Changes between Version 58 and Version 59 of GENIBibliography


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Timestamp:
09/26/17 09:37:12 (5 years ago)
Author:
Mark Berman
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  • GENIBibliography

    v58 v59  
    8585
    8686<li>
     87<b>Akella, Anand V. and Xiong, Kaiqi</b>,
     88&quot;Quality of Service (QoS)-Guaranteed Network Resource Allocation via Software Defined Networking (SDN).&quot;
     892014 IEEE 12th International Conference on Dependable, Autonomic and Secure Computing, Dalian, China, IEEE,
     902014.
     91doi:10.1109/dasc.2014.11.
     92<a href="http://dx.doi.org/10.1109/dasc.2014.11">http://dx.doi.org/10.1109/dasc.2014.11</a>
     93<br><br><b>Abstract: </b>Quality of Service (QoS) -- based bandwidth allocation plays a key role in real-time computing systems and applications such as voice IP, teleconferencing, and gaming. Likewise, customer services often need to be distinguished according to their service priorities and requirements. In this paper, we consider bandwidth allocation in the networks of a cloud carrier in which cloud users' requests are processed and transferred by a cloud provider subject to QoS requirements. We present a QoS-guaranteed approach for bandwidth allocation that satisfies QoS requirements for all priority cloud users by using Open vSwitch, based on software defined networking (SDN). We implement and test the proposed approach on the Global Environment for Networking Innovations (GENI). Experimental results show the effectiveness of the proposed approach.
     94</li>
     95<br>
     96
     97
     98
     99<li>
    87100<b>AlEroud, Ahmed and Alsmadi, Izzat</b>,
    88101&quot;Identifying cyber-attacks on software defined networks: An inference-based intrusion detection approach.&quot;
     
    111124
    112125<li>
     126<b>Alaoui, Sara E. and Ramamurthy, Byrav</b>,
     127&quot;EAODR: A Novel Routing Algorithm Based on the Modified Temporal Graph Network Model for DTN-Based Interplanetary Networks.&quot;
     128Computer Networks,
     1292017.
     130doi:10.1016/j.comnet.2017.09.012.
     131<a href="http://dx.doi.org/10.1016/j.comnet.2017.09.012">http://dx.doi.org/10.1016/j.comnet.2017.09.012</a>
     132<br><br><b>Abstract: </b>The Interplanetary Internet is a network that interconnects objects traveling in space and on planets such as satellites, rovers and comets. This network has very different communication conditions than the networks deployed on the surface of Earth. The large delays, intermittent connections and rough environment in space require the adoption of the Delay/Disruption Tolerant Network architecture/techniques. The currently used implementation of DTN interplanetary networks uses the Contact Graph Routing mechanism that we show, using the Interplanetary Overlay Network (ION) based experiments, has some shortcomings leading to less efficient use of the network. In this paper, we propose a novel model to represent such networks based on temporal graphs obtaining a near-real-time representation of these deterministic dynamic networks. This Modified Temporal Graph (MTG) model is then used for the implementation of our proposed routing algorithm, the Earliest Arrival Optimal Delivery Ratio (EAODR) routing algorithm. We provide the proof of correctness of EAODR, and we use our routing simulator to run experiments on a real-world network and also on large networks. We prove that EAODR outperforms the Contact Graph Routing (CGR) in terms of a decrease in delay of up to 12.9&#x0025;.
     133</li>
     134<br>
     135
     136
     137
     138<li>
    113139<b>Albrecht, J. and Huang, D. Y.</b>,
    114140&quot;Managing distributed applications using Gush.&quot;
     
    265291
    266292<li>
     293<b>Avgeris, Marios and Kalatzis, Nikos and Dechouniotis, Dimitrios and Roussaki, Ioanna and Papavassiliou, Symeon</b>,
     294&quot;Semantic Resource Management of Federated IoT Testbeds.&quot;
     295Ad-hoc, Mobile, and Wireless Networks, Springer International Publishing,
     2962017.
     297doi:10.1007/978-3-319-67910-5&#x005F;3.
     298<a href="http://dx.doi.org/10.1007/978-3-319-67910-5&#x005F;3">http://dx.doi.org/10.1007/978-3-319-67910-5&#x005F;3</a>
     299<br><br><b>Abstract: </b>Testbeds and experimental network facilities accelerate the expansion of disruptive Internet services and support their evolution. The integration of IoT technologies in the context of Unmanned Vehicles (UxVs) and their deployment in federated, real–world testbeds introduce various challenging research issues. This paper presents the Semantic Aggregate Manager (SAM) that exploits semantic technologies for modeling and managing resources of federated IoT Testbeds. SAM introduces new semantics–based features tailored to the needs of IoT enabled UxVs, but on the same time allows the compatibility with existing legacy, ” de facto” standardised protocols, currently utilized by multiple federated testbed management systems. The proposed framework is currently being deployed in order to be evaluated in real–world testbeds across several sites in Europe.
     300</li>
     301<br>
     302
     303
     304
     305<li>
    267306<b>Babaoglu, A. C. and Dutta, R.</b>,
    268307&quot;A GENI Meso-Scale Experiment of a Verification Service.&quot;
     
