Changes between Version 54 and Version 55 of GENIBibliography


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Timestamp:
05/09/17 16:46:03 (2 years ago)
Author:
Mark Berman
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  • GENIBibliography

    v54 v55  
    955955<li>
    956956<b>Chin, Tommy and Mountrouidou, Xenia and Li, Xiangyang and Xiong, Kaiqi</b>
     957, &quot;An SDN-supported collaborative approach for DDoS flooding detection and containment.&quot;
     958Military Communications Conference, MILCOM 2015 - 2015 IEEE, IEEE,
     9592015.
     960doi:10.1109/milcom.2015.7357519.
     961<a href="http://dx.doi.org/10.1109/milcom.2015.7357519">http://dx.doi.org/10.1109/milcom.2015.7357519</a>
     962<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.
     963</li>
     964<br>
     965
     966<li>
     967<b>Chin, Tommy and Mountrouidou, Xenia and Li, Xiangyang and Xiong, Kaiqi</b>
    957968, &quot;Selective Packet Inspection to Detect DoS Flooding Using Software Defined Networking (SDN).&quot;
    958969Distributed Computing Systems Workshops (ICDCSW), 2015 IEEE 35th International Conference on, IEEE,
     
    964975<br>
    965976
    966 <li>
    967 <b>Chin, Tommy and Mountrouidou, Xenia and Li, Xiangyang and Xiong, Kaiqi</b>
    968 , &quot;An SDN-supported collaborative approach for DDoS flooding detection and containment.&quot;
    969 Military Communications Conference, MILCOM 2015 - 2015 IEEE, IEEE,
    970 2015.
    971 doi:10.1109/milcom.2015.7357519.
    972 <a href="http://dx.doi.org/10.1109/milcom.2015.7357519">http://dx.doi.org/10.1109/milcom.2015.7357519</a>
    973 <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.
    974 </li>
    975 <br>
    976 
    977 
     977
     978
     979<li>
     980<b>Chin, Tommy and Xiong, Kaiqi</b>
     981, &quot;MPBSD: A Moving Target Defense Approach for Base Station Security in Wireless Sensor Networks.&quot;
     982Wireless Algorithms, Systems, and Applications, Springer International Publishing,
     9832016.
     984doi:10.1007/978-3-319-42836-9&#x005F;43.
     985<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>
     986<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.
     987</li>
     988<br>
    978989
    979990<li>
     
    985996<a href="http://dx.doi.org/10.1109/eitec.2016.7503690">http://dx.doi.org/10.1109/eitec.2016.7503690</a>
    986997<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.
    987 </li>
    988 <br>
    989 
    990 <li>
    991 <b>Chin, Tommy and Xiong, Kaiqi</b>
    992 , &quot;MPBSD: A Moving Target Defense Approach for Base Station Security in Wireless Sensor Networks.&quot;
    993 Wireless Algorithms, Systems, and Applications, Springer International Publishing,
    994 2016.
    995 doi:10.1007/978-3-319-42836-9&#x005F;43.
    996 <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>
    997 <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.
    998998</li>
    999999<br>
     
