Changes between Version 24 and Version 25 of GENIBibliography


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Timestamp:
04/08/15 14:28:43 (5 years ago)
Author:
Mark Berman
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  • GENIBibliography

    v24 v25  
    635635
    636636<li>
     637<b>Patali, Rohit</b>
     638, &quot;Utility-Directed Resource Allocation in Virtual Desktop Clouds.&quot;
     639
     6402011.
     641
     642<a href="https://etd.ohiolink.edu/!etd.send&#x005F;file?accession=osu1306872632">https://etd.ohiolink.edu/!etd.send&#x005F;file?accession=osu1306872632</a>
     643<br><br><b>Abstract: </b>User communities are rapidly transitioning their ” traditional desktops” that have dedicated hardware and software installations into ” virtual desktop clouds” (VDCs) that are accessible via thin-clients. To allocate and manage VDC resources for Internet-scale desktop delivery, existing work focuses mainly on managing server-side resources based on utility functions of CPU and memory loads, and do not consider network health and thin-client user experience. Resource allocations without combined utility-directed information of system loads, network health and thin-client user experience in VDC platforms inevitably results in costly guesswork and overprovisioning of resources. In this thesis, an analytical model i.e., ” Utility-Directed Resource Allocation Model (U-RAM)” is presented to solve the combined utility-directed resource allocation problem within VDCs. The solution uses an iterative algorithm that leverages utility functions of system, network and human components obtained using a novel virtual desktop performance benchmarking toolkit i.e., ” VDBench”. The combined utility functions are used to direct decision schemes based on Kuhn-Tucker optimality conditions for creating user desktop pools and determining optimal resource allocation size/location. U-RAM is evaluated in a VDC testbed featuring: (a) popular user applications (Spreadsheet Calculator, Internet Browser, Media Player, Interactive Visualization), and (b) TCP/UDP based thin-client protocols (RDP, RGS, PCoIP) under a variety of user load and network health conditions. Evaluation results demonstrate that U-RAM solution maximizes VDC scalability i.e., 'VDs per core density', and 'user connections quantity', while delivering satisfactory thin-client user experience.
     644</li>
     645<br>
     646
     647
     648
     649<li>
    637650<b>Paul, Subharthi and Pan, Jianli and Jain, Raj</b>
    638651, &quot;Architectures for the future networks and the next generation Internet: A survey.&quot;
     
    10171030<li>
    10181031<b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>
    1019 , &quot;Performance of GENI Cloud Testbeds for Real Time Scientific Application.&quot;
    1020 First GENI Research and Educational Experiment Workshop (GREE 2012), Los Angeles,
    1021 2012.
    1022 
    1023 
    1024 <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.
    1025 </li>
    1026 <br>
    1027 
    1028 <li>
    1029 <b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>
    10301032, &quot;Network capabilities of cloud services for a real time scientific application.&quot;
    1031103337th Annual IEEE Conference on Local Computer Networks, Clearwater Beach, FL, USA, IEEE,
     
    10371039<br>
    10381040
     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;
     1044First GENI Research and Educational Experiment Workshop (GREE 2012), Los Angeles,
     10452012.
     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
    10391052
    10401053
     