    10181057<li>
    10191058<b>Chin, Tommy and Mountrouidou, Xenia and Li, Xiangyang and Xiong, Kaiqi</b>,
    1020 &quot;An SDN-supported collaborative approach for DDoS flooding detection and containment.&quot;
    1021 Military Communications Conference, MILCOM 2015 - 2015 IEEE, IEEE,
    1022 2015.
    1023 doi:10.1109/milcom.2015.7357519.
    1024 <a href="http://dx.doi.org/10.1109/milcom.2015.7357519">http://dx.doi.org/10.1109/milcom.2015.7357519</a>
    1025 <br><br><b>Abstract: </b>Software Defined Networking (SDN) has the potential to enable novel security applications that support flexible, on-demand deployment of system elements. It can offer targeted forensic evidence collection and investigation of computer network attacks. Such unique capabilities are instrumental to network intrusion detection that is challenged by large volumes of data and complex network topologies. This paper presents an innovative approach that coordinates distributed network traffic Monitors and attack Correlators supported by Open Virtual Switches (OVS). The Monitors conduct anomaly detection and the Correlators perform deep packet inspection for attack signature recognition. These elements take advantage of complementary views and information availability on both the data and control planes. Moreover, they collaboratively look for network flooding attack signature constituents that possess different characteristics in the level of information abstraction. Therefore, this approach is able to not only quickly raise an alert against potential threats, but also follow it up with careful verification to reduce false alarms. We experiment with this SDN-supported collaborative approach to detect TCP SYN flood attacks on the Global Environment for Network Innovations (GENI), a realistic virtual testbed. The response times and detection accuracy, in the context of a small to medium corporate network, have demonstrated its effectiveness and scalability.
    1026 </li>
    1027 <br>
    1028 
    1029 <li>
    1030 <b>Chin, Tommy and Mountrouidou, Xenia and Li, Xiangyang and Xiong, Kaiqi</b>,
    10311059&quot;Selective Packet Inspection to Detect DoS Flooding Using Software Defined Networking (SDN).&quot;
    10321060Distributed Computing Systems Workshops (ICDCSW), 2015 IEEE 35th International Conference on, IEEE,
     
    10381066<br>
    10391067
    1040 
     1068<li>
     1069<b>Chin, Tommy and Mountrouidou, Xenia and Li, Xiangyang and Xiong, Kaiqi</b>,
     1070&quot;An SDN-supported collaborative approach for DDoS flooding detection and containment.&quot;
     1071MILCOM 2015 - 2015 IEEE Military Communications Conference, Tampa, FL, USA, IEEE,
     10722015.
     1073doi:10.1109/milcom.2015.7357519.
     1074<a href="http://dx.doi.org/10.1109/milcom.2015.7357519">http://dx.doi.org/10.1109/milcom.2015.7357519</a>
     1075<br><br><b>Abstract: </b>Software Defined Networking (SDN) has the potential to enable novel security applications that support flexible, on-demand deployment of system elements. It can offer targeted forensic evidence collection and investigation of computer network attacks. Such unique capabilities are instrumental to network intrusion detection that is challenged by large volumes of data and complex network topologies. This paper presents an innovative approach that coordinates distributed network traffic Monitors and attack Correlators supported by Open Virtual Switches (OVS). The Monitors conduct anomaly detection and the Correlators perform deep packet inspection for attack signature recognition. These elements take advantage of complementary views and information availability on both the data and control planes. Moreover, they collaboratively look for network flooding attack signature constituents that possess different characteristics in the level of information abstraction. Therefore, this approach is able to not only quickly raise an alert against potential threats, but also follow it up with careful verification to reduce false alarms. We experiment with this SDN-supported collaborative approach to detect TCP SYN flood attacks on the Global Environment for Network Innovations (GENI), a realistic virtual testbed. The response times and detection accuracy, in the context of a small to medium corporate network, have demonstrated its effectiveness and scalability.
     1076</li>
     1077<br>
     1078
     1079
     1080
     1081<li>
     1082<b>Chin, Tommy and Xiong, Kaiqi</b>,
     1083&quot;Dynamic generation containment systems (DGCS): A Moving Target Defense approach.&quot;
     10842016 3rd International Workshop on Emerging Ideas and Trends in Engineering of Cyber-Physical Systems (EITEC), IEEE,
     10852016.
     1086doi:10.1109/eitec.2016.7503690.
     1087<a href="http://dx.doi.org/10.1109/eitec.2016.7503690">http://dx.doi.org/10.1109/eitec.2016.7503690</a>
     1088<br><br><b>Abstract: </b>Supervisory Control and Data Acquisition (SCADA) systems are critical assets to public utility and manufacturing organizations. These systems, although critical, are prone to numerous cyber security related threats and attacks. To combat such challenges, we propose a Dynamic Generated Containment System (DGCS), a moving target defense model as a method of threat evasion. Under the proposed approach, we employ the use of intrusion detection systems (IDS) in conjunction with virtualization solution - Docker. The proposed approach provides an individual Docker container for each threat detected by our IDS. We conduct several experiments using high performance computing systems to measure and demonstrate our proposed approach.
     1089</li>
     1090<br>
     1091
     1092<li>
     1093<b>Chin, Tommy and Xiong, Kaiqi</b>,
     1094&quot;A Forensic Methodology for Software-Defined Network Switches.&quot;
     1095Advances in Digital Forensics XIII, Springer International Publishing, Cham,
     10962017.
     1097doi:10.1007/978-3-319-67208-3&#x005F;6.
     1098<a href="http://dx.doi.org/10.1007/978-3-319-67208-3&#x005F;6">http://dx.doi.org/10.1007/978-3-319-67208-3&#x005F;6</a>
     1099<br><br><b>Abstract: </b>This chapter presents a forensic methodology for computing systems in a software-defined networking environment that consists of an application plane, control plane and data plane. The methodology involves a forensic examination of the software-defined networking infrastructure from the perspective of a switch. Memory images of a live switch and southbound communications are leveraged to enable forensic investigators to identify and locate potential evidence for triage in real time. The methodology is evaluated using a real-world testbed exposed to network attacks. The experimental results demonstrate the effectiveness of the methodology for forensic investigations of software-defined networking infrastructures.
     1100</li>
     1101<br>
    10411102
    10421103<li>
     
