-poster.pdf [[br]]
    306    http://openflow.clemson.edu/
    307 ----
    308 
    309 == Scalable Sensing Service (S3MONITOR) ==
    310 
    311 Sonia Fahmy, Purdue University [[br]]
    312 Ethan Blanton, Purdue University [[br]]
    313 Sumit Kala, HP Labs
    314 
    315 '''Abstract'''
    316 
    317     The Scalable Sensing Service (S3 Monitor) provides basic management services for users to take controlled measurements, e.g., available bandwidth or packet loss, between GENI nodes.  A web interface is provided to the user for scheduling and initiating measurements, managing ongoing measurements, and retrieving measurement results.
    318 
    319 GENI Project: [[br]]
    320     Scalable, Extensible, and Safe Monitoring of GENI: [wiki:ScalableMonitoring]
    321 
    322 More Information: [[br]]
    323     http://groups.geni.net/geni/attachment/wiki/ScalableMonitoring/gec11-onepage.pdf
    324 
    325 ----
    326 
    327 == SPP Deployment and Named Data Networking Research ==
    328 
    329 
    330 Patrick Crowley (PI), Washington University [[br]]
    331 Jon Turner (PI), Washington University [[br]]
    332 John !DeHart, Washington University [[br]]
    333 Mart Haitjema, Washington University [[br]]
    334 Shakir James, Washington University [[br]]
    335 Jyoti Parwatikar, Washington University [[br]]
    336 Michael Wilson, Washington University [[br]]
    337 Haowei Yuan, Washington University [[br]]
    338 
    339 '''Abstract'''
    340 
    341     Washington University Internet Scale Overlay Hosting/SPP Deployment
    342 
    343 More Information: [[br]]
    344    http://wiki.arl.wustl.edu/index.php/Internet_Scale_Overlay_Hosting
    345 
    346 ----
    347 == Socially Aware Single System Image ==
    348 
    349 Prof. Chunming Qiao (PI), SUNY Buffalo [[br]]
    350 Lokesh Mandvekar, SUNY Buffalo
    351 
    352 '''Abstract'''
    353    A single system image (SSI) is the property of a system that hides the heterogeneous and distributed nature of the available resources and presents them to users and applications as a single unified computing resource. The current GENI infrastructure allows users to select and configure resources at geographically dispersed deployments and thus create their own “slice”. Our proposed experiment will allow a user to augment his resources into a single unified system by leasing/sharing resources with his friends/social contacts (along the lines of a social networking model). An SSI will thus be different from a GENI end-to-end slice in that the SSI effectively appears as a single system to the user and not as a heterogeneous end-to-end connected set of resources. An SSI cluster provides the following benefits:
    354         1. single entry point
    355         2. single user interface
    356         3. single process space
    357         4. single memory space
    358         5. single i/o space
    359         6. single file hierarchy
    360         7. single job management system
    361         8. single control point and management
    362    The other most important benefit of using an SSI is security and data privacy. By forming an SSI with trusted resources an user can get the computing power needed to run his/her application without the fear of the application being compromised by using a third party service.
    363 ----
    364 
    365 == Integration for GENI Experiments and Measurement Archive (!OnTimeMeasure) ==
    366 
    367 Prasad Calyam, OSC/OARnet, Ohio State University [[br]]
    368 Yingxiao Xu, OSC, Ohio State University [[br]]
    369 Alex Berryman, OARnet, Ohio State University [[br]]
    370 Ashiwan Sivakumar, Purdue University [[br]]
    371 Giridhar Manepalli, CNRI [[br]]
    372 
    373 '''Abstract''' [[br]]
    374     Our poster describes the !OnTimeMeasure measurement service integration with two GENI Experiments viz., “Resource allocation in virtual desktop clouds” led by The Ohio State University, and “Emulating cloud dynamics for performance sensitive applications” led by Purdue University. Based on these two experiment integration case studies, a general framework for “new metric” integration in !OnTimeMeasure that is relevant for any GENI Experiment is presented. Lastly, the poster describes the use cases and features for archiving experiment slice measurement datasets along with meta-data collected by !OnTimeMeasure into the GENI Measurement Data Archive being developed/hosted by “Digital Object Registry” led by CNRI.
