Changes between Version 25 and Version 26 of GENIBibliography


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Timestamp:
04/08/15 14:56:14 (5 years ago)
Author:
Mark Berman
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  • GENIBibliography

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    417417<a href="http://s3.amazonaws.com/marcoy&#x005F;thesis/Thesis.pdf">http://s3.amazonaws.com/marcoy&#x005F;thesis/Thesis.pdf</a>
    418 <br><br><b>Abstract: </b>Computer networking researchers often have access to a few dierent network testbeds (Section 1.2) for their experiments. However, those testbeds are limited in resources; contentions for resources are prominent in those testbeds especially when conference deadline is looming. Moreover, services running on those testbeds are subject to seasonal and daily trac spikes from users all round the world. Hence, demand for resources at the testbeds are high. Some researchers can use other testbeds in conjunction with the ones they are using. Even though each of the testbeds may have dierent infrastructures, and characteristics, in the end, what the researchers receive in return is a set of computing resources, either virtual machines or physical machines. Essentially, those testbeds are providing a similar service, but researchers have to manage the credentials for accessing the testbeds manually, and they have to manually request resources from dierent testbeds in order to setup experiments that span across dierent testbeds. This thesis presents GENICloud, a project that enables the federation of testbeds with clouds. Computing and storage resources can be provisioned to researchers and services running on existing testbeds dynamically from an Eucalyptus cloud. As a part of the GENICloud project, the user proxy (Section 3.4) provides a less arduous method for testbeds administrators to federate with other testbeds; the same serviceiv also manages researchers credentials, so they do not have to acquire resources from each testbed individually. The user proxy provides a single interface for researchers to interact with dierent testbeds and clouds and manage their experiments. Furthermore, GENICloud demonstrates that there are, in fact, quite a few architectural similarities between dierent testbeds and even clouds
     418<br><br><b>Abstract: </b>Computer networking researchers often have access to a few di
     419erent network testbeds (Section 1.2) for their experiments. However, those testbeds are limited in resources; contentions for resources are prominent in those testbeds especially when conference deadline is looming. Moreover, services running on those testbeds are subject to seasonal and daily trac spikes from users all round the world. Hence, demand for resources at the testbeds are high. Some researchers can use other testbeds in conjunction with the ones they are using. Even though each of the testbeds may have di
     420erent infrastructures, and characteristics, in the end, what the researchers receive in return is a set of computing resources, either virtual machines or physical machines. Essentially, those testbeds are providing a similar service, but researchers have to manage the credentials for accessing the testbeds manually, and they have to manually request resources from di
     421erent testbeds in order to setup experiments that span across di
     422erent testbeds. This thesis presents GENICloud, a project that enables the federation of testbeds with clouds. Computing and storage resources can be provisioned to researchers and services running on existing testbeds dynamically from an Eucalyptus cloud. As a part of the GENICloud project, the user proxy (Section 3.4) provides a less arduous method for testbeds administrators to federate with other testbeds; the same serviceiv also manages researchers credentials, so they do not have to acquire resources from each testbed individually. The user proxy provides a single interface for researchers to interact with di
     423erent testbeds and clouds and manage their experiments. Furthermore, GENICloud demonstrates that there are, in fact, quite a few architectural similarities between di
     424erent testbeds and even clouds
    419425</li>
    420426<br>
     
    10301036<li>
    10311037<b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>
     1038, &quot;Performance of GENI Cloud Testbeds for Real Time Scientific Application.&quot;
     1039First GENI Research and Educational Experiment Workshop (GREE 2012), Los Angeles,
     10402012.
     1041
     1042
     1043<br><br><b>Abstract: </b>Dedicating high end servers for short-term execution of scientific applications such as weather forecasting wastes resources. Cloud platforms IaaS model seems well suited for applications which are executed on an irregular basis and for short duration. In this paper, we evaluate the performance of research testbed cloud platforms such as GENICloud and ORCA cloud clusters for our real-time scientific application of short-term weather forecasting called Nowcasting. In this paper, we evaluate the network capabilities of these research cloud testbeds for our real-time application of weather forecasting. In addition, we evaluate the computation time of executing Nowcasting on each cloud platform for weather data collected from real weather events. We also evaluate the total time taken to generate and transmit short-term forecast images to end users with live data from our own radar on campus. We also compare the performance of each of these clusters for Nowcasting with commercial cloud services such as Amazon's EC2. The results obtained from our measurement show that cloud testbeds are suitable for real-time application experiments to be carried out on a cloud platform.
     1044</li>
     1045<br>
     1046
     1047<li>
     1048<b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>
    10321049, &quot;Network capabilities of cloud services for a real time scientific application.&quot;
    1033105037th Annual IEEE Conference on Local Computer Networks, Clearwater Beach, FL, USA, IEEE,
     