    10481109<a href="http://dx.doi.org/10.1007/978-3-319-42836-9&#x005F;43">http://dx.doi.org/10.1007/978-3-319-42836-9&#x005F;43</a>
    10491110<br><br><b>Abstract: </b>This paper addresses one major concern on how to secure the location information of a base station in a compromised Wireless Sensor Network (WSN). In this concern, disrupting or damaging the wireless base station can be catastrophic for a WSN. To aid in the mitigation of this challenge, we present Moving Proximity Base Station Defense (MPBSD), a Moving Target Defense (MTD) approach to concealing the location of a base station within a WSN. In this approach, we employ multiple base stations to serve a WSN where one of the multiple base stations is elected to serve the WSN in a specific period of time. Specifically, our approach periodically changes the designation over a period of time to provide obscurity in the location information of the base station. We further evaluate MPBSD using a real-world testbed environment utilizing Wi-Fi frequencies. Our results show that MPBSD is an effective MTD approach to securing base stations for a WSN in term of sensory performance such as end-to-end delay.
    1050 </li>
    1051 <br>
    1052 
    1053 <li>
    1054 <b>Chin, Tommy and Xiong, Kaiqi</b>,
    1055 &quot;Dynamic generation containment systems (DGCS): A Moving Target Defense approach.&quot;
    1056 2016 3rd International Workshop on Emerging Ideas and Trends in Engineering of Cyber-Physical Systems (EITEC), IEEE,
    1057 2016.
    1058 doi:10.1109/eitec.2016.7503690.
    1059 <a href="http://dx.doi.org/10.1109/eitec.2016.7503690">http://dx.doi.org/10.1109/eitec.2016.7503690</a>
    1060 <br><br><b>Abstract: </b>Supervisory Control and Data Acquisition (SCADA) systems are critical assets to public utility and manufacturing organizations. These systems, although critical, are prone to numerous cyber security related threats and attacks. To combat such challenges, we propose a Dynamic Generated Containment System (DGCS), a moving target defense model as a method of threat evasion. Under the proposed approach, we employ the use of intrusion detection systems (IDS) in conjunction with virtualization solution - Docker. The proposed approach provides an individual Docker container for each threat detected by our IDS. We conduct several experiments using high performance computing systems to measure and demonstrate our proposed approach.
    10611111</li>
    10621112<br>
     
    16621712<li>
    16631713<b>Griffioen, J. and Fei, Zongming and Nasir, H. and Wu, Xiongqi and Reed, J. and Carpenter, C.</b>,
     1714&quot;The design of an instrumentation system for federated and virtualized network testbeds.&quot;
     1715Network Operations and Management Symposium (NOMS), 2012 IEEE, IEEE,
     17162012.
     1717doi:10.1109/NOMS.2012.6212061.
     1718<a href="http://dx.doi.org/10.1109/NOMS.2012.6212061">http://dx.doi.org/10.1109/NOMS.2012.6212061</a>
     1719<br><br><b>Abstract: </b>Much of the GENI effort in developing network testbeds has been focused on building the control frameworks needed to allocate and initialize the network resources that make up an experiment. We argue that building the instrumentation and measurement system to monitor and capture the behavior of the network is just as important and challenging as setting up the network itself, especially in a virtualized and federated environment where getting information from experimental nodes is too complicated and too much to handle for a typical user. In this paper, we describe the design of an instrumentation and measurement infrastructure that allows users to monitor their experiments. The challenge that virtualization and federation of GENI testbeds bring to instrumentation and monitoring is how to hide the details of instrumentation setup from users so that users do not need to be experts in system administration or network management of virtualized and federated systems, but are still able to ” see” what is going on with their experiments. Our instrumentation tool sets up experiment-specific monitoring infrastructure that is tailored to capture, record, and display only information associated with that experiment. Our tools are currently available in GENI, and we present a simple example of how to use them to instrument an experiment.
     1720</li>
     1721<br>
     1722
     1723<li>
     1724<b>Griffioen, J. and Fei, Zongming and Nasir, H. and Wu, Xiongqi and Reed, J. and Carpenter, C.</b>,
    16641725&quot;GENI-Enabled Programming Experiments for Networking Classes.&quot;
    16651726Research and Educational Experiment Workshop (GREE), 2013 Second GENI, IEEE,
     
    16681729<a href="http://dx.doi.org/10.1109/gree.2013.30">http://dx.doi.org/10.1109/gree.2013.30</a>
    16691730<br><br><b>Abstract: </b>Although GENI has been readily embraced by the research community as a testbed for exploring new network architectures and services, its use as an educational tool has not seen the same level of acceptance and usage. There are multiple reasons for this, not the least of which is a lack of good examples showing how to use GENI in an educational setting. This paper attempts to remedy this by describing our experiences using GENI in our networking classes at the University of Kentucky. Using GENI as the experimental basis for the projects in our classes allowed us to leverage several of its rich set of features including its global span of resources, programmability, virtualization, and instrumentation and measurement tools. In particular, we describe two projects that we have used in our networking classes, and we share some of the experience we gained in the process. As a result, these experiences motivated us to develop and integrate new functions into the GENI desktop in order to make it easier to access and control GENI's various resources and tools.
    1670 </li>
    1671 <br>
    1672 
    1673 <li>
    1674 <b>Griffioen, J. and Fei, Zongming and Nasir, H. and Wu, Xiongqi and Reed, J. and Carpenter, C.</b>,
    1675 &quot;The design of an instrumentation system for federated and virtualized network testbeds.&quot;
    1676 Network Operations and Management Symposium (NOMS), 2012 IEEE, IEEE,
    1677 2012.
    1678 doi:10.1109/NOMS.2012.6212061.
    1679 <a href="http://dx.doi.org/10.1109/NOMS.2012.6212061">http://dx.doi.org/10.1109/NOMS.2012.6212061</a>
    1680 <br><br><b>Abstract: </b>Much of the GENI effort in developing network testbeds has been focused on building the control frameworks needed to allocate and initialize the network resources that make up an experiment. We argue that building the instrumentation and measurement system to monitor and capture the behavior of the network is just as important and challenging as setting up the network itself, especially in a virtualized and federated environment where getting information from experimental nodes is too complicated and too much to handle for a typical user. In this paper, we describe the design of an instrumentation and measurement infrastructure that allows users to monitor their experiments. The challenge that virtualization and federation of GENI testbeds bring to instrumentation and monitoring is how to hide the details of instrumentation setup from users so that users do not need to be experts in system administration or network management of virtualized and federated systems, but are still able to ” see” what is going on with their experiments. Our instrumentation tool sets up experiment-specific monitoring infrastructure that is tailored to capture, record, and display only information associated with that experiment. Our tools are currently available in GENI, and we present a simple example of how to use them to instrument an experiment.
    16811731</li>
    16821732<br>
     