    10151015
    10161016<li>
     1017<b>Chung, Joaquin and Owen, Henry and Clark, Russell</b>
     1018, &quot;SDX architectures: A qualitative analysis.&quot;
     1019SoutheastCon 2016, Norfolk, VA, USA, IEEE,
     10202016.
     1021doi:10.1109/secon.2016.7506749.
     1022<a href="http://dx.doi.org/10.1109/secon.2016.7506749">http://dx.doi.org/10.1109/secon.2016.7506749</a>
     1023<br><br><b>Abstract: </b>A novel internetworking paradigm, software-defined exchange (SDX), allows multiple independent administrative domains to share computing, storage, and networking resources. Although the term SDX is very recent, the concept has already been used by many distinct disciplines. For example, cloud-computing researchers use it to add network virtualization resources to their inter-clouds, while networking researchers use it to insert SDN technologies into the networking exchange infrastructure. Despite the different uses, the efforts of the various disciplines that share networking resources converge to a single poing enabled by the virtualization and the separation of control and data planes. This paper presents a survey of the most relevant SDX studies from various research areas, focusing on their architectures. The paper defines a taxonomy for the SDX, provides generalized architecture models, and concludes by presenting a qualitative analysis of the architectures that focuses on the scalability, resilience, peering technologies, and deployment of SDX.
     1024</li>
     1025<br>
     1026
     1027
     1028
     1029<li>
     1030<b>Chung, Joaquín and Cox, Jacob and Ibarra, Julio and Bezerra, Jerônimo and Morgan, Heidi and Clark, Russell and Owen, Henry</b>
     1031, &quot;AtlanticWave-SDX: An International SDX to Support Science Data Applications.&quot;
     1032International Conference for High Performance Computing, Networking, Storage and Analysis (SC15), Austin,
     10332015.
     1034
     1035<a href="http://amlight.net/wp-content/uploads/2015/04/AtlanticWave-SDX.pdf">http://amlight.net/wp-content/uploads/2015/04/AtlanticWave-SDX.pdf</a>
     1036<br><br><b>Abstract: </b>New scientific instruments that are being designed and deployed in the coming years will dramatically increase the need for large, real-time data transfers among scientists throughout the world. One such instrument is the Large Synoptic Survey Telescope being built in Chile that will produce 6.4 GB images every 17 seconds. This paper describes an ongoing effort to meet the demands of these large data scientific instruments through the development of an international software defined exchange point (SDX) that will meet the provisioning needs for the scientific users. The specific planned and ongoing work in SDX architecture is described with specific consideration for policy specification and security.
     1037</li>
     1038<br>
     1039
     1040
     1041
     1042<li>
    10171043<b>Collings, Jake and Liu, Jun</b>
    10181044, &quot;An OpenFlow-Based Prototype of SDN-Oriented Stateful Hardware Firewalls.&quot;
     
    10871113<a href="https://www.usenix.org/conference/nsdi15/technical-sessions/presentation/dong">https://www.usenix.org/conference/nsdi15/technical-sessions/presentation/dong</a>
    10881114
     1115</li>
     1116<br>
     1117
     1118
     1119
     1120<li>
     1121<b>Donovan, Sean and Chung, Joaquin and Sanders, Matt and Clark, Russ</b>
     1122, &quot;MetroSDX: A resilient edge network for the smart community.&quot;
     11232017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Kona, Big Island, HI, USA, IEEE,
     11242017.
     1125doi:10.1109/percomw.2017.7917626.
     1126<a href="http://dx.doi.org/10.1109/percomw.2017.7917626">http://dx.doi.org/10.1109/percomw.2017.7917626</a>
     1127<br><br><b>Abstract: </b>Smart and connected communities and their associated edge devices are creating new demands on network services. Edge network connectivity is often not resilient to failures, leading to data loss when network devices are isolated by the failure of a single service provider, while other providers are still functional. We propose MetroSDX, a neutral network design that increases the resiliency of edge networks and global and local services, improves isolation of network functions, and preserves data from edge devices when they are disconnected. MetroSDX is a software-defined exchange, a meet-me point for exchanging computing, storage, and networking resources. This work focuses on MetroSDX's approach to location specific resilience and performance in this multi-network paradigm with an eye towards addressing increased demands from the growing set of connected devices and services which will increasingly and inevitably require communication between and across elements connected to multiple networks.
    10891128</li>
    10901129<br>
     
    13281367<li>
    13291368<b>Fioravanti, Mark E.</b>
    1330 , &quot;Digital Quorum Sensing for Self-Organizing Malware (PhD Thesis).&quot;
     1369, &quot;Digital Quorum Sensing for Self-Organizing Malware (Doctoral dissertation).&quot;
    13311370Melbourne, Florida,
    133213712016.
     
    14971536<li>
    14981537<b>Gosain, Abhimanyu and Seskar, Ivan</b>
     1538, &quot;GENI wireless testbed: An open edge ecosystem for ubiquitous computing applications.&quot;
     15392017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Kona, Big Island, HI, USA, IEEE,
     15402017.
     1541doi:10.1109/percomw.2017.7917520.
     1542<a href="http://dx.doi.org/10.1109/percomw.2017.7917520">http://dx.doi.org/10.1109/percomw.2017.7917520</a>
     1543<br><br><b>Abstract: </b>This demo presents the architecture of GENI (Global Environment of Network Innovations) [1] edge cloud computing network in the form of compute and storage systems, a mobile 4G LTE edge and a high speed campus network. GENI's edge computing strategy proceeds by deploying self-contained packages of network, computing, storage resources, or GENI Racks [2] connected via high speed fiber to LTE BS(s) across twelve campuses in the US, all interconnected via a nationwide research network. The GENI mobile computing resource manager is based on the Orbit Management framework (OMF) [3] and provides seamless access to the computing resources via the GENI Portal for experimentation, scheduling, data collection and processing of ubiquitous computing applications.
     1544</li>
     1545<br>
     1546
     1547<li>
     1548<b>Gosain, Abhimanyu and Seskar, Ivan</b>
    14991549, &quot;GENI Wireless Testbed: A Flexible Open Ecosystem for Wireless Communications Research: Demo.&quot;
    15001550Proceedings of the 22Nd Annual International Conference on Mobile Computing and Networking, New York City, New York, ACM, New York, NY, USA,
     