    13391352
    13401353<li>
     1354<b>Venkataraman, Aishwarya</b>
     1355, &quot;Defragmentation of Resources in Virtual Desktop clouds for Cost-aware Utility-maximal Allocation.&quot;
     1356
     13572012.
     1358
     1359<a href="https://etd.ohiolink.edu/!etd.send&#x005F;file?accession=osu1339747492">https://etd.ohiolink.edu/!etd.send&#x005F;file?accession=osu1339747492</a>
     1360<br><br><b>Abstract: </b>Cloud Service Providers (CSPs) make virtual desktop cloud (VDC) resource provisioning decisions within desktop pools based on user groups and their application pro- files. Such provisioning is aimed to not only satisfy acceptable user quality of experience (QoE) levels and provide high scalability, but also provide ” knobs” to CSPs to operate according their economic policies. The next challenge is to place user VD requests in an optimal and fast manner across distributed data centers. The placement decisions are influenced by session latency, load balancing and operation cost constraints. In this work, we identify the resource fragmentation problem that occurs when placement is done opportunistically to minimize provisioning time and deliver satisfactory user QoE. To solve this problem, which inherently is an NP-Hard problem, we propose a defragmentation scheme that has fast convergence time and has three levels of complexity: (i) ” Economics-directed resource allocation model” (E-RAM) that considers economic policies while optimizing resource provisioning within a data center (ii) ” Cost-aware Utility-maximal Local Placement” to optimize resource provisioning between multiple data centers, and (iii) ” Costaware Utility-maximal Global Placement with Migration” to optimize resource provisioning using cost-aware and utility-maximal VD re-allocations and migrations - to increase scalability and performance. We evaluate our E-RAM, Cost-aware Utility-maximal Local and Global Placement schemes using a novel ” VDC-Sim” simulator that we have developed in this study. Our simulations leverage profiles of user groups and their applications within desktop pools, obtained from a real VDC testbed. We also implemented our schemes in a real cloud infrastructure. Our results demonstrate that defragmentation is an important optimization step and defragmentation together with E-RAM and our Cost-aware Utilitymaximal placement schemes can enable CSPs to achieve optimal user QoE, higher VDC scalability, improved system performance and resilience.
     1361</li>
     1362<br>
     1363
     1364
     1365
     1366<li>
    13411367<b>Vulimiri, Ashish and Michel, Oliver and Godfrey, P. Brighten and Shenker, Scott</b>
    13421368, &quot;More is Less: Reducing Latency via Redundancy.&quot;
     
    14751501<b>Jin, Ruofan and Wang, Bing</b>
    14761502, &quot;Malware Detection for Mobile Devices Using Software-Defined Networking.&quot;
     15032013 Proceedings Second GENI Research and Educational Experiment Workshop, Salt Lake City, UT, IEEE,
     15042013.
     1505doi:10.1109/GREE.2013.24.
     1506<a href="http://dx.doi.org/10.1109/GREE.2013.24">http://dx.doi.org/10.1109/GREE.2013.24</a>
     1507
     1508</li>
     1509<br>
     1510
     1511<li>
     1512<b>Jin, Ruofan and Wang, Bing</b>
     1513, &quot;Malware Detection for Mobile Devices Using Software-Defined Networking.&quot;
    14771514Research and Educational Experiment Workshop (GREE), 2013 Second GENI, IEEE,
    147815152013.
     
    14831520<br>
    14841521
    1485 <li>
    1486 <b>Jin, Ruofan and Wang, Bing</b>
    1487 , &quot;Malware Detection for Mobile Devices Using Software-Defined Networking.&quot;
    1488 2013 Proceedings Second GENI Research and Educational Experiment Workshop, Salt Lake City, UT, IEEE,
    1489 2013.
    1490 doi:10.1109/GREE.2013.24.
    1491 <a href="http://dx.doi.org/10.1109/GREE.2013.24">http://dx.doi.org/10.1109/GREE.2013.24</a>
    1492 
    1493 </li>
    1494 <br>
    1495 
    14961522
    14971523
     
