7 | | With this in mind, in this demo we highlight one potential assignment for an undergraduate Distributed Systems or Networks course that has a unique emphasis on giving students hands-on access to distributed systems. The assignment asks students to implement multiple distribution and caching strategies in a simple content distribution network, and evaluate their performance under different load patterns. In this particular case, we will use a combination of PlanetLab and ProtoGENI resources to deploy and evaluate our sample software package. |
| 8 | Internet traffic is increasing at a tremendous rate. Recent reports suggest that the total amount of traffic might grow 5X by 2013. This is expected to put tremendous strain on installed network capacity. If left unaddressed, this issue can severely impact user experience, particularly in accessing multimedia content. Unfortunately, the obvious solution of upgrading link speeds is too expensive and cannot keep up with the rapid traffic growth. |
| 9 | We propose universal redundancy elimination (RE) to improve network efficiency and support robust user experience. In our RE framework, network elements keep track of recently forwarded packets in a local store, and strip redundant content from packets on the fly by comparing against the recently forwarded packets. The downstream network elements reconstruct full packets by substituting content from their store. Our approach expands the scope of existing duplicate suppression techniques (for example, Web caches) to the entire Internet as well as to all applications, including hitherto unforeseen ones. |
| 10 | |
| 11 | We demonstrate the benefits of redundancy elimination using a GENI-based experiment. We emulate a popular on-demand video service and show how our framework allows both the service and the network capacities to scale; note that such services are predicted to be predominant sources of traffic in the future. Our GENI slice spans multiple sites and our experiment composes several different GENI software and hardware resources. We also leverage the flexibility that GENI provides to demonstrate the benefits of modifying other aspects of the Internet, e.g., Internet routing, based on traffic redundancy information. |
| 12 | |
| 13 | === Resilient Routing in the Pathlet Architecture === |
| 14 | |
| 15 | Brighten Godfrey, ''University of Illinois'' |
| 16 | |
| 17 | Many of the key shortcomings in the Internet---including unreliability, inefficiency, and security against traffic attraction attacks---can be traced to inflexible routing decisions that are fixed within the network. The Internet offers only a single path to each destination, and this path may be broken, congested, or insecure. An alternate approach is to decouple routing decisions from the network, allowing devices at the edge, such as source end-hosts or edge routers, to select paths on a per-packet basis informed by observed performance. |
| 18 | |
| 19 | This project is developing and experimenting with pathlet routing, a highly flexible routing architecture that enables policy-compliant, scalable source-controlled routing. Specifically, we are studying how edge devices can effectively use multipath routing flexibility in the face of network dynamics via end-to-end performance observations. The project utilizes GENI's ProtoGENI and OpenFlow resources, whose deep programmability is essential for performance-sensitive measurements of the system, to enable novel experiments within the network. In our demo, we show how a streaming real-time media application can use the pathlet substrate's flexibility to weather "storms" on the network. |
| 20 | |
| 21 | === !NetServ === |
| 22 | |
| 23 | Jae Woo Lee, ''Columbia University'' |
| 24 | |
| 25 | We present !NetServ, a framework for deploying in-network services in the next generation Internet. Traditionally Internet nodes fall into one of two categories. Routers in the network core provide packet processing – forwarding, monitoring, and manipulating packets – but they do not normally provide addressable services. Servers at the