    15201570
    15211571
     1572
     1573<li>
     1574<b>Griffioen, J. and Fei, Zongming and Nasir, H. and Wu, Xiongqi and Reed, J. and Carpenter, C.</b>
     1575, &quot;The design of an instrumentation system for federated and virtualized network testbeds.&quot;
     1576Network Operations and Management Symposium (NOMS), 2012 IEEE, IEEE,
     15772012.
     1578doi:10.1109/NOMS.2012.6212061.
     1579<a href="http://dx.doi.org/10.1109/NOMS.2012.6212061">http://dx.doi.org/10.1109/NOMS.2012.6212061</a>
     1580<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.
     1581</li>
     1582<br>
    15221583
    15231584<li>
     
    15321593<br>
    15331594
    1534 <li>
    1535 <b>Griffioen, J. and Fei, Zongming and Nasir, H. and Wu, Xiongqi and Reed, J. and Carpenter, C.</b>
    1536 , &quot;The design of an instrumentation system for federated and virtualized network testbeds.&quot;
    1537 Network Operations and Management Symposium (NOMS), 2012 IEEE, IEEE,
    1538 2012.
    1539 doi:10.1109/NOMS.2012.6212061.
    1540 <a href="http://dx.doi.org/10.1109/NOMS.2012.6212061">http://dx.doi.org/10.1109/NOMS.2012.6212061</a>
    1541 <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.
    1542 </li>
    1543 <br>
    1544 
    15451595
    15461596
     
    17291779<li>
    17301780<b>Huang, Shufeng and Griffioen, James and Calvert, Ken</b>
     1781, &quot;PVNs: Making virtualized network infrastructure usable.&quot;
     17822012 ACM/IEEE Symposium on Architectures for Networking and Communications Systems (ANCS),
     17832012.
     1784
     1785<a href="http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7846352">http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7846352</a>
     1786<br><br><b>Abstract: </b>Network virtualization is becoming a fundamental building block of future Internet architectures. Although the underlying network infrastructure needed to dynamically create and deploy custom virtual networks is rapidly taking shape ( e.g., GENI), constructing and using a virtual network is still a challenging and labor intensive task, one best left to experts. In this paper, we present the concept of a Packaged Virtual Network (PVN), that enables normal users to easily download, deploy and use application-specific virtual networks. At the heart of our approach is a PVN Hypervisor that ” runs” a PVN by allocating the virtual network resources needed by the PVN and then connecting the PVN's participants into the network on demand. To demonstrate our PVN approach, we implemented a multicast PVN that runs on the PVN hypervisor prototype using ProtoGENI as the underlying virtual network, allowing average users to create their own private multicast network.
     1787</li>
     1788<br>
     1789
     1790<li>
     1791<b>Huang, Shufeng and Griffioen, James and Calvert, Ken</b>
    17311792, &quot;PVNs: Making Virtualized Network Infrastructure Usable.&quot;
    17321793ACM/IEEE Symposium on Architectures for Networking and Communications Systems (ANCS '12),
     