    16141640
    16151641<li>
     1642<b>Rajagopalan, Sudharsan</b>
     1643, &quot;Leveraging OpenFlow for Resource Placement of Virtual Desktop Cloud Applications.&quot;
     1644
     16452013.
     1646
     1647<a href="http://rave.ohiolink.edu/etdc/view?acc&#x005F;num=osu1367456412">http://rave.ohiolink.edu/etdc/view?acc&#x005F;num=osu1367456412</a>
     1648<br><br><b>Abstract: </b>Popular applications such as email, photo/video galleries, and file storage are increasingly being supported by cloud platforms in residential, academia and industry communities. The next frontier for these user communities will be to transition `traditional desktops' that have dedicated hardware and software configurations into `virtual desktop clouds' that are accessible via thin-clients. In this paper, we describe an Intelligent resource placement framework for thin-client based virtual desktops. The framework leverages principles of software defined networking and features a `unified resource broker' that uses special `marker packets' for: (a) ” route setup” when handling non-IP traffic between thin-client sites and data centers, (b) ” path selection” and ” load balancing” of virtual desktop flows to improve performance of interactive applications and video playback, and to cope with faults such as link-failures or Denial of Service cyber-attacks. The Framework has the ability to provisioning OpenFlow paths with less Service Response times for VD Requests. Our Framework In addition, we detail our framework implementation within a virtual desktop cloud (VDC) setup in a multi-domain Global Environment for Network Innovations (GENI) Future Internet testbed spanning backbone and access networks with a automation and centralized control using a tool called VDC-Sim. We present empirical results from our experimentation that leverages OpenFlow programmable networking, as well as cross-traffic capabilities for validating our framework in GENI under realistic settings. Our results demonstrate the importance of scheduling regulated measurements that can be used for intelligent resource placement decisions. Our results also show the feasibility and benefits of using OpenFlow controller applications for path selection and load balancing between thin-client sites and data centers in VDCs. The thesis also shows how our OpenFlow Framework can used for other cloud applications using GridFTP application over WAN as a Case Study.
     1649</li>
     1650<br>
     1651
     1652
     1653
     1654<li>
    16161655<b>Ricci, Robert and Wong, Gary and Stoller, Leigh and Duerig, Jonathon</b>
    16171656, &quot;An Architecture For International Federation of Network Testbeds.&quot;
     
    16271666
    16281667<li>
     1668<b>Selvadhurai, Arunprasaath</b>
     1669, &quot;Network Measurement Tool Components for Enabling Performance Intelligence within Cloud-based Applications.&quot;
     1670
     16712013.
     1672
     1673<a href="http://rave.ohiolink.edu/etdc/view?acc&#x005F;num=osu1367446588">http://rave.ohiolink.edu/etdc/view?acc&#x005F;num=osu1367446588</a>
     1674<br><br><b>Abstract: </b>Popular applications such as email, photo/video galleries, and file storage are increasingly being supported by cloud platforms in residential, academic and industry communities. The next frontier for these user communities will be to transition `traditional desktops' that have dedicated hardware and software configurations into `virtual desktop clouds' that are accessible via thin-clients. In our thesis, we show how the underlying measurement services, with some additional capabilities, can be used as intelligent agents to provide network intelligence within thin-client based virtual desktops applications. The framework leverages principles of software defined networking and features an `unified resource broker' that uses special `marker packets' for: (a) ” route setup” when handling non-IP traffic between thin-client sites and data centers, (b) ” path selection” and ” load balancing” of virtual desktop flows to improve the performance of interactive applications and video playback, and to cope with faults such as link-failures or Denial-of-Service cyber-attacks. In addition, we detail our framework implementation within a virtual desktop cloud (VDC) in a multi-domain Global Environment for Network Innovations (GENI). We present empirical results from our experimentation that leverages OpenFlow programmable networking, as well as OnTimeMeasure instrumentation-and-measurement capabilities for validating our framework in GENI under realistic settings. Our results demonstrate the importance of scheduling regulated measurements that can be used for intelligent resource placement decisions. Our results also show the feasibility and benefits of using the measurement services for effective path selection and load balancing between thin-client sites and data centers in VDCs and simulation applications.
     1675</li>
     1676<br>
     1677
     1678
     1679
     1680<li>
    16291681<b>Sterbenz, JamesP and &#x43;&#x0327;etinkaya, EgemenK and Hameed, MahmoodA and Jabbar, Abdul and Qian, Shi and Rohrer, JustinP</b>
    16301682, &quot;Evaluation of network resilience, survivability, and disruption tolerance: analysis, topology generation, simulation, and experimentation.&quot;
     