    19722022<li>
    19732023<b>Juluri, Parikshit and Tamarapalli, Venkatesh and Medhi, Deep</b>,
    1974 &quot;QoE management in DASH systems using the segment aware rate adaptation algorithm.&quot;
    1975 NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium, IEEE,
    1976 2016.
    1977 doi:10.1109/noms.2016.7502805.
    1978 <a href="http://dx.doi.org/10.1109/noms.2016.7502805">http://dx.doi.org/10.1109/noms.2016.7502805</a>
    1979 <br><br><b>Abstract: </b>Dynamic Adaptive Streaming over HTTP (DASH) enables the video player to adapt the bitrate of the video while streaming to ensure playback without interruptions even with varying throughput. A DASH server hosts multiple representations of the same video, each of which is broken down into small segments of fixed playback duration. The video bitrate adaptation is purely driven by the player at the endhost. Typically, the player employs an Adaptive Bitrate (ABR) algorithm, that determines the most appropriate representation for the next segment to be downloaded, based on the current network conditions and user preferences. The aim of an ABR algorithm is to dynamically manage the Quality of Experience (QoE) of the user during the playback. ABR algorithms manage the QoE by maximizing the bitrate while at the same time trying to minimize the other QoE metrics: playback start time, duration and number of buffering events, and the number of bitrate switching events. Typically, the ABR algorithms manage the QoE by using the measured network throughput and buffer occupancy to adapt the playback bitrate. However, due to the video encoding schemes employed, the sizes of the individual segments may vary significantly. For low bandwidth networks, fluctuation in the segment sizes results in inaccurate estimation the expected segment fetch times, thereby resulting in inaccurate estimation of the optimum bitrate. In this paper we demonstrate how the Segment-Aware Rate Adaptation (SARA) algorithm, that considers the measured throughput, buffer occupancy, and the variation in segment sizes helps in better management of the users' QoE in a DASH system. By comparing with a typical throughput-based and buffer-based adaptation algorithm under varying network conditions, we demonstrate that SARA manages the QoE better, especially in a low bandwidth network. We also developed AStream, an open-source Python-based emulated DASH-video player that was used to evaluate three different ABR algor- thms and measure the QoE metrics with each of them.
    1980 </li>
    1981 <br>
    1982 
    1983 <li>
    1984 <b>Juluri, Parikshit and Tamarapalli, Venkatesh and Medhi, Deep</b>,
    19852024&quot;SARA: Segment aware rate adaptation algorithm for dynamic adaptive streaming over HTTP.&quot;
    19862025Communication Workshop (ICCW), 2015 IEEE International Conference on, IEEE,
     
    19892028<a href="http://dx.doi.org/10.1109/iccw.2015.7247436">http://dx.doi.org/10.1109/iccw.2015.7247436</a>
    19902029<br><br><b>Abstract: </b>Dynamic adaptive HTTP (DASH) based streaming is steadily becoming the most popular online video streaming technique. DASH streaming provides seamless playback by adapting the video quality to the network conditions during the video playback. A DASH server supports adaptive streaming by hosting multiple representations of the video and each representation is divided into small segments of equal playback duration. At the client end, the video player uses an adaptive bitrate selection (ABR) algorithm to decide the bitrate to be selected for each segment depending on the current network conditions. Currently, proposed ABR algorithms ignore the fact that the segment sizes significantly vary for a given video bitrate. Due to this, even though an ABR algorithm is able to measure the network bandwidth, it may fail to predict the time to download the next segment In this paper, we propose a segment-aware rate adaptation (SARA) algorithm that considers the segment size variation in addition to the estimated path bandwidth and the current buffer occupancy to accurately predict the time required to download the next segment We also developed an open source Python based emulated DASH video player, that was used to compare the performance of SARA and a basic ABR. Our results show that SARA provides a significant gain over the basic algorithm in the video quality delivered, without noticeably impacting the video switching rates.
     2030</li>
     2031<br>
     2032
     2033<li>
     2034<b>Juluri, Parikshit and Tamarapalli, Venkatesh and Medhi, Deep</b>,
     2035&quot;QoE management in DASH systems using the segment aware rate adaptation algorithm.&quot;
     2036NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium, IEEE,
     20372016.
     2038doi:10.1109/noms.2016.7502805.
     2039<a href="http://dx.doi.org/10.1109/noms.2016.7502805">http://dx.doi.org/10.1109/noms.2016.7502805</a>
     2040<br><br><b>Abstract: </b>Dynamic Adaptive Streaming over HTTP (DASH) enables the video player to adapt the bitrate of the video while streaming to ensure playback without interruptions even with varying throughput. A DASH server hosts multiple representations of the same video, each of which is broken down into small segments of fixed playback duration. The video bitrate adaptation is purely driven by the player at the endhost. Typically, the player employs an Adaptive Bitrate (ABR) algorithm, that determines the most appropriate representation for the next segment to be downloaded, based on the current network conditions and user preferences. The aim of an ABR algorithm is to dynamically manage the Quality of Experience (QoE) of the user during the playback. ABR algorithms manage the QoE by maximizing the bitrate while at the same time trying to minimize the other QoE metrics: playback start time, duration and number of buffering events, and the number of bitrate switching events. Typically, the ABR algorithms manage the QoE by using the measured network throughput and buffer occupancy to adapt the playback bitrate. However, due to the video encoding schemes employed, the sizes of the individual segments may vary significantly. For low bandwidth networks, fluctuation in the segment sizes results in inaccurate estimation the expected segment fetch times, thereby resulting in inaccurate estimation of the optimum bitrate. In this paper we demonstrate how the Segment-Aware Rate Adaptation (SARA) algorithm, that considers the measured throughput, buffer occupancy, and the variation in segment sizes helps in better management of the users' QoE in a DASH system. By comparing with a typical throughput-based and buffer-based adaptation algorithm under varying network conditions, we demonstrate that SARA manages the QoE better, especially in a low bandwidth network. We also developed AStream, an open-source Python-based emulated DASH-video player that was used to evaluate three different ABR algor- thms and measure the QoE metrics with each of them.
    19912041</li>
    19922042<br>
     
    21522202<li>
    21532203<b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>,
    2154 &quot;Performance of GENI Cloud Testbeds for Real Time Scientific Application.&quot;
    2155 First GENI Research and Educational Experiment Workshop (GREE 2012), Los Angeles,
    2156 2012.
    2157 
    2158 
    2159 <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.
    2160 </li>
    2161 <br>
    2162 
    2163 <li>
    2164 <b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>,
    21652204&quot;Network capabilities of cloud services for a real time scientific application.&quot;
    2166220537th Annual IEEE Conference on Local Computer Networks, Clearwater Beach, FL, USA, IEEE,
     