    17341795doi:10.1145/2396556.2396590.
    17351796<a href="http://dx.doi.org/10.1145/2396556.2396590">http://dx.doi.org/10.1145/2396556.2396590</a>
    1736 <br><br><b>Abstract: </b>Network virtualization is becoming a fundamental building block of future Internet architectures. Although the underlying network infrastructure needed to dynamically create and deploy custom virtual networks is rapidly taking shape ( e.g., GENI), constructing and using a virtual network is still a challenging and labor intensive task, one best left to experts. In this paper, we present the concept of a Packaged Virtual Network (PVN), that enables normal users to easily download, deploy and use application-specific virtual networks. At the heart of our approach is a PVN Hypervisor that ” runs” a PVN by allocating the virtual network resources needed by the PVN and then connecting the PVN's participants into the network on demand. To demonstrate our PVN approach, we implemented a multicast PVN that runs on the PVN hypervisor prototype using ProtoGENI as the underlying virtual network, allowing average users to create their own private multicast network.
    1737 </li>
    1738 <br>
    1739 
    1740 <li>
    1741 <b>Huang, Shufeng and Griffioen, James and Calvert, Ken</b>
    1742 , &quot;PVNs: Making virtualized network infrastructure usable.&quot;
    1743 2012 ACM/IEEE Symposium on Architectures for Networking and Communications Systems (ANCS),
    1744 2012.
    1745 
    1746 <a href="http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7846352">http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7846352</a>
    17471797<br><br><b>Abstract: </b>Network virtualization is becoming a fundamental building block of future Internet architectures. Although the underlying network infrastructure needed to dynamically create and deploy custom virtual networks is rapidly taking shape ( e.g., GENI), constructing and using a virtual network is still a challenging and labor intensive task, one best left to experts. In this paper, we present the concept of a Packaged Virtual Network (PVN), that enables normal users to easily download, deploy and use application-specific virtual networks. At the heart of our approach is a PVN Hypervisor that ” runs” a PVN by allocating the virtual network resources needed by the PVN and then connecting the PVN's participants into the network on demand. To demonstrate our PVN approach, we implemented a multicast PVN that runs on the PVN hypervisor prototype using ProtoGENI as the underlying virtual network, allowing average users to create their own private multicast network.
    17481798</li>
     
    20242074<li>
    20252075<b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>
    2026 , &quot;Performance of GENI Cloud Testbeds for Real Time Scientific Application.&quot;
    2027 First GENI Research and Educational Experiment Workshop (GREE 2012), Los Angeles,
    2028 2012.
    2029 
    2030 
    2031 <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.
    2032 </li>
    2033 <br>
    2034 
    2035 <li>
    2036 <b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>
    20372076, &quot;Network capabilities of cloud services for a real time scientific application.&quot;
    2038207737th Annual IEEE Conference on Local Computer Networks, Clearwater Beach, FL, USA, IEEE,
     
    20412080<a href="http://dx.doi.org/10.1109/lcn.2012.6423665">http://dx.doi.org/10.1109/lcn.2012.6423665</a>
    20422081<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.
     2082</li>
     2083<br>
     2084
     2085<li>
     2086<b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>
     2087, &quot;Performance of GENI Cloud Testbeds for Real Time Scientific Application.&quot;
     2088First GENI Research and Educational Experiment Workshop (GREE 2012), Los Angeles,
     20892012.
     2090
     2091
     2092<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.
    20432093</li>
    20442094<br>
     
    24252475<li>
    24262476<b>Mambretti, Joe and Chen, Jim and Yeh, Fei</b>
     2477, &quot;Next Generation Virtual Network Architecture for Multi-tenant Distributed Clouds: Challenges and Emerging Techniques.&quot;
     2478Proceedings of the 4th Workshop on Distributed Cloud Computing, Chicago, Illinois, ACM, New York, NY, USA,
     24792016.
     2480doi:10.1145/2955193.2955194.
     2481<a href="http://dx.doi.org/10.1145/2955193.2955194">http://dx.doi.org/10.1145/2955193.2955194</a>
     2482<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.
     2483</li>
     2484<br>
     2485
     2486<li>
     2487<b>Mambretti, Joe and Chen, Jim and Yeh, Fei</b>
    24272488, &quot;Software-Defined Network Exchanges (SDXs): Architecture, services, capabilities, and foundation technologies.&quot;
    24282489Teletraffic Congress (ITC), 2014 26th International, IEEE,
     