    19822034
    19832035<li>
     2036<b>Calyam, Prasad and Rajagopalan, Sudharsan and Seetharam, Sripriya and Selvadhurai, Arunprasath and Salah, Khaled and Ramnath, Rajiv</b>
     2037, &quot;VDC-Analyst: Design and verification of virtual desktop cloud resource allocations.&quot;
     2038Computer Networks,
     20392014.
     2040doi:10.1016/j.comnet.2014.02.022.
     2041<a href="http://dx.doi.org/10.1016/j.comnet.2014.02.022">http://dx.doi.org/10.1016/j.comnet.2014.02.022</a>
     2042<br><br><b>Abstract: </b>One of the significant challenges for Cloud Service Providers (CSPs) hosting ” virtual desktop cloud” (VDC) infrastructures is to deliver a satisfactory quality of experience (QoE) to the user. In order to maximize the user QoE without expensive resource overprovisioning, there is a need to design and verify resource allocation schemes for a comprehensive set of VDC configurations. In this paper, we present ” VDC-Analyst”, a novel tool that can capture critical quality metrics such as Net Utility and Service Response Time, which can be used to quantify VDC platform readiness. This tool allows CSPs, researchers and educators to design and verify various resource allocation schemes using both simulation and emulation in two modes: ” Run Simulation” and ” Run Experiment”, respectively. The Run Simulation mode allows users to test and visualize resource provisioning and placement schemes on a simulation framework. Run Experiment mode allows testing on a real software-defined network testbed using emulated virtual desktop application traffic to create a realistic environment. Results from using our tool demonstrate that a significant increase in perceived user QoE can be achieved by using a combination of the following techniques incorporated in the tool: (i) optimizing Net Utility through a ” Cost-Aware Utility-Maximal Resource Allocation Algorithm”, (ii) estimating values for Service Response Time using a ” Multi-stage Queuing Model”, and (iii) appropriate load balancing through software-defined networking adaptations in the VDC testbed.
     2043</li>
     2044<br>
     2045
     2046
     2047
     2048<li>
    19842049<b>Collings, Jake and Liu, Jun</b>
    19852050, &quot;An OpenFlow-Based Prototype of SDN-Oriented Stateful Hardware Firewalls.&quot;
     
    22272292
    22282293<li>
     2294<b>Martin, Vincent and Coulaby, Adama and Schaff, Nathan and Tan, Chiu C. and Lin, Shan</b>
     2295, &quot;Bandwidth Prediction on a WiMAX Network.&quot;
     2296Mobile Ad Hoc and Sensor Systems (MASS), 2014 IEEE 11th International Conference on, IEEE,
     22972014.
     2298doi:10.1109/mass.2014.75.
     2299<a href="http://dx.doi.org/10.1109/mass.2014.75">http://dx.doi.org/10.1109/mass.2014.75</a>
     2300<br><br><b>Abstract: </b>The IEEE 802.16 standard (WiMAX) is an important next-generation networking technology which promises highspeed network access for both mobile and fixed users. In this paper we present a method to estimate link quality for devices connected to Temple University's WiMAX network as they traverse both the main campus and the city of Philadelphia via foot and motor vehicle. This is accomplished by first measuring receive signal strength indicator (RSSI), carrier to interference plus noise ratio (CINR), and bandwidth. After capturing these values, we then analyze the data to provide an estimation of the actual system rate. We then present an approach to predict future states of link quality both while stationary at Temple and when traversing Philadelphia via bus.
     2301</li>
     2302<br>
     2303
     2304
     2305
     2306<li>
    22292307<b>Maziku, H. and Shetty, S.</b>
    22302308, &quot;Network Aware VM Migration in Cloud Data Centers.&quot;
     
    23872465
    238824662014.
    2389 
     2467doi:10.1109/CloudNet.2014.6969014.
    23902468<a href="http://people.cs.missouri.edu/&#x63;&#x0303;alyamp/publications/adon-cloudnet14.pdf">http://people.cs.missouri.edu/&#x63;&#x0303;alyamp/publications/adon-cloudnet14.pdf</a>
    23912469<br><br><b>Abstract: </b>Campuses are increasingly adopting hybrid cloud architectures for supporting data-intensive science applications that require ” on-demand” 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 software-defined networking principles. In this paper, we present an ” Application-driven Overlay Network-as-a-Service” (ADON) that can manage the hybrid cloud requirements of multiple applications in a scalable and extensible manner using features such as: programmable ” custom templates” and a ” virtual tenant handler”. Our solution approach involves scheduling transit selection and traffic engi- neering at the campus-edge based on real-time policy control that ensures predictable application performance delivery for multi-tenant traffic profiles. We validate our ADON approach with an implementation on a wide-area overlay network testbed across two campuses, and present a workflow that eases the orchestration of network programmability for campus network providers and data-intensive application users. Lastly, we present an emulation study of the ADON effectiveness in handling temporal behavior of multi-tenant traffic burst arrivals using profiles from a diverse set of actual data-intensive applications.
     