    21692208<a href="http://dx.doi.org/10.1109/lcn.2012.6423665">http://dx.doi.org/10.1109/lcn.2012.6423665</a>
    21702209<br><br><b>Abstract: </b>Dedicating high-end servers for executing scientific applications that run intermittently, such as severe weather detection or generalized weather forecasting, wastes resources. While the Infrastructure-as-a-Service (IaaS) model used by today's cloud platforms is well-suited for the bursty computational demands of these applications, it is unclear if the network capabilities of today's cloud platforms are sufficient. In this paper, we analyze the networking capabilities of multiple commercial (Amazon's EC2 and Rackspace) and research (GENICloud and ExoGENI cloud) platforms in the context of a Nowcasting application, a forecasting algorithm for highly accurate, near-term, e.g., 5-20 minutes, weather predictions. The application has both computational and network requirements. While it executes rarely, whenever severe weather approaches, it benefits from an IaaS model; However, since its results are time-critical, enough bandwidth must be available to transmit radar data to cloud platforms before it becomes stale. We conduct network capacity measurements between radar sites and cloud platforms throughout the country. Our results indicate that ExoGENI cloud performs the best for both serial and parallel data transfer with an average throughput of 110.22 Mbps and 17.2 Mbps, respectively. We also found that the cloud services perform better in the distributed data transfer case, where a subset of nodes transmit data in parallel to a cloud instance. Ultimately, we conclude that commercial and research clouds are capable of providing sufficient bandwidth for our real-time Nowcasting application.
     2210</li>
     2211<br>
     2212
     2213<li>
     2214<b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>,
     2215&quot;Performance of GENI Cloud Testbeds for Real Time Scientific Application.&quot;
     2216First GENI Research and Educational Experiment Workshop (GREE 2012), Los Angeles,
     22172012.
     2218
     2219
     2220<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.
    21712221</li>
    21722222<br>
     
    25532603<li>
    25542604<b>Mambretti, Joe and Chen, Jim and Yeh, Fei</b>,
     2605&quot;Next Generation Virtual Network Architecture for Multi-tenant Distributed Clouds: Challenges and Emerging Techniques.&quot;
     2606Proceedings of the 4th Workshop on Distributed Cloud Computing, Chicago, Illinois, ACM, New York, NY, USA,
     26072016.
     2608doi:10.1145/2955193.2955194.
     2609<a href="http://dx.doi.org/10.1145/2955193.2955194">http://dx.doi.org/10.1145/2955193.2955194</a>
     2610<br><br><b>Abstract: </b>Providing services for multiple tenants within a single or federated distributed cloud environment requires a variety of special considerations related to network design, provisioning, and operations. Especially important are multiple topics concerning the implementation of multiple parallel programmable virtual networks for large numbers of tenants, who require autonomous management, control, and data planes. This paper provides an overview of some of the challenges that arise from developing and implementing parallel programmable virtual networks, describes experiences with several experimental techniques for addressing those challenges based on large scale distributed testbeds, and presents the results of the experiments that were conducted. Distributed environments used include a distributed cloud testbed, the Chameleon Cloud, sponsored by the National Science Foundation's NSFCloud program, the NSF's Global Environment for Network Innovations (GENI), an international distributed OpenFlow testbed, and the Open Science Data Cloud.
     2611</li>
     2612<br>
     2613
     2614<li>
     2615<b>Mambretti, Joe and Chen, Jim and Yeh, Fei</b>,
     2616&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;
     2617Computer Networks,
     26182014.
     2619doi:10.1016/j.bjp.2013.12.024.
     2620<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>
     2621<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.
     2622</li>
     2623<br>
     2624
     2625<li>
     2626<b>Mambretti, Joe and Chen, Jim and Yeh, Fei</b>,
    25552627&quot;Software-Defined Network Exchanges (SDXs): Architecture, services, capabilities, and foundation technologies.&quot;
    25562628Teletraffic Congress (ITC), 2014 26th International, IEEE,
     
    25592631<a href="http://dx.doi.org/10.1109/itc.2014.6932970">http://dx.doi.org/10.1109/itc.2014.6932970</a>
    25602632<br><br><b>Abstract: </b>Software Defined Networks (SDNs), primarily based on OpenFlow, are being deployed in single domain networks around the world. The popularity of SDNs has given rise to multiple considerations about designing, implementing, and operating Software-Defined Network Exchanges (SDXs), to enable SDNs to interconnect SDN islands and to extend SDNs across multiple domains. These goals can be accomplished only by developing new techniques that extend the single domain orientation of current SDN/OpenFlow approaches to include capabilities for multidomain control, including those for resource discovery, signaling, and dynamic provisioning. Several networking research communities have begun to investigate these concepts. Early architectural models of SDXs have been designed and implemented as prototypes. These SDXs are being used to conduct experiments and to demonstrate the potentials of SDXs.
    2561 </li>
    2562 <br>
    2563 
    2564 <li>
    2565 <b>Mambretti, Joe and Chen, Jim and Yeh, Fei</b>,
    2566 &quot;Next Generation Virtual Network Architecture for Multi-tenant Distributed Clouds: Challenges and Emerging Techniques.&quot;
    2567 Proceedings of the 4th Workshop on Distributed Cloud Computing, Chicago, Illinois, ACM, New York, NY, USA,
    2568 2016.
    2569 doi:10.1145/2955193.2955194.
    2570 <a href="http://dx.doi.org/10.1145/2955193.2955194">http://dx.doi.org/10.1145/2955193.2955194</a>
    2571 <br><br><b>Abstract: </b>Providing services for multiple tenants within a single or federated distributed cloud environment requires a variety of special considerations related to network design, provisioning, and operations. Especially important are multiple topics concerning the implementation of multiple parallel programmable virtual networks for large numbers of tenants, who require autonomous management, control, and data planes. This paper provides an overview of some of the challenges that arise from developing and implementing parallel programmable virtual networks, describes experiences with several experimental techniques for addressing those challenges based on large scale distributed testbeds, and presents the results of the experiments that were conducted. Distributed environments used include a distributed cloud testbed, the Chameleon Cloud, sponsored by the National Science Foundation's NSFCloud program, the NSF's Global Environment for Network Innovations (GENI), an international distributed OpenFlow testbed, and the Open Science Data Cloud.
    2572 </li>
    2573 <br>
    2574 
    2575 <li>
    2576 <b>Mambretti, Joe and Chen, Jim and Yeh, Fei</b>,
    2577 &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;
    2578 Computer Networks,
    2579 2014.
    2580 doi:10.1016/j.bjp.2013.12.024.
    2581 <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>
    2582 <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.
    25832633</li>
    25842634<br>
     