    10391056<br>
    10401057
    1041 <li>
    1042 <b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>
    1043 , &quot;Performance of GENI Cloud Testbeds for Real Time Scientific Application.&quot;
    1044 First GENI Research and Educational Experiment Workshop (GREE 2012), Los Angeles,
    1045 2012.
    1046 
    1047 
    1048 <br><br><b>Abstract: </b>Dedicating high end servers for short-term execution of scientific applications such as weather forecasting wastes resources. Cloud platforms IaaS model seems well suited for applications which are executed on an irregular basis and for short duration. In this paper, we evaluate the performance of research testbed cloud platforms such as GENICloud and ORCA cloud clusters for our real-time scientific application of short-term weather forecasting called Nowcasting. In this paper, we evaluate the network capabilities of these research cloud testbeds for our real-time application of weather forecasting. In addition, we evaluate the computation time of executing Nowcasting on each cloud platform for weather data collected from real weather events. We also evaluate the total time taken to generate and transmit short-term forecast images to end users with live data from our own radar on campus. We also compare the performance of each of these clusters for Nowcasting with commercial cloud services such as Amazon's EC2. The results obtained from our measurement show that cloud testbeds are suitable for real-time application experiments to be carried out on a cloud platform.
    1049 </li>
    1050 <br>
    1051 
    10521058
    10531059
     
    20992105
    21002106<li>
     2107<b>Fei, Zongming and Yi, Ping and Yang, Jianjun</b>
     2108, &quot;A Performance Perspective on Choosing between Single Aggregate and Multiple Aggregates for GENI Experime nts.&quot;
     2109EAI Endorsed Transactions on Industrial Networks and Intelligent Systems,
     21102014.
     2111doi:10.4108/inis.1.1.e5.
     2112<a href="http://dx.doi.org/10.4108/inis.1.1.e5">http://dx.doi.org/10.4108/inis.1.1.e5</a>
     2113<br><br><b>Abstract: </b>The Global Environment for Network Innovations (GENI) provides a virtual laboratory for exploring future internets at scale. It consists of many geographically distributed aggregates for providing computing and networking resources for setting up network experiments. A key design question for GENI experimenters is where they should reserve the resources, and in particular whether they should reserve the resources from a single aggregate or from multiple aggregates. This not only depends on the nature of the experiment, but needs a better understanding of underlying GENI networks as well. This paper studies the performance of GENI networks, with a focus on the tradeoff between single aggregate and multiple aggregates in the design of GENI experiments from the performance perspective. The analysis of data collected will shed light on the decision process for designing GENI experiments.
     2114</li>
     2115<br>
     2116
     2117
     2118
     2119<li>
    21012120<b>Ghaffarinejad, A. and Syrotiuk, V. R.</b>
    21022121, &quot;Load Balancing in a Campus Network Using Software Defined Networking.&quot;
     
