| 156 | ==== Application Centric Network Orchestration Framework: ODENOS ==== |
| 157 | |
| 158 | We demonstrate a virtual network orchestrator framework, called ODENOS (Object-DEfined Network Operating System). ODENOS allows end users and application service providers to create and control virtual networks on top of heterogeneous (multi-layer and multi-domain) WAN (Wide Area Network) in an integrated way. |
| 159 | ODENOS has a powerful graph-based network abstraction that can accommodate different kinds of network domains and layers, where any kind of network is abstracted as a graph of node, port, link, and flow. ODENOS also has a modularity and hierarchical structure, where modules can be stacked and are allowed to be inserted or removed. With the powerful abstraction, ODENOS can federate different network administrative domains. Also, ODENOS can slice a network and delegate the control of slices to application service providers. In addition, ODENOS can provide virtual network view and control API (Application Programming Interface) for each application service providers. |
| 160 | ODENOS is an open source software released in February 2015, and distributed on GitHub. ODENOS is a part of Japanese government funded project, called O3, and the project member includes major Japanese telecom carriers and vendors, such as NTT, NTT Communications, Fujitsu, Hitachi and NEC. |
| 161 | Our demonstration shows that ODENOS provides virtual networks that enable application service providers to satisfy requirements for application service quality without considering network architecture in detail. In the demonstration, ODENOS slices carrier networks consisting of multi-layer and multi-domain networks on demand, and performs application service provisioning smoothly. Types of application are video delivery and monitoring, and will be IoT (Internet of Things) service in the future. In addition, we show that ODENOS provides virtual network view of each service providers by user-friendly GUI (Graphical User Interface). |
| 162 | |
| 163 | Participants: |
| 164 | * Satoshi Kamiya, kamiya@ak.jp.nec.com, NEC Corporation |
| 165 | * Kazuya Suzuki |
| 166 | * Masahiro Hayashitani |
| 167 | * Yoshiaki Kiriha |
| 168 | |
| 169 | ==== Building A Software Defined Networking-Based Communication Framework for Emergency Response ==== |
| 170 | |
| 171 | Timely and reliable data transfer between incident sites and emergency management office has played a key role in emergency response applications. In this project, we have been building a communication framework for ensuring minimal delay guarantee in emergency response networks by using Software Defined Networking (SDN) techniques. In this poster and demo, we will demonstrate the proposed communication framework whose experiments have been conducted on the Global Environment for Networking Innovations (GENI) testbed, and show the evaluation results. More precisely, we will demonstrate how to leverage an SDN controller to choose the best path between incident sites and emergency management office according to an objective, in this example, a path with minimal delay so as to minimize response delays in emergency communication networks. |
| 172 | |
| 173 | Participants: |
| 174 | * Kaiqi Xiong, kqxiong18@gmail.com |
| 175 | |
| 176 | ==== GENI Cinema ==== |
| 177 | |
| 178 | Video streaming over the Internet, be it static or live streaming, is rapidly increasing in popularity. Many video streaming services exist to serve a variety of needs, such as video conferencing, entertainment, education, and the broadcast of live events. These services rely heavily on the server application to adapt to increasing and decreasing demand for a particular video resource. Furthermore, they require the reallocation of resources and the restart of the stream when a client stops, starts, and/or switches to a different stream. SDN and specifically OpenFlow can be creatively used to reallocate some of these tasks to the network and link layers. |
| 179 | |
| 180 | Our goal is to provide a scalable service for GENI using OpenFlow that supports the broadcast of live video streams from an arbitrary number of video-producers to an arbitrary number of video-consumers, where video-consumers can change “channels” without disrupting their existing stream and without affecting the load on a particular video stream source. |
| 181 | |
| 182 | Participants: |
| 183 | * Ryan Izard, rizard@g.clemson.edu, Clemson University |
| 184 | * Qing Wang |
| 185 | * Geddings Barrineau |
| 186 | * KC Wang |
| 187 | |
| 188 | ==== SDN/OpenFlow GENI lab exercises to measure and improve QoS/QoA/QoE ==== |
| 189 | |
| 190 | We have prepared a set of SDN/OpenFlow GENI lab exercises to measure and improve QoS/QoA/QoE for advanced Cloud Computing course and use one of these labs as a demo. During the demo we solve a problem of running a real research application called LOFT over a simple network infrastructure in a disaster scenario. The LOFT is used for regional scale tracking purposes and therefore requires fast image transferring from the collection site to the computation site. Moreover, in a disaster scenario regular networks usually are congested. To solve this real research problem, we perform traffic engineering in overlay network to overcome congestions. Finally, we show QoS, QoA and QoE improvement, based on following metrics: available Bandwidth (Objective QoS), Bandwidth Consumption (Objective QoA), File Transfer Time (Objective QoA), Mean Opinion Score (Subjective QoE). We note that this demo is based on one of the labs for advanced Cloud Computing course and can be used for education. |
| 191 | |
| 192 | Participants: |
| 193 | * Prasad Calyam, calyamp@missouri.edu, University of Missouri |
| 194 | * Dmitrii Chemodanov |
| 195 | |
| 196 | ==== Managing NFV using SDN and control theory ==== |
| 197 | |