    375 
    376 GENI Project: [[br]]
    377     [wiki:OnTimeMeasure]
    378 ----
     391== Trema; An Open Source OpenFlow Controller Platform ==
     392
     393Hideyuki Shimonishi, System Platforms Research Laboratories, NEC Corporation [[br]]
     394Yasunobu Chiba, System Platforms Research Laboratories, NEC Corporation [[br]]
     395Yasuhito Takamiya, System Platforms Research Laboratories, NEC Corporation [[br]]
     396Kazushi Sugyo, System Platforms Research Laboratories, NEC Corporation [[br]]
     397
     398'''Abstract'''
     399 * Trema is a free !OpenFlow controller platform (GPL v2)
     400    * Assists anyone who wants to develop his/her own !OpenFlow controller
     401    * Not targeted for any specific !OpenFlow controller implementation
     402 * Trema allows to implement !OpenFlow controllers in C and Ruby
     403 * Trema provides:
     404    * Various basic libraries on which you can build your own !OpenFlow controller
     405    * Integrated network emulator and developing environment
     406 * Contact
     407    * Mailing list: trema-dev@googlegroups.com  /  twitter: @trema_news [[br]]
     408
     409More Information: [[br]]
     410   http://trema.github.com/trema/doc/Trema_GEC11_poster.pdf [[br]]
     411   http://trema.github.com/trema/ [[br]]
     412   https://github.com/trema/trema/wiki [[br]]
     413
     414----
     415
     416
     417== TUNIE: A Flexible and Programmable Virtualized Network Innovation Environment in China ==
     418
     419Yong Li, Electronic Engineering, Tsinghua University [[br]]
     420
     421'''Abstract'''
     422    Network community needs a flexible platform for network experiment of new architectures, algorithms and protocols in the research of network innovation. However, building such a platform faces lots of challenges due to its complicate requirements. In this poster, we present TUNIE, a network testbed for rapid concurrent experiment of network innovation on virtualized programmable infrastructure in China. !ExpoNet provides end-to-end slice including wired and wireless components, which integrates both software- and hardware-based router virtualization technologies to provide a flexible approach to configure and customize both the control plane and data plane while satisfying various experiment requirements. In the wireless part, we have a sensor testbed including 100 wireless sensor nodes, and a !WiFi testbed. In the wired part, we have setup one !OpenFlow network, and two virtualization testbed based on multi-core servers and FPGA data plane. In our current platform implementation, we have four sites, two sites in Tsinghua University, one another university of BUPT, and one in China Union, one of the largest Service Providers in China. We have setup a Federation plan to extend our platform with other Universities and companies like HUST, Huawei, etc.
     423
     424More Information: [[br]]
     425   http://166.111.66.197:81/Main/LabTeams
     426
     427----
     428
    379429
    380430== Using OMF/OML for WiMAX Experiments (WIMXBBN) ==
     
    394444----
    395445
    396 == GENI Monitoring Slice: Enabling Network Visibility in the GENI !OpenFlow Core Network (LAMP) ==
    397 
    398 Ali Sydney, Raytheon BBN Technologies [[br]]
    399 
    400 '''Abstract'''
    401 
    402 One fundamental requirement of any research or production network architecture is visibility: the ability to observe the performance of a network over time. This fact becomes even more evident when abnormalities in a network become prevalent. These can include classic broadcast storms from an operator's perspective or irresponsiveness of nodes within a slice from an experimenter's point of view.  To date, a plethora of network tools including iperf, nuttcap, ping, Ganglia, and Nagios are available to provide much needed insights into a network's performance.  However, these tools are tailored for "barebone" network components. In GENI, users are provided "slices" which will contain some subset of virtualized, programmable computing resources. For this reason, there exist an emerging class of "visibility" tools dedicated towards monitoring, within a slice context.  Among other tools, we use LAMP, adapted from perfSONAR, to manage and visualize I&M services and data. In particular, we create a reference slice which spans the GENI !OpenFlow backbone to provide experimenters a somewhat "ideal" view of the network's health. Among other uses, we envision that in such cases as network connectivity irregularities within a user's slice, they can quickly refer to the reference slice as a troubleshooting guide.