    22562275<li>
    22572276<b>Mambretti, Joe and Chen, Jim and Yeh, Fei</b>
     2277, &quot;Creating environments for innovation: Designing and implementing advanced experimental network research testbeds based on the Global Lambda Integrated Facility and the StarLight Exchange.&quot;
     2278Computer Networks,
     22792014.
     2280doi:10.1016/j.bjp.2013.12.024.
     2281<a href="http://dx.doi.org/10.1016/j.bjp.2013.12.024">http://dx.doi.org/10.1016/j.bjp.2013.12.024</a>
     2282<br><br><b>Abstract: </b>Large scale national and international experimental research environments are required to advance communication services and supporting network architecture, technology, and infrastructure. Theories and concepts are often explored using simulation and modeling techniques within labs or on small scale testbeds. However, while such testbeds are valuable resources for the research process, these facilities alone cannot provide an appropriate approximation of the real world conditions required to explore ideas at scale. Very large scale global, experimental network research capabilities are required to deeply investigate innovative concepts. For many years, network testbeds were created to address fairly specific, well defined, limited research goals, and they were implemented for fairly short periods. Recently, taking advantage of a number of macro information technology trends, such as virtualization and programmable resources, several network research communities have been developing innovative types of network research environments. Instead of designing traditional network testbeds, research communities are designing large scale, highly flexible distributed platforms that can be used to create many different types of testbeds. Also, rather than creating short term testbeds for limited research objectives, these new environments are being designed as long term persistent resources to support many types of experimental research. This paper describes the motivations for this trend, provides several examples of large scale distributed network research environments based on the Global Lambda Integrated Facility (GLIF) and the StarLight Exchange Facility, including the Global Environment for Network Innovation (GENI), and indicates emerging future trends for these types of environments.
     2283</li>
     2284<br>
     2285
     2286<li>
     2287<b>Mambretti, Joe and Chen, Jim and Yeh, Fei</b>
    22582288, &quot;Software-Defined Network Exchanges (SDXs): Architecture, services, capabilities, and foundation technologies.&quot;
    22592289Teletraffic Congress (ITC), 2014 26th International, IEEE,
     
    22652295<br>
    22662296
    2267 <li>
    2268 <b>Mambretti, Joe and Chen, Jim and Yeh, Fei</b>
    2269 , &quot;Creating environments for innovation: Designing and implementing advanced experimental network research testbeds based on the Global Lambda Integrated Facility and the StarLight Exchange.&quot;
    2270 Computer Networks,
    2271 2014.
    2272 doi:10.1016/j.bjp.2013.12.024.
    2273 <a href="http://dx.doi.org/10.1016/j.bjp.2013.12.024">http://dx.doi.org/10.1016/j.bjp.2013.12.024</a>
    2274 <br><br><b>Abstract: </b>Large scale national and international experimental research environments are required to advance communication services and supporting network architecture, technology, and infrastructure. Theories and concepts are often explored using simulation and modeling techniques within labs or on small scale testbeds. However, while such testbeds are valuable resources for the research process, these facilities alone cannot provide an appropriate approximation of the real world conditions required to explore ideas at scale. Very large scale global, experimental network research capabilities are required to deeply investigate innovative concepts. For many years, network testbeds were created to address fairly specific, well defined, limited research goals, and they were implemented for fairly short periods. Recently, taking advantage of a number of macro information technology trends, such as virtualization and programmable resources, several network research communities have been developing innovative types of network research environments. Instead of designing traditional network testbeds, research communities are designing large scale, highly flexible distributed platforms that can be used to create many different types of testbeds. Also, rather than creating short term testbeds for limited research objectives, these new environments are being designed as long term persistent resources to support many types of experimental research. This paper describes the motivations for this trend, provides several examples of large scale distributed network research environments based on the Global Lambda Integrated Facility (GLIF) and the StarLight Exchange Facility, including the Global Environment for Network Innovation (GENI), and indicates emerging future trends for these types of environments.
    2275 </li>
    2276 <br>
    2277 
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    24612480
    24622481<li>
     2482<b>Seetharam, Sripriya</b>
     2483, &quot;Application-Driven Overlay Network as a Service for Data-Intensive Science.&quot;
     2484
     24852014.
     2486
     2487
     2488<br><br><b>Abstract: </b>Campuses are increasingly adopting hybrid cloud architectures for supporting data-intensive science applications that require &#x6f;&#x0308;n-demand&#x20;&#x0308;resources, which are not always available locally on-site. Policies at the campus edge for handling multiple such applications competing for remote resources can cause bottlenecks across applications. These bottlenecks can be proactively avoided with pertinent profiling, monitoring and control of application flows using the emerging paradigm of software-defined networking (SDN). In this thesis, we leverage SDN principles in the design and implementation of an &#x41;&#x0308;pplication-driven Overlay Network-as-a-Service&#x20;&#x0308;(ADON) framework that can manage the hybrid cloud requirements of multiple applications in a scalable and extensible manner. ADON's main features include: programmable &#x63;&#x0308;ustom templates&#x20;&#x0308;and a &#x76;&#x0308;irtual tenant handler&#x20;&#x0308;algorithm. Our solution approach in ADON involves scheduling transit selection and traffic engineering at the campus-edge based on real-time policy control that ensures predictable application performance delivery for multi-tenant traffic profiles. We also present a market-driven (distributed) resource optimization scheme that can address the Internet-scale scalability problems of handling resource requests of multiple data-intensive applications within a desktop-as-a-service cloud environment. We show how our optimization scheme can increase the system performance and user experience levels using metrics such as 'Service Response Time' and 'Net-Utility'. Lastly,we discuss ADON effectiveness validation with an implementation on a wide-area overlay network testbed featuring temporal behavior of multi-tenant traffic burst arrivals. We conclude by presenting hybrid cloud implementation best practices that ease the orchestration of network programmability for campus network providers and data-intensive application users.
     2489</li>
     2490<br>
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     2493
     2494<li>
    24632495<b>Seetharam, Sripriya and Calyam, Prasad and Beyene, Tsegereda</b>
    24642496, &quot;ADON: Application-Driven Overlay Network-as-a-Service for Data-Intensive Science.&quot;
     