    25532631<li>
    25542632<b>Xin, Yufeng and Baldin, Ilya and Heermann, Chris and Mandal, Anirban and Ruth, Paul</b>
     2633, &quot;Capacity of Inter-cloud Layer-2 Virtual Networking.&quot;
     2634Proceedings of the 2014 ACM SIGCOMM Workshop on Distributed Cloud Computing, Chicago, Illinois, USA, ACM, New York, NY, USA,
     26352014.
     2636doi:10.1145/2627566.2627573.
     2637<a href="http://dx.doi.org/10.1145/2627566.2627573">http://dx.doi.org/10.1145/2627566.2627573</a>
     2638<br><br><b>Abstract: </b>Due to the economy of scale of Ethernet networks and available dynamic circuit capability from the major national research and educational networks, VLAN (Virtual LAN) based virtual networking solution has been successfully adopted in some advanced distributed cloud systems. However, there are two major constraints in this adaptation: (1) dynamic circuit service is far from pervasive; (2) there is only limited VLAN tags offered by regional network service providers. In this paper, after examining layer-2 networking in large-scale distributed cloud environments, we present a graph theoretical model to study the network capacity in terms of the number of inter-cloud connections that can co-exist. We further design the algorithms to achieve this capacity for both point-to-point and multi-point inter-cloud connections in both static and dynamic scenarios. We also study a general topology embedding problem based on this model. As tagging is a common mechanism for isolating communication channels in other network layers, the proposed models and algorithms can be extended to optical and IP networks.
     2639</li>
     2640<br>
     2641
     2642<li>
     2643<b>Xin, Yufeng and Baldin, Ilya and Heermann, Chris and Mandal, Anirban and Ruth, Paul</b>
    25552644, &quot;Scaling up applications over distributed clouds with dynamic layer-2 exchange and broadcast service.&quot;
    25562645Teletraffic Congress (ITC), 2014 26th International, IEEE,
     
    25622651<br>
    25632652
    2564 <li>
    2565 <b>Xin, Yufeng and Baldin, Ilya and Heermann, Chris and Mandal, Anirban and Ruth, Paul</b>
    2566 , &quot;Capacity of Inter-cloud Layer-2 Virtual Networking.&quot;
    2567 Proceedings of the 2014 ACM SIGCOMM Workshop on Distributed Cloud Computing, Chicago, Illinois, USA, ACM, New York, NY, USA,
    2568 2014.
    2569 doi:10.1145/2627566.2627573.
    2570 <a href="http://dx.doi.org/10.1145/2627566.2627573">http://dx.doi.org/10.1145/2627566.2627573</a>
    2571 <br><br><b>Abstract: </b>Due to the economy of scale of Ethernet networks and available dynamic circuit capability from the major national research and educational networks, VLAN (Virtual LAN) based virtual networking solution has been successfully adopted in some advanced distributed cloud systems. However, there are two major constraints in this adaptation: (1) dynamic circuit service is far from pervasive; (2) there is only limited VLAN tags offered by regional network service providers. In this paper, after examining layer-2 networking in large-scale distributed cloud environments, we present a graph theoretical model to study the network capacity in terms of the number of inter-cloud connections that can co-exist. We further design the algorithms to achieve this capacity for both point-to-point and multi-point inter-cloud connections in both static and dynamic scenarios. We also study a general topology embedding problem based on this model. As tagging is a common mechanism for isolating communication channels in other network layers, the proposed models and algorithms can be extended to optical and IP networks.
    2572 </li>
    2573 <br>
    2574 
    25752653
    25762654
     