    403 
    404 GENI Project: [[br]]
    405     [wiki:LAMP], [wiki:OFBBN], [wiki:ProtoGENI], and [wiki:PlanetLab]
    406 
    407 More Information: [[br]]
    408     http://groups.geni.net/geni/wiki/LAMP/Tutorial [[br]]
    409     http://psps.perfsonar.net/
    410    
    411 ----
    412 
    413 == !GridStat on GENI : Simulating a Smart Power Grid Infrastructure over GENI (PlanetLab) ==
    414 
    415 Divya Giri, Washington State University [[br]]
    416 Ruma Rani Paul, Washington State University
    417 
    418 '''Abstract'''
    419     Developments in power grid measurement and monitoring technology have enabled precise and frequent measurement of the state of the power grid.  Modern power grid control infrastructure are insufficient to the effective forwarding of this information to the necessary control facilities.  The GridStat framework offers an efficient, low-latency data forwarding framework that can provide the necessary Quality of Service for control facilities to maintain sub-second status of monitored power grid substations.  However, the current GridStat prototypes have not been tested outside local clusters.  The GENI infrastructure provide the platform through which it is possible to test GridStat at scale and identify problems with the current framework.
    420 
    421 GENI Project: [[br]]
    422     [wiki:PlanetLab]
    423 
    424 ----
    425 
    426 == The Performance Evaluation of Bandwidth Allocation Algorithms in Multi-domain Networks ==
    427 
    428 Jiten Patel, Rochester Institute of Technology [[br]]
    429 Kaiqi Xiong, Rochester Institute of Technology [[br]]
    430 
    431 '''Abstract'''
    432     This project is concerned with dynamic bandwidth allocation in multi-domain networks. We have been designing and developing the algorithms to minimize the total cost of network bandwidth when satisfying the requirements of Quality of Service (QoS) predefined in the Service Level Agreement (SLA). An SLA is a contract negotiated between a network service provider and customers. The goal of this research is to evaluate the performance of these bandwidth allocation algorithms by a use of the GENI infrastructure. We have conducted experiments for the validation of percentile delay calculations as well as the evaluation of Additive Increase/Multiplicative Decrease (AIMD)-based bandwidth allocation algorithms. Furthermore, by using the research experiments of this project, we have designed GENI educational experiments that have been used in networking courses at RIT.
    433 
    434 ----
    435 
    436 == MAX GENI Aggregate Federation and Stitching ==
    437 
    438 Tom Lehman, University of Southern California [[br]]
    439 Xi Yang, Information Sciences Institute, Virginia [[br]]
    440 Abella  Battou, Mid-Atlantic Crossroads GigaPOP [[br]]
    441 Balu Pillai, University of Maryland [[br]]
    442 
    443 '''Abstract'''
    444    The MAX project has constructed the "Mid-Atlantic Crossroads GENI (MAX GENI) Facility" which enables the MAX Regional Network resources to be made available for GENI experiments.   This includes development of a MAX Aggregate Manager which integrates the dynamic provision of network and host based resources. The host based resources include !PlanetLab node virtual slices.  MAX Network Stitching capabilities allow the host resources to be stitched together with Ethernet VLANs.  The MAX AM is also federated with !PlanetLab Princeton and ProtoGENI.   In addition, a separate instance of a MAX Aggregate Manager has been deployed to "cover" the Internet2 ION Network.This combination of these capabilities now allows us to provide multi-aggregate sliver creation and stitching operations in response to Experimenters requests.
    445 
    446 More Information: [[br]]
    447     geni.maxgigapop.net/twiki/pub/GENI/Publications/max-geni-gec11-poster.pdf [[br]]
    448     geni.maxgigapop.net
     446
     447