    26612693<a href="http://dx.doi.org/10.1109/gree.2014.16">http://dx.doi.org/10.1109/gree.2014.16</a>
    26622694<br><br><b>Abstract: </b>In the new cloud computing paradigm, outsourcing computation is a fundamental principle. Among its various aspects, the correctness of the computation result remains paramount. This motivates the birth of verifiable computation, which aims at efficiently checking the result for general-purpose computation. Although significant progress has been made in verifiable computation towards practice, the verifier's workload still remains too high. Only through batching or amortizing the very expensive investment over a large number of computation instances, can the verifiers cost be less than re-computing the computation task from the scratch. In the work of delegation of verification (PODC'13), Xu et al. proposes that the client can also outsource (again) the verification to a third party. However, whether this idea is feasible in large scale network is not clear. In this paper, we propose to adopt the Global Environment for Network Innovation (GENI) infrastructure, which is known as a mature virtual laboratory for exploring future Internet to investigate the feasibility of outsourcing computation/verification in large scale networks.
     2695</li>
     2696<br>
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     2699
     2700<li>
     2701<b>Xu, Ke and Wang, Kuang-Ching and Amin, Rahul and Martin, Jim and Izard, Ryan</b>
     2702, &quot;A Fast Cloud-based Network Selection Scheme Using Coalition Formation Games in Vehicular Networks.&quot;
     2703IEEE Transactions on Vehicular Technology, IEEE,
     27042014.
     2705doi:10.1109/tvt.2014.2379953.
     2706<a href="http://dx.doi.org/10.1109/tvt.2014.2379953">http://dx.doi.org/10.1109/tvt.2014.2379953</a>
     2707<br><br><b>Abstract: </b>Leveraging multiple wireless technologies and radio access networks, vehicles on the move have the potential to get robust connectivity and continuous service. To support the demands of as many vehicles as possible, an efficient and fast network selection scheme is critically important to achieve high performance and efficiency. So far, prior works have primarily focused on design of optimization algorithms and utility functions for either user or network performance. Most such studies do not address the complexities involved in the acquisition of needed information and the execution of algorithms, making them unsuitable for practical implementations in vehicles. This paper proposes a fast, cloud-based network selection scheme for vehicular networks. By leveraging a compute cloud's abundant computing and data storage resources, vehicles can leverage wider scope network information for decision making. Vehicles select best access networks through a coalition formation game approach. A one-iteration fast convergence algorithm is proposed to achieve the final state of coalition structure in the game. Through extensive simulation, the proposed network selection scheme was shown to balance system throughput and fairness with built-in utility division rule of the framework. The algorithm efficiency showed eight-fold enhancement over a conventional coalition formation algorithm. Such features validate the potential of implementation in practice.
    26632708</li>
    26642709<br>
     