    26292707<br>
    26302708<a id="full-2015"><H2>GENI Publications for 2015</H2></a>
     2709
     2710
     2711<li>
     2712<b>Edwards, Sarah and Liu, Xuan and Riga, Niky</b>
     2713, &quot;Creating Repeatable Computer Science and Networking Experiments on Shared, Public Testbeds.&quot;
     2714SIGOPS Oper. Syst. Rev., ACM, New York, NY, USA,
     27152015.
     2716doi:10.1145/2723872.2723884.
     2717<a href="http://dx.doi.org/10.1145/2723872.2723884">http://dx.doi.org/10.1145/2723872.2723884</a>
     2718<br><br><b>Abstract: </b>There are many compelling reasons to use a shared, public testbed such as GENI, Emulab, or PlanetLab to conduct experiments in computer science and networking. These testbeds support creating experiments with a large and diverse set of resources. Moreover these testbeds are constructed to inherently support the repeatability of experiments as required for scientifically sound research. Finally, the artifacts needed for a researcher to repeat their own experiment can be shared so that others can readily repeat the experiment in the same environment. However using a shared, public testbed is different from conducting experiments on resources either owned by the experimenter or someone the experimenter knows. Experiments on shared, public testbeds are more likely to use large topologies, use scarce resources, and need to be tolerant to outages and maintenances in the testbed. In addition, experimenters may not have access to low-level debugging information. This paper describes a methodology for new experimenters to write and deploy repeatable and sharable experiments which deal with these challenges by: having a clear plan; automating the execution and analysis of an experiment by following best practices from software engineering and system administration; and building scalable experiments. In addition, the paper describes a case study run on the GENI testbed which illustrates the methodology described.
     2719</li>
     2720<br>
     2721
    26312722
    26322723
     
    26392730<a href="http://winlab.rutgers.edu/&#x73;&#x0303;hreya/comsnets.pdf">http://winlab.rutgers.edu/&#x73;&#x0303;hreya/comsnets.pdf</a>
    26402731<br><br><b>Abstract: </b>This paper discusses the design challenges associated with supporting advanced mobility services in the future Internet. The recent transition of the Internet from the fixed host-server model to one in which mobile platforms are the norm motivates a next-generation protocol architecture which provides integrated and efficient support for advanced mobility services. Key wireless access and mobility usage scenarios are identified including host mobility, multihoming, vehicular access and context addressability, and key protocol support requirements are identified in each case. The MobilityFirst (MF) architecture being developed under the National Science Foundation's future Internet Architecture (FIA) program is proposed as a possible realization that meets the identified requirements. MF protocol specifics are given for each wireless/mobile use case, along with sample evaluation results demonstrating achievable performance benefits.
     2732</li>
     2733<br>
     2734
     2735
     2736
     2737<li>
     2738<b>Ricci, Robert and Wong, Gary and Stoller, Leigh and Webb, Kirk and Duerig, Jonathon and Downie, Keith and Hibler, Mike</b>
     2739, &quot;Apt: A Platform for Repeatable Research in Computer Science.&quot;
     2740SIGOPS Oper. Syst. Rev., ACM, New York, NY, USA,
     27412015.
     2742doi:10.1145/2723872.2723885.
     2743<a href="http://dx.doi.org/10.1145/2723872.2723885">http://dx.doi.org/10.1145/2723872.2723885</a>
     2744<br><br><b>Abstract: </b>Repeating research in computer science requires more than just code and data: it requires an appropriate environment in which to run experiments. In some cases, this environment appears fairly straightforward: it consists of a particular operating system and set of required libraries. In many cases, however, it is considerably more complex: the execution environment may be an entire network, may involve complex and fragile configuration of the dependencies, or may require large amounts of resources in terms of computation cycles, network bandwidth, or storage. Even the &#x73;&#x0308;traightforward&#x20;&#x0308;case turns out to be surprisingly intricate: there may be explicit or hidden dependencies on compilers, kernel quirks, details of the ISA, etc. The result is that when one tries to repeat published results, creating an environment sufficiently similar to one in which the experiment was originally run can be troublesome; this problem only gets worse as time passes. What the computer science community needs, then, are environments that have the explicit goal of enabling repeatable research. This paper outlines the problem of repeatable research environments, presents a set of requirements for such environments, and describes one facility that attempts to address them.
    26412745</li>
    26422746<br>
     
    31743278
    31753279<li>
     3280<b>Patali, Rohit</b>
     3281, &quot;Utility-Directed Resource Allocation in Virtual Desktop Clouds.&quot
     3282
     32832011.
     3284
     3285</li>
     3286<br>
     3287
     3288
     3289
     3290<li>
    31763291<b>Paul, Subharthi and Pan, Jianli and Jain, Raj</b>
    31773292, &quot;Architectures for the future networks and the next generation Internet: A survey.&quot
     