    30023052<li>
    30033053<b>Ozcelik, Ilker and Brooks, Richard R.</b>,
    3004 &quot;Performance Analysis of DDoS Detection Methods on Real Network.&quot;
    3005 First GENI Research and Educational Experiment Workshop (GREE 2012), Los Angeles,
    3006 2012.
    3007 
    3008 
    3009 <br><br><b>Abstract: </b>Distributed Denial of Service (DDoS) attacks are major security threats to the Internet. The distributed structure of these attacks makes it difficult to distinguish between legitimate and attack traffic, making detection difficult. In addition to this challenge, researchers also have to study and find countermeasures against these attacks without using an operational network for testing, since attacks on operational networks inconvenience users. In this paper, we propose a method to perform DDoS analysis on real hardware using real traffic without jeopardizing the original network. We implement our experiments on the Geni testbed using Openflow. We present results from DDoS detection methods using operational traffic.
    3010 </li>
    3011 <br>
    3012 
    3013 <li>
    3014 <b>Ozcelik, Ilker and Brooks, Richard R.</b>,
    30153054&quot;Operational System Testing for Designed in Security.&quot;
    30163055Proceedings of the Eighth Annual Cyber Security and Information Intelligence Research Workshop, Oak Ridge, Tennessee, ACM, New York, NY, USA,
     
    30193058<a href="http://dx.doi.org/10.1145/2459976.2460038">http://dx.doi.org/10.1145/2459976.2460038</a>
    30203059<br><br><b>Abstract: </b>To design secure systems, one needs to understand how attackers use system vulnerabilities in their favor. This requires testing vulnerabilities on operational systems. However, working on operational systems is not always possible because of the risk of disturbance. In this study, we introduce an approach to experimenting using operational system data and performing real attacks without disturbing the original system. We applied this approach to a network security experiment and tested the performance of three detection methods. The approach used in this study can be used when developing systems with Designed-in Security to identify and test system vulnerabilities.
     3060</li>
     3061<br>
     3062
     3063<li>
     3064<b>Ozcelik, Ilker and Brooks, Richard R.</b>,
     3065&quot;Performance Analysis of DDoS Detection Methods on Real Network.&quot;
     3066First GENI Research and Educational Experiment Workshop (GREE 2012), Los Angeles,
     30672012.
     3068
     3069
     3070<br><br><b>Abstract: </b>Distributed Denial of Service (DDoS) attacks are major security threats to the Internet. The distributed structure of these attacks makes it difficult to distinguish between legitimate and attack traffic, making detection difficult. In addition to this challenge, researchers also have to study and find countermeasures against these attacks without using an operational network for testing, since attacks on operational networks inconvenience users. In this paper, we propose a method to perform DDoS analysis on real hardware using real traffic without jeopardizing the original network. We implement our experiments on the Geni testbed using Openflow. We present results from DDoS detection methods using operational traffic.
    30213071</li>
    30223072<br>
     
    40924142<li>
    40934143<b>Van Vorst, N. and Erazo, M. and Liu, J.</b>,
    4094 &quot;PrimoGENI for hybrid network simulation and emulation experiments in GENI.&quot;
    4095 Journal of Simulation,
    4096 2012.
    4097 doi:10.1057/jos.2012.5.
    4098 <a href="http://dx.doi.org/10.1057/jos.2012.5">http://dx.doi.org/10.1057/jos.2012.5</a>
    4099 <br><br><b>Abstract: </b>The Global Environment for Network Innovations (GENI) is a community-driven research and development effort to build a collaborative and exploratory network experimentation platform—a 'virtual laboratory' for the design, implementation, and evaluation of future networks. The PrimoGENI project enables real-time network simulation by extending an existing network simulator to become part of the GENI federation to support large-scale experiments involving physical, simulated, and emulated network entities. In this paper, we describe a novel design of PrimoGENI, which aims at supporting realistic, scalable, and flexible network experiments with real-time simulation and emulation capabilities. We present a flexible emulation infrastructure that allows both remote client machines, local cluster nodes running virtual machines, and external networks to seamlessly interoperate with the simulated network running within a designated 'slice' of resources. We present the results of our preliminary validation and performance studies to demonstrate the capabilities as well as limitations of our approach.
    4100 </li>
    4101 <br>
    4102 
    4103 <li>
    4104 <b>Van Vorst, N. and Erazo, M. and Liu, J.</b>,
    41054144&quot;PrimoGENI: Integrating Real-Time Network Simulation and Emulation in GENI.&quot;
    41064145Principles of Advanced and Distributed Simulation (PADS), 2011 IEEE Workshop on, Nice, France, IEEE,
     