    24312492<a href="http://dx.doi.org/10.1109/itc.2014.6932970">http://dx.doi.org/10.1109/itc.2014.6932970</a>
    24322493<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.
    2433 </li>
    2434 <br>
    2435 
    2436 <li>
    2437 <b>Mambretti, Joe and Chen, Jim and Yeh, Fei</b>
    2438 , &quot;Next Generation Virtual Network Architecture for Multi-tenant Distributed Clouds: Challenges and Emerging Techniques.&quot;
    2439 Proceedings of the 4th Workshop on Distributed Cloud Computing, Chicago, Illinois, ACM, New York, NY, USA,
    2440 2016.
    2441 doi:10.1145/2955193.2955194.
    2442 <a href="http://dx.doi.org/10.1145/2955193.2955194">http://dx.doi.org/10.1145/2955193.2955194</a>
    2443 <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.
    24442494</li>
    24452495<br>
     
    29763026<li>
    29773027<b>Rajagopalan, Sudharsan</b>
    2978 , &quot;Leveraging OpenFlow for Resource Placement of Virtual Desktop Cloud Applications.&quot;
     3028, &quot;Leveraging OpenFlow for Resource Placement of Virtual Desktop Cloud Applications (Master's thesis).&quot;
    29793029
    298030302013.
     
    39253975<li>
    39263976<b>Van Vorst, N. and Erazo, M. and Liu, J.</b>
    3927 , &quot;PrimoGENI for hybrid network simulation and emulation experiments in GENI.&quot;
    3928 Journal of Simulation,
    3929 2012.
    3930 doi:10.1057/jos.2012.5.
    3931 <a href="http://dx.doi.org/10.1057/jos.2012.5">http://dx.doi.org/10.1057/jos.2012.5</a>
    3932 <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.
    3933 </li>
    3934 <br>
    3935 
    3936 <li>
    3937 <b>Van Vorst, N. and Erazo, M. and Liu, J.</b>
    39383977, &quot;PrimoGENI: Integrating Real-Time Network Simulation and Emulation in GENI.&quot;
    39393978Principles of Advanced and Distributed Simulation (PADS), 2011 IEEE Workshop on, Nice, France, IEEE,
     
    39423981<a href="http://dx.doi.org/10.1109/pads.2011.5936747">http://dx.doi.org/10.1109/pads.2011.5936747</a>
    39433982<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.
     3983</li>
     3984<br>
     3985
     3986<li>
     3987<b>Van Vorst, N. and Erazo, M. and Liu, J.</b>
     3988, &quot;PrimoGENI for hybrid network simulation and emulation experiments in GENI.&quot;
     3989Journal of Simulation,
     39902012.
     3991doi:10.1057/jos.2012.5.
     3992<a href="http://dx.doi.org/10.1057/jos.2012.5">http://dx.doi.org/10.1057/jos.2012.5</a>
     3993<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.
    39443994</li>
    39453995<br>
     
    51725222<li>
    51735223<b>Chen, Kang and Shen, Haiying</b>
     5224, &quot;Cont2: Social-Aware Content and Contact Based File Search in Delay Tolerant Networks.&quot
     5225Proceedings of the 2013 42Nd International Conference on Parallel Processing, IEEE Computer Society, Washington, DC, USA,
     52262013.
     5227doi:10.1109/icpp.2013.28.
     5228</li>
     5229<br>
     5230
     5231<li>
     5232<b>Chen, Kang and Shen, Haiying</b>
    51745233, &quot;Global optimization of file availability through replication for efficient file sharing in MANETs.&quot
    51755234Network Protocols (ICNP), 2011 19th IEEE International Conference on, Vancouver, AB, Canada, IEEE,
    517652352011.
    51775236doi:10.1109/icnp.2011.6089056.
    5178 </li>
    5179 <br>
    5180 
    5181 <li>
    5182 <b>Chen, Kang and Shen, Haiying</b>
    5183 , &quot;Cont2: Social-Aware Content and Contact Based File Search in Delay Tolerant Networks.&quot
    5184 Proceedings of the 2013 42Nd International Conference on Parallel Processing, IEEE Computer Society, Washington, DC, USA,
    5185 2013.
    5186 doi:10.1109/icpp.2013.28.
    51875237</li>
    51885238<br>
     