    34983613<li>
    34993614<b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>
     3615, &quot;Network capabilities of cloud services for a real time scientific application.&quot
     361637th Annual IEEE Conference on Local Computer Networks, Clearwater Beach, FL, USA, IEEE,
     36172012.
     3618doi: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>
    35003624, &quot;Performance of GENI Cloud Testbeds for Real Time Scientific Application.&quot
    35013625First GENI Research and Educational Experiment Workshop (GREE 2012), Los Angeles,
    350236262012.
    35033627
    3504 </li>
    3505 <br>
    3506 
    3507 <li>
    3508 <b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>
    3509 , &quot;Network capabilities of cloud services for a real time scientific application.&quot
    3510 37th Annual IEEE Conference on Local Computer Networks, Clearwater Beach, FL, USA, IEEE,
    3511 2012.
    3512 doi:10.1109/lcn.2012.6423665.
    35133628</li>
    35143629<br>
     
    37703885
    37713886<li>
     3887<b>Venkataraman, Aishwarya</b>
     3888, &quot;Defragmentation of Resources in Virtual Desktop clouds for Cost-aware Utility-maximal Allocation.&quot
     3889
     38902012.
     3891
     3892</li>
     3893<br>
     3894
     3895
     3896
     3897<li>
    37723898<b>Vulimiri, Ashish and Michel, Oliver and Godfrey, P. Brighten and Shenker, Scott</b>
    37733899, &quot;More is Less: Reducing Latency via Redundancy.&quot
     
    38864012<b>Jin, Ruofan and Wang, Bing</b>
    38874013, &quot;Malware Detection for Mobile Devices Using Software-Defined Networking.&quot
    3888 Research and Educational Experiment Workshop (GREE), 2013 Second GENI, IEEE,
    3889 2013.
    3890 doi:10.1109/gree.2013.24.
     40142013 Proceedings Second GENI Research and Educational Experiment Workshop, Salt Lake City, UT, IEEE,
     40152013.
     4016doi:10.1109/GREE.2013.24.
    38914017</li>
    38924018<br>
     
    38954021<b>Jin, Ruofan and Wang, Bing</b>
    38964022, &quot;Malware Detection for Mobile Devices Using Software-Defined Networking.&quot
    3897 2013 Proceedings Second GENI Research and Educational Experiment Workshop, Salt Lake City, UT, IEEE,
    3898 2013.
    3899 doi:10.1109/GREE.2013.24.
     4023Research and Educational Experiment Workshop (GREE), 2013 Second GENI, IEEE,
     40242013.
     4025doi:10.1109/gree.2013.24.
    39004026</li>
    39014027<br>
     
    40034129
    40044130<li>
     4131<b>Rajagopalan, Sudharsan</b>
     4132, &quot;Leveraging OpenFlow for Resource Placement of Virtual Desktop Cloud Applications.&quot
     4133
     41342013.
     4135
     4136</li>
     4137<br>
     4138
     4139
     4140
     4141<li>
    40054142<b>Ricci, Robert and Wong, Gary and Stoller, Leigh and Duerig, Jonathon</b>
    40064143, &quot;An Architecture For International Federation of Network Testbeds.&quot
     
    40144151
    40154152<li>
     4153<b>Selvadhurai, Arunprasaath</b>
     4154, &quot;Network Measurement Tool Components for Enabling Performance Intelligence within Cloud-based Applications.&quot
     4155
     41562013.
     4157
     4158</li>
     4159<br>
     4160
     4161
     4162
     4163<li>
    40164164<b>Sterbenz, JamesP and &#x43;&#x0327;etinkaya, EgemenK and Hameed, MahmoodA and Jabbar, Abdul and Qian, Shi and Rohrer, JustinP</b>
    40174165, &quot;Evaluation of network resilience, survivability, and disruption tolerance: analysis, topology generation, simulation, and experimentation.&quot
     