    41094148<a href="http://dx.doi.org/10.1109/pads.2011.5936747">http://dx.doi.org/10.1109/pads.2011.5936747</a>
    41104149<br><br><b>Abstract: </b>The Global Environment for Network Innovations (GENI) is a community-driven research and development effort to build a collaborative and exploratory network experimentation platform -- a &#x76;&#x0308;irtual laboratory'' for the design, implementation and evaluation of future networks. The PrimoGENI project enables real-time network simulation by extending an existing network simulator to become part of the GENI federation to support large-scale experiments involving physical, simulated and emulated network entities. In this paper, we describe a novel design of PrimoGENI, which aims at supporting realistic, scalable, and flexible network experiments with real-time simulation and emulation capabilities. We present a flexible emulation infrastructure that allows both remote client machines and local cluster nodes running virtual machines to seamlessly interoperate with the simulated network running within a designated &#x73;&#x0308;lice'' of resources. We show the results of our preliminary validation and performance studies to demonstrate the capabilities and limitations of our approach.
     4150</li>
     4151<br>
     4152
     4153<li>
     4154<b>Van Vorst, N. and Erazo, M. and Liu, J.</b>,
     4155&quot;PrimoGENI for hybrid network simulation and emulation experiments in GENI.&quot;
     4156Journal of Simulation,
     41572012.
     4158doi:10.1057/jos.2012.5.
     4159<a href="http://dx.doi.org/10.1057/jos.2012.5">http://dx.doi.org/10.1057/jos.2012.5</a>
     4160<br><br><b>Abstract: </b>The Global Environment for Network Innovations (GENI) is a community-driven research and development effort to build a collaborative and exploratory network experimentation platform—a 'virtual laboratory' for the design, implementation, and evaluation of future networks. The PrimoGENI project enables real-time network simulation by extending an existing network simulator to become part of the GENI federation to support large-scale experiments involving physical, simulated, and emulated network entities. In this paper, we describe a novel design of PrimoGENI, which aims at supporting realistic, scalable, and flexible network experiments with real-time simulation and emulation capabilities. We present a flexible emulation infrastructure that allows both remote client machines, local cluster nodes running virtual machines, and external networks to seamlessly interoperate with the simulated network running within a designated 'slice' of resources. We present the results of our preliminary validation and performance studies to demonstrate the capabilities as well as limitations of our approach.
    41114161</li>
    41124162<br>
     
    47544804
    47554805<li>
     4806<b>Akella, Anand V. and Xiong, Kaiqi</b>,
     4807&quot;Quality of Service (QoS)-Guaranteed Network Resource Allocation via Software Defined Networking (SDN).&quot
     48082014 IEEE 12th International Conference on Dependable, Autonomic and Secure Computing, Dalian, China, IEEE,
     48092014.
     4810doi:10.1109/dasc.2014.11.
     4811</li>
     4812<br>
     4813
     4814
     4815
     4816<li>
    47564817<b>AlEroud, Ahmed and Alsmadi, Izzat</b>,
    47574818&quot;Identifying cyber-attacks on software defined networks: An inference-based intrusion detection approach.&quot
     
    47764837
    47774838<li>
     4839<b>Alaoui, Sara E. and Ramamurthy, Byrav</b>,
     4840&quot;EAODR: A Novel Routing Algorithm Based on the Modified Temporal Graph Network Model for DTN-Based Interplanetary Networks.&quot
     4841Computer Networks,
     48422017.
     4843doi:10.1016/j.comnet.2017.09.012.
     4844</li>
     4845<br>
     4846
     4847
     4848
     4849<li>
    47784850<b>Albrecht, J. and Huang, D. Y.</b>,
    47794851&quot;Managing distributed applications using Gush.&quot
     
    49064978
    49074979<li>
     4980<b>Avgeris, Marios and Kalatzis, Nikos and Dechouniotis, Dimitrios and Roussaki, Ioanna and Papavassiliou, Symeon</b>,
     4981&quot;Semantic Resource Management of Federated IoT Testbeds.&quot
     4982Ad-hoc, Mobile, and Wireless Networks, Springer International Publishing,
     49832017.
     4984doi:10.1007/978-3-319-67910-5&#x005F;3.
     4985</li>
     4986<br>
     4987
     4988
     4989
     4990<li>
    49084991<b>Babaoglu, A. C. and Dutta, R.</b>,
    49094992&quot;A GENI Meso-Scale Experiment of a Verification Service.&quot
     
    54575540<li>
    54585541<b>Chen, Kang and Shen, Haiying</b>,
     5542&quot;Cont2: Social-Aware Content and Contact Based File Search in Delay Tolerant Networks.&quot
     5543Proceedings of the 2013 42Nd International Conference on Parallel Processing, IEEE Computer Society, Washington, DC, USA,
     55442013.
     5545doi:10.1109/icpp.2013.28.
     5546</li>
     5547<br>
     5548
     5549<li>
     5550<b>Chen, Kang and Shen, Haiying</b>,
    54595551&quot;Global optimization of file availability through replication for efficient file sharing in MANETs.&quot
    54605552Network Protocols (ICNP), 2011 19th IEEE International Conference on, Vancouver, AB, Canada, IEEE,
    546155532011.
    54625554doi:10.1109/icnp.2011.6089056.
    5463 </li>
    5464 <br>
    5465 
    5466 <li>
    5467 <b>Chen, Kang and Shen, Haiying</b>,
    5468 &quot;Cont2: Social-Aware Content and Contact Based File Search in Delay Tolerant Networks.&quot
    5469 Proceedings of the 2013 42Nd International Conference on Parallel Processing, IEEE Computer Society, Washington, DC, USA,
    5470 2013.
    5471 doi:10.1109/icpp.2013.28.
    54725555</li>
    54735556<br>
     
    55435626<li>
    55445627<b>Chin, Tommy and Mountrouidou, Xenia and Li, Xiangyang and Xiong, Kaiqi</b>,
    5545 &quot;An SDN-supported collaborative approach for DDoS flooding detection and containment.&quot
    5546 Military Communications Conference, MILCOM 2015 - 2015 IEEE, IEEE,
    5547 2015.
    5548 doi:10.1109/milcom.2015.7357519.
    5549 </li>
    5550 <br>
    5551 
    5552 <li>
    5553 <b>Chin, Tommy and Mountrouidou, Xenia and Li, Xiangyang and Xiong, Kaiqi</b>,
    55545628&quot;Selective Packet Inspection to Detect DoS Flooding Using Software Defined Networking (SDN).&quot
    55555629Distributed Computing Systems Workshops (ICDCSW), 2015 IEEE 35th International Conference on, IEEE,
     