    36133658<li>
    36143659<b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>
     3660, &quot;Performance of GENI Cloud Testbeds for Real Time Scientific Application.&quot
     3661First GENI Research and Educational Experiment Workshop (GREE 2012), Los Angeles,
     36622012.
     3663
     3664</li>
     3665<br>
     3666
     3667<li>
     3668<b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>
    36153669, &quot;Network capabilities of cloud services for a real time scientific application.&quot
    3616367037th Annual IEEE Conference on Local Computer Networks, Clearwater Beach, FL, USA, IEEE,
    361736712012.
    36183672doi:10.1109/lcn.2012.6423665.
    3619 </li>
    3620 <br>
    3621 
    3622 <li>
    3623 <b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>
    3624 , &quot;Performance of GENI Cloud Testbeds for Real Time Scientific Application.&quot
    3625 First GENI Research and Educational Experiment Workshop (GREE 2012), Los Angeles,
    3626 2012.
    3627 
    36283673</li>
    36293674<br>
     
    45184563
    45194564<li>
     4565<b>Fei, Zongming and Yi, Ping and Yang, Jianjun</b>
     4566, &quot;A Performance Perspective on Choosing between Single Aggregate and Multiple Aggregates for GENI Experime nts.&quot
     4567EAI Endorsed Transactions on Industrial Networks and Intelligent Systems,
     45682014.
     4569doi:10.4108/inis.1.1.e5.
     4570</li>
     4571<br>
     4572
     4573
     4574
     4575<li>
    45204576<b>Ghaffarinejad, A. and Syrotiuk, V. R.</b>
    45214577, &quot;Load Balancing in a Campus Network Using Software Defined Networking.&quot
     
    46514707<li>
    46524708<b>Mambretti, Joe and Chen, Jim and Yeh, Fei</b>
     4709, &quot;Creating environments for innovation: Designing and implementing advanced experimental network research testbeds based on the Global Lambda Integrated Facility and the StarLight Exchange.&quot
     4710Computer Networks,
     47112014.
     4712doi:10.1016/j.bjp.2013.12.024.
     4713</li>
     4714<br>
     4715
     4716<li>
     4717<b>Mambretti, Joe and Chen, Jim and Yeh, Fei</b>
    46534718, &quot;Software-Defined Network Exchanges (SDXs): Architecture, services, capabilities, and foundation technologies.&quot
    46544719Teletraffic Congress (ITC), 2014 26th International, IEEE,
    465547202014.
    46564721doi:10.1109/itc.2014.6932970.
    4657 </li>
    4658 <br>
    4659 
    4660 <li>
    4661 <b>Mambretti, Joe and Chen, Jim and Yeh, Fei</b>
    4662 , &quot;Creating environments for innovation: Designing and implementing advanced experimental network research testbeds based on the Global Lambda Integrated Facility and the StarLight Exchange.&quot
    4663 Computer Networks,
    4664 2014.
    4665 doi:10.1016/j.bjp.2013.12.024.
    46664722</li>
    46674723<br>
     
    48244880
    48254881<li>
     4882<b>Seetharam, Sripriya</b>
     4883, &quot;Application-Driven Overlay Network as a Service for Data-Intensive Science.&quot
     4884
     48852014.
     4886
     4887</li>
     4888<br>
     4889
     4890
     4891
     4892<li>
    48264893<b>Seetharam, Sripriya and Calyam, Prasad and Beyene, Tsegereda</b>
    48274894, &quot;ADON: Application-Driven Overlay Network-as-a-Service for Data-Intensive Science.&quot
     
    499250592014.
    49935060doi:10.1109/gree.2014.16.
     5061</li>
     5062<br>
     5063
     5064
     5065
     5066<li>
     5067<b>Xu, Ke and Wang, Kuang-Ching and Amin, Rahul and Martin, Jim and Izard, Ryan</b>
     5068, &quot;A Fast Cloud-based Network Selection Scheme Using Coalition Formation Games in Vehicular Networks.&quot
     5069IEEE Transactions on Vehicular Technology, IEEE,
     50702014.
     5071doi:10.1109/tvt.2014.2379953.
    49945072</li>
    49955073<br>