    43154463
    43164464<li>
     4465<b>Calyam, Prasad and Rajagopalan, Sudharsan and Seetharam, Sripriya and Selvadhurai, Arunprasath and Salah, Khaled and Ramnath, Rajiv</b>
     4466, &quot;VDC-Analyst: Design and verification of virtual desktop cloud resource allocations.&quot
     4467Computer Networks,
     44682014.
     4469doi:10.1016/j.comnet.2014.02.022.
     4470</li>
     4471<br>
     4472
     4473
     4474
     4475<li>
    43174476<b>Collings, Jake and Liu, Jun</b>
    43184477, &quot;An OpenFlow-Based Prototype of SDN-Oriented Stateful Hardware Firewalls.&quot
     
    45224681
    45234682<li>
     4683<b>Martin, Vincent and Coulaby, Adama and Schaff, Nathan and Tan, Chiu C. and Lin, Shan</b>
     4684, &quot;Bandwidth Prediction on a WiMAX Network.&quot
     4685Mobile Ad Hoc and Sensor Systems (MASS), 2014 IEEE 11th International Conference on, IEEE,
     46862014.
     4687doi:10.1109/mass.2014.75.
     4688</li>
     4689<br>
     4690
     4691
     4692
     4693<li>
    45244694<b>Maziku, H. and Shetty, S.</b>
    45254695, &quot;Network Aware VM Migration in Cloud Data Centers.&quot
     
    46584828
    465948292014.
    4660 
     4830doi:10.1109/CloudNet.2014.6969014.
    46614831</li>
    46624832<br>
     
    47984968<li>
    47994969<b>Xin, Yufeng and Baldin, Ilya and Heermann, Chris and Mandal, Anirban and Ruth, Paul</b>
     4970, &quot;Capacity of Inter-cloud Layer-2 Virtual Networking.&quot
     4971Proceedings of the 2014 ACM SIGCOMM Workshop on Distributed Cloud Computing, Chicago, Illinois, USA, ACM, New York, NY, USA,
     49722014.
     4973doi:10.1145/2627566.2627573.
     4974</li>
     4975<br>
     4976
     4977<li>
     4978<b>Xin, Yufeng and Baldin, Ilya and Heermann, Chris and Mandal, Anirban and Ruth, Paul</b>
    48004979, &quot;Scaling up applications over distributed clouds with dynamic layer-2 exchange and broadcast service.&quot
    48014980Teletraffic Congress (ITC), 2014 26th International, IEEE,
    480249812014.
    48034982doi:10.1109/itc.2014.6932973.
    4804 </li>
    4805 <br>
    4806 
    4807 <li>
    4808 <b>Xin, Yufeng and Baldin, Ilya and Heermann, Chris and Mandal, Anirban and Ruth, Paul</b>
    4809 , &quot;Capacity of Inter-cloud Layer-2 Virtual Networking.&quot
    4810 Proceedings of the 2014 ACM SIGCOMM Workshop on Distributed Cloud Computing, Chicago, Illinois, USA, ACM, New York, NY, USA,
    4811 2014.
    4812 doi:10.1145/2627566.2627573.
    48134983</li>
    48144984<br>
     
    48625032<br>
    48635033<a id="concise-2015"><H2>GENI Publications for 2015</H2></a>
     5034
     5035
     5036<li>
     5037<b>Edwards, Sarah and Liu, Xuan and Riga, Niky</b>
     5038, &quot;Creating Repeatable Computer Science and Networking Experiments on Shared, Public Testbeds.&quot
     5039SIGOPS Oper. Syst. Rev., ACM, New York, NY, USA,
     50402015.
     5041doi:10.1145/2723872.2723884.
     5042</li>
     5043<br>
     5044
    48645045
    48655046
     
    487050512015.
    48715052
     5053</li>
     5054<br>
     5055
     5056
     5057
     5058<li>
     5059<b>Ricci, Robert and Wong, Gary and Stoller, Leigh and Webb, Kirk and Duerig, Jonathon and Downie, Keith and Hibler, Mike</b>
     5060, &quot;Apt: A Platform for Repeatable Research in Computer Science.&quot
     5061SIGOPS Oper. Syst. Rev., ACM, New York, NY, USA,
     50622015.
     5063doi:10.1145/2723872.2723885.
    48725064</li>
    48735065<br>