    55595633<br>
    55605634
    5561 
     5635<li>
     5636<b>Chin, Tommy and Mountrouidou, Xenia and Li, Xiangyang and Xiong, Kaiqi</b>,
     5637&quot;An SDN-supported collaborative approach for DDoS flooding detection and containment.&quot
     5638MILCOM 2015 - 2015 IEEE Military Communications Conference, Tampa, FL, USA, IEEE,
     56392015.
     5640doi:10.1109/milcom.2015.7357519.
     5641</li>
     5642<br>
     5643
     5644
     5645
     5646<li>
     5647<b>Chin, Tommy and Xiong, Kaiqi</b>,
     5648&quot;Dynamic generation containment systems (DGCS): A Moving Target Defense approach.&quot
     56492016 3rd International Workshop on Emerging Ideas and Trends in Engineering of Cyber-Physical Systems (EITEC), IEEE,
     56502016.
     5651doi:10.1109/eitec.2016.7503690.
     5652</li>
     5653<br>
     5654
     5655<li>
     5656<b>Chin, Tommy and Xiong, Kaiqi</b>,
     5657&quot;A Forensic Methodology for Software-Defined Network Switches.&quot
     5658Advances in Digital Forensics XIII, Springer International Publishing, Cham,
     56592017.
     5660doi:10.1007/978-3-319-67208-3&#x005F;6.
     5661</li>
     5662<br>
    55625663
    55635664<li>
     
    556756682016.
    55685669doi:10.1007/978-3-319-42836-9&#x005F;43.
    5569 </li>
    5570 <br>
    5571 
    5572 <li>
    5573 <b>Chin, Tommy and Xiong, Kaiqi</b>,
    5574 &quot;Dynamic generation containment systems (DGCS): A Moving Target Defense approach.&quot
    5575 2016 3rd International Workshop on Emerging Ideas and Trends in Engineering of Cyber-Physical Systems (EITEC), IEEE,
    5576 2016.
    5577 doi:10.1109/eitec.2016.7503690.
    55785670</li>
    55795671<br>
     
    60876179<li>
    60886180<b>Griffioen, J. and Fei, Zongming and Nasir, H. and Wu, Xiongqi and Reed, J. and Carpenter, C.</b>,
     6181&quot;The design of an instrumentation system for federated and virtualized network testbeds.&quot
     6182Network Operations and Management Symposium (NOMS), 2012 IEEE, IEEE,
     61832012.
     6184doi:10.1109/NOMS.2012.6212061.
     6185</li>
     6186<br>
     6187
     6188<li>
     6189<b>Griffioen, J. and Fei, Zongming and Nasir, H. and Wu, Xiongqi and Reed, J. and Carpenter, C.</b>,
    60896190&quot;GENI-Enabled Programming Experiments for Networking Classes.&quot
    60906191Research and Educational Experiment Workshop (GREE), 2013 Second GENI, IEEE,
    609161922013.
    60926193doi:10.1109/gree.2013.30.
    6093 </li>
    6094 <br>
    6095 
    6096 <li>
    6097 <b>Griffioen, J. and Fei, Zongming and Nasir, H. and Wu, Xiongqi and Reed, J. and Carpenter, C.</b>,
    6098 &quot;The design of an instrumentation system for federated and virtualized network testbeds.&quot
    6099 Network Operations and Management Symposium (NOMS), 2012 IEEE, IEEE,
    6100 2012.
    6101 doi:10.1109/NOMS.2012.6212061.
    61026194</li>
    61036195<br>
     
    63496441<li>
    63506442<b>Juluri, Parikshit and Tamarapalli, Venkatesh and Medhi, Deep</b>,
    6351 &quot;QoE management in DASH systems using the segment aware rate adaptation algorithm.&quot
    6352 NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium, IEEE,
    6353 2016.
    6354 doi:10.1109/noms.2016.7502805.
    6355 </li>
    6356 <br>
    6357 
    6358 <li>
    6359 <b>Juluri, Parikshit and Tamarapalli, Venkatesh and Medhi, Deep</b>,
    63606443&quot;SARA: Segment aware rate adaptation algorithm for dynamic adaptive streaming over HTTP.&quot
    63616444Communication Workshop (ICCW), 2015 IEEE International Conference on, IEEE,
    636264452015.
    63636446doi:10.1109/iccw.2015.7247436.
     6447</li>
     6448<br>
     6449
     6450<li>
     6451<b>Juluri, Parikshit and Tamarapalli, Venkatesh and Medhi, Deep</b>,
     6452&quot;QoE management in DASH systems using the segment aware rate adaptation algorithm.&quot
     6453NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium, IEEE,
     64542016.
     6455doi:10.1109/noms.2016.7502805.
    63646456</li>
    63656457<br>
     
    65016593<li>
    65026594<b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>,
     6595&quot;Network capabilities of cloud services for a real time scientific application.&quot
     659637th Annual IEEE Conference on Local Computer Networks, Clearwater Beach, FL, USA, IEEE,
     65972012.
     6598doi:10.1109/lcn.2012.6423665.
     6599</li>
     6600<br>
     6601
     6602<li>
     6603<b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>,
    65036604&quot;Performance of GENI Cloud Testbeds for Real Time Scientific Application.&quot
    65046605First GENI Research and Educational Experiment Workshop (GREE 2012), Los Angeles,
    650566062012.
    65066607
    6507 </li>
    6508 <br>
    6509 
    6510 <li>
    6511 <b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>,
    6512 &quot;Network capabilities of cloud services for a real time scientific application.&quot
    6513 37th Annual IEEE Conference on Local Computer Networks, Clearwater Beach, FL, USA, IEEE,
    6514 2012.
    6515 doi:10.1109/lcn.2012.6423665.
    65166608</li>
    65176609<br>
     
    68406932<li>
    68416933<b>Mambretti, Joe and Chen, Jim and Yeh, Fei</b>,
    6842 &quot;Software-Defined Network Exchanges (SDXs): Architecture, services, capabilities, and foundation technologies.&quot
    6843 Teletraffic Congress (ITC), 2014 26th International, IEEE,
    6844 2014.
    6845 doi:10.1109/itc.2014.6932970.
     6934&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
     6935Computer Networks,
     69362014.
     6937doi:10.1016/j.bjp.2013.12.024.
    68466938</li>
    68476939<br>
     
    68586950<li>
    68596951<b>Mambretti, Joe and Chen, Jim and Yeh, Fei</b>,
    6860 &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
    6861 Computer Networks,
    6862 2014.
    6863 doi:10.1016/j.bjp.2013.12.024.
     6952&quot;Software-Defined Network Exchanges (SDXs): Architecture, services, capabilities, and foundation technologies.&quot
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