    52585308<li>
    52595309<b>Chin, Tommy and Mountrouidou, Xenia and Li, Xiangyang and Xiong, Kaiqi</b>
     5310, &quot;An SDN-supported collaborative approach for DDoS flooding detection and containment.&quot
     5311Military Communications Conference, MILCOM 2015 - 2015 IEEE, IEEE,
     53122015.
     5313doi:10.1109/milcom.2015.7357519.
     5314</li>
     5315<br>
     5316
     5317<li>
     5318<b>Chin, Tommy and Mountrouidou, Xenia and Li, Xiangyang and Xiong, Kaiqi</b>
    52605319, &quot;Selective Packet Inspection to Detect DoS Flooding Using Software Defined Networking (SDN).&quot
    52615320Distributed Computing Systems Workshops (ICDCSW), 2015 IEEE 35th International Conference on, IEEE,
    526253212015.
    52635322doi:10.1109/icdcsw.2015.27.
    5264 </li>
    5265 <br>
    5266 
    5267 <li>
    5268 <b>Chin, Tommy and Mountrouidou, Xenia and Li, Xiangyang and Xiong, Kaiqi</b>
    5269 , &quot;An SDN-supported collaborative approach for DDoS flooding detection and containment.&quot
    5270 Military Communications Conference, MILCOM 2015 - 2015 IEEE, IEEE,
    5271 2015.
    5272 doi:10.1109/milcom.2015.7357519.
    52735323</li>
    52745324<br>
     
    53085358
    53095359<li>
     5360<b>Chung, Joaquin and Owen, Henry and Clark, Russell</b>
     5361, &quot;SDX architectures: A qualitative analysis.&quot
     5362SoutheastCon 2016, Norfolk, VA, USA, IEEE,
     53632016.
     5364doi:10.1109/secon.2016.7506749.
     5365</li>
     5366<br>
     5367
     5368
     5369
     5370<li>
     5371<b>Chung, Joaquín and Cox, Jacob and Ibarra, Julio and Bezerra, Jerônimo and Morgan, Heidi and Clark, Russell and Owen, Henry</b>
     5372, &quot;AtlanticWave-SDX: An International SDX to Support Science Data Applications.&quot
     5373International Conference for High Performance Computing, Networking, Storage and Analysis (SC15), Austin,
     53742015.
     5375
     5376</li>
     5377<br>
     5378
     5379
     5380
     5381<li>
    53105382<b>Collings, Jake and Liu, Jun</b>
    53115383, &quot;An OpenFlow-Based Prototype of SDN-Oriented Stateful Hardware Firewalls.&quot
     
    536854402015.
    53695441
     5442</li>
     5443<br>
     5444
     5445
     5446
     5447<li>
     5448<b>Donovan, Sean and Chung, Joaquin and Sanders, Matt and Clark, Russ</b>
     5449, &quot;MetroSDX: A resilient edge network for the smart community.&quot
     54502017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Kona, Big Island, HI, USA, IEEE,
     54512017.
     5452doi:10.1109/percomw.2017.7917626.
    53705453</li>
    53715454<br>
     
    55735656<li>
    55745657<b>Fioravanti, Mark E.</b>
    5575 , &quot;Digital Quorum Sensing for Self-Organizing Malware (PhD Thesis).&quot
     5658, &quot;Digital Quorum Sensing for Self-Organizing Malware (Doctoral dissertation).&quot
    55765659Melbourne, Florida,
    557756602016.
     
    57165799<li>
    57175800<b>Gosain, Abhimanyu and Seskar, Ivan</b>
     5801, &quot;GENI wireless testbed: An open edge ecosystem for ubiquitous computing applications.&quot
     58022017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Kona, Big Island, HI, USA, IEEE,
     58032017.
     5804doi:10.1109/percomw.2017.7917520.
     5805</li>
     5806<br>
     5807
     5808<li>
     5809<b>Gosain, Abhimanyu and Seskar, Ivan</b>
    57185810, &quot;GENI Wireless Testbed: A Flexible Open Ecosystem for Wireless Communications Research: Demo.&quot
    57195811Proceedings of the 22Nd Annual International Conference on Mobile Computing and Networking, New York City, New York, ACM, New York, NY, USA,
     