| 198 | This demo shows that control theory and SDN (Software Defined Networking) are key components for NFV (Network Function Virtualization) deployment. The management architecture of RINA (a clean-slate Recursive InterNetwork Architecture) is used to manage Virtual Network Function (VNF) instances over the GENI testbed. |
| 199 | |
| 200 | In this demo, we will deploy an Intrusion Detection and Prevention System (IDPS) as the VNF. Our network topology has source and destination hosts, multiple IDPSes, an Open vSwitch (OVS) and an OpenFlow controller. |
| 201 | |
| 202 | A distributed management application running on RINA measures the state of the VNF instances and communicates this information to the OpenFlow controller. The controller uses a control-theoretic approach to balance load across the VNF instances by updating flow rules on the OVS switch. |
| 203 | |
| 204 | This demo demonstrates the benefits of RINA management and control-theoretic load balancing in virtualized environments. It also shows that GENI can easily support a wide range of SDN and NFV related experiments. |
| 205 | |
| 206 | Participants: |
| 207 | * Ibrahim Matta |
| 208 | * Nabeel Akhtar, nabeel@bu.edu, Boston University |
| 209 | |
| 210 | ==== Experimental Demonstration of Brokered Orchestration for end-to-end Service Provisioning and Interoperability across Heterogeneous Multi-Operator (Multi-AS) Optical Networks ==== |
| 211 | |
| 212 | A broker on top of opaquely-managed optical domains advertising their capabilities is proposed to provision multi-AS connections in multi-operator scenarios. In case of no spectrum continuity, intra-domain spectral defragmentation is performed. Experimental assessment was conducted on a distributed multi-continental infrastructure. |
| 213 | |
| 214 | Participants: |
| 215 | * Alberto Castro, albcastro@ucdavis.edu, University of California-Davis |
| 216 | * Lluis Gifre |
| 217 | * Cen Chen |
| 218 | * Jie Yin |
| 219 | * Zuqin Zhu |
| 220 | * Luis Velasco |
| 221 | * S. J. Ben Yoo |
| 222 | |
| 223 | ==== Architectural Issues in Virtualizing Intrusion Detection System as a Network Function ==== |
| 224 | |
| 225 | "Networking Services Providers face many challenges to introducing a new network service. Traditionally such services are offered through custom hardware appliances, which are difficult to deploy, have a limited life cycle, and are tied to a particular service. Virtualization of Network Functions promises many of the advantages that Cloud Computing has offered to traditional computing: efficient resource utilization, economies of scale, use of commodity hardware, elastic resource scaling, speedy deployment of new services, etc. We look at security features as network functions (NFs) that can be virtualized and offered as a service. In particular, we propose different ”security-as-a-service” architecture scenarios for intrusion detection/prevention system (IDS/IPS), and analyze the security and cost implications of the architecture choice. We create a framework to study the impact of architecture choices. We validate several of these architectures in a realistic deployment on GENI and also study their impact on network performance. |
| 226 | |
| 227 | Our deployment on GENI uses dynamically reserved compute and network resources at multiple sites across the country to realistically emulate various cloud deployment scenarios. As future work, we plan on creating a number of virtualized network functions (VNFs) and orchestrating service function chains that can integrate in the ChoiceNet (NSF FIA) framework." |
| 228 | |
| 229 | Participants: |
| 230 | * Harshvardhan P. Joshi, hpjoshi@ncsu.edu, North Carolina State University |
| 231 | * Rudra Dutta |
| 232 | |
| 233 | ==== A Public Safety 3D Surveillance Network ==== |
| 234 | |
| 235 | The project describes a mobile surveillance system to help law enforcement better perform public surveillance. Conventional and 3D cameras are mounted on the police vehicles to stream data in real-time to the cloud for processing. We use SDN to control the network flow to prioritize more important videos from less important ones. The 3D cameras are used to automatically detect potentially suspicious incidents in poor light conditions, e.g. person hiding in the dark, and acts as an input to the SDN controller. The poster will describe the overall surveillance system. The demo will include video clips of how the 3D cameras perform in the dark. |
| 236 | |
| 237 | Participants: |
| 238 | * Md Zakirul Alam Bhuiyan |
| 239 | * Waqas Latif |
| 240 | * Pengpeng Liang |
| 241 | * Joshua Lloret |
| 242 | * Haibin Ling |
| 243 | * Chiu C. Tan, cctan@temple.edu, Temple University |
| 244 | * Jie Wu |
| 245 | |
| 246 | ==== Frequency-Minimal Moving Target Defense using Software Defined Networking ==== |
| 247 | |
| 248 | With the increase of cyber attacks such as DDoS, there is a need for intelligent counter-strategies to protect critical cloud-hosted applications. The challenge for the defense is to minimize the wastage of cloud resources and limit loss of availability, yet have effective proactive and reactive measures that can thwart attackers. In this poster, we address the defense needs by leveraging moving target defense protection within Software Defined Networking-enabled cloud infrastructure. Our novelty is in the frequency minimization and consequent location selection of target movement across heterogeneous virtual machines based on attack probability, which in turn minimizes cloud management overheads. We evaluate effectiveness of our scheme using a large-scale GENI testbed for a just-in-time news feed application setup. Our results show low attack success rate and higher performance of target application in comparison to the existing static moving target defense schemes that assume homogeneous virtual machines. |
| 249 | |
| 250 | Participants: |
| 251 | * Saptarshi Debroy, debroysa@missouri.edu, University of Missouri |
| 252 | * Prasad Calyam |
| 253 | |
| 254 | |
| 255 | |
| 256 | |
| 257 | |
| 258 | |