    59126004<li>
    59136005<b>Huang, Shufeng and Griffioen, James and Calvert, Ken</b>
     6006, &quot;PVNs: Making Virtualized Network Infrastructure Usable.&quot
     6007ACM/IEEE Symposium on Architectures for Networking and Communications Systems (ANCS '12),
     60082012.
     6009doi:10.1145/2396556.2396590.
     6010</li>
     6011<br>
     6012
     6013<li>
     6014<b>Huang, Shufeng and Griffioen, James and Calvert, Ken</b>
    59146015, &quot;PVNs: Making virtualized network infrastructure usable.&quot
    591560162012 ACM/IEEE Symposium on Architectures for Networking and Communications Systems (ANCS),
    591660172012.
    59176018
    5918 </li>
    5919 <br>
    5920 
    5921 <li>
    5922 <b>Huang, Shufeng and Griffioen, James and Calvert, Ken</b>
    5923 , &quot;PVNs: Making Virtualized Network Infrastructure Usable.&quot
    5924 ACM/IEEE Symposium on Architectures for Networking and Communications Systems (ANCS '12),
    5925 2012.
    5926 doi:10.1145/2396556.2396590.
    59276019</li>
    59286020<br>
     
    60096101<li>
    60106102<b>Juluri, Parikshit and Tamarapalli, Venkatesh and Medhi, Deep</b>
     6103, &quot;SARA: Segment aware rate adaptation algorithm for dynamic adaptive streaming over HTTP.&quot
     6104Communication Workshop (ICCW), 2015 IEEE International Conference on, IEEE,
     61052015.
     6106doi:10.1109/iccw.2015.7247436.
     6107</li>
     6108<br>
     6109
     6110<li>
     6111<b>Juluri, Parikshit and Tamarapalli, Venkatesh and Medhi, Deep</b>
    60116112, &quot;QoE management in DASH systems using the segment aware rate adaptation algorithm.&quot
    60126113NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium, IEEE,
    601361142016.
    60146115doi:10.1109/noms.2016.7502805.
    6015 </li>
    6016 <br>
    6017 
    6018 <li>
    6019 <b>Juluri, Parikshit and Tamarapalli, Venkatesh and Medhi, Deep</b>
    6020 , &quot;SARA: Segment aware rate adaptation algorithm for dynamic adaptive streaming over HTTP.&quot
    6021 Communication Workshop (ICCW), 2015 IEEE International Conference on, IEEE,
    6022 2015.
    6023 doi:10.1109/iccw.2015.7247436.
    60246116</li>
    60256117<br>
     
    61616253<li>
    61626254<b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>
     6255, &quot;Network capabilities of cloud services for a real time scientific application.&quot
     625637th Annual IEEE Conference on Local Computer Networks, Clearwater Beach, FL, USA, IEEE,
     62572012.
     6258doi:10.1109/lcn.2012.6423665.
     6259</li>
     6260<br>
     6261
     6262<li>
     6263<b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>
    61636264, &quot;Performance of GENI Cloud Testbeds for Real Time Scientific Application.&quot
    61646265First GENI Research and Educational Experiment Workshop (GREE 2012), Los Angeles,
    616562662012.
    61666267
    6167 </li>
    6168 <br>
    6169 
    6170 <li>
    6171 <b>Krishnappa, Dilip K. and Lyons, Eric and Irwin, David and Zink, Michael</b>
    6172 , &quot;Network capabilities of cloud services for a real time scientific application.&quot
    6173 37th Annual IEEE Conference on Local Computer Networks, Clearwater Beach, FL, USA, IEEE,
    6174 2012.
    6175 doi:10.1109/lcn.2012.6423665.
    61766268</li>
    61776269<br>
     
    65006592<li>
    65016593<b>Mambretti, Joe and Chen, Jim and Yeh, Fei</b>
     6594, &quot;Next Generation Virtual Network Architecture for Multi-tenant Distributed Clouds: Challenges and Emerging Techniques.&quot
     6595Proceedings of the 4th Workshop on Distributed Cloud Computing, Chicago, Illinois, ACM, New York, NY, USA,
     65962016.
     6597doi:10.1145/2955193.2955194.
     6598</li>
     6599<br>
     6600
     6601<li>
     6602<b>Mambretti, Joe and Chen, Jim and Yeh, Fei</b>
    65026603, &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
    65036604Computer Networks,
    650466052014.
    65056606doi:10.1016/j.bjp.2013.12.024.
    6506 </li>
    6507 <br>
    6508 
    6509 <li>
    6510 <b>Mambretti, Joe and Chen, Jim and Yeh, Fei</b>
    6511 , &quot;Next Generation Virtual Network Architecture for Multi-tenant Distributed Clouds: Challenges and Emerging Techniques.&quot
    6512 Proceedings of the 4th Workshop on Distributed Cloud Computing, Chicago, Illinois, ACM, New York, NY, USA,
    6513 2016.
    6514 doi:10.1145/2955193.2955194.
    65156607</li>
    65166608<br>
     
    68686960<li>
    68696961<b>Ozcelik, Ilker and Brooks, Richard R.</b>
     6962, &quot;Security experimentation using operational systems.&quot
     6963Proceedings of the Seventh Annual Workshop on Cyber Security and Information Intelligence Research, Oak Ridge, Tennessee, ACM, New York, NY, USA,
     69642011.
     6965doi:10.1145/2179298.2179388.
     6966</li>
     6967<br>
     6968
     6969<li>
     6970<b>Ozcelik, Ilker and Brooks, Richard R.</b>
    68706971, &quot;Operational System Testing for Designed in Security.&quot
    68716972Proceedings of the Eighth Annual Cyber Security and Information Intelligence Research Workshop, Oak Ridge, Tennessee, ACM, New York, NY, USA,
    687269732013.
    68736974doi:10.1145/2459976.2460038.
    6874 </li>
    6875 <br>
    6876 
    6877 <li>
    6878 <b>Ozcelik, Ilker and Brooks, Richard R.</b>
    6879 , &quot;Security experimentation using operational systems.&quot
    6880 Proceedings of the Seventh Annual Workshop on Cyber Security and Information Intelligence Research, Oak Ridge, Tennessee, ACM, New York, NY, USA,
    6881 2011.
    6882 doi:10.1145/2179298.2179388.
    68836975</li>
    68846976<br>
     
    69657057<li>
    69667058<b>Rajagopalan, Sudharsan</b>
    6967 , &quot;Leveraging OpenFlow for Resource Placement of Virtual Desktop Cloud Applications.&quot
     7059, &quot;Leveraging OpenFlow for Resource Placement of Virtual Desktop Cloud Applications (Master's thesis).&quot
    69687060
    696970612013.
     
    83108402<li> Berryman, Alex (Berryman, A.) </li>
    83118403<li> Beyene, Tsegereda </li>
     8404<li> Bezerra, Jero&#770;nimo </li>
    83128405<li> Bhanage, Gautam (Bhanage, G., Bhanage, G. D.) </li>
    83138406<li> Bhat, Divyashri </li>
     
    83658458<li> Chuah, M. </li>
    83668459<li> Chung, Chun-Jen </li>
     8460<li> Chung, Joaqui&#769;n (Chung, Joaquin) </li>
    83678461<li> Clancy, T. Charles </li>
    83688462<li> Clark, Russell (Clark, Russ) </li>
     
    83738467<li> Corner, Mark </li>
    83748468<li> Coulaby, Adama </li>
     8469<li> Cox, Jacob </li>
    83758470<li> Crovella, Mark </li>
    83768471<li> Crowley, Patrick </li>
     
    84058500<li> Dong, Chen </li>
    84068501<li> Dong, Mo </li>
    8407 <li> Donovan, Sean P. </li>
     8502<li> Donovan, Sean P. (Donovan, Sean) </li>
    84088503<li> Dos Santos, F. </li>
    84098504<li> Doucette, Cody </li>
     
    85028597<li> Husain, M. I. </li>
    85038598<li> Hussain, Alefiya </li>
     8599<li> Ibarra, Julio </li>
    85048600<li> Igarashi, K. </li>
    85058601<li> Ilyas, Muhammad U. </li>
     
    86688764<li> Moore, R. </li>
    86698765<li> Morago, B. </li>
     8766<li> Morgan, Heidi </li>
    86708767<li> Morita, Itsuro </li>
    86718768<li> Morsey, Mohamed </li>
     
    87118808<li> Ott, Maximilian (Ott, Max) </li>
    87128809<li> Ovon, Carol </li>
     8810<li> Owen, Henry </li>
    87138811<li> O&#776;zc&#807;elik, I&#775;lker (Ozcelik, I., Ozcelik, Ilker) </li>
    87148812<li> Padala, P. </li>
     
    87908888<li> Salvadori, E. </li>
    87918889<li> Sampathkumar, S. </li>
     8890<li> Sanders, Matt </li>
    87928891<li> Sathyaraja, Anandatirtha </li>
    87938892<li> Schaff, Nathan </li>
     
    89889087<!-- End HTML to be inserted into wiki page. -->
    89899088
     9089
    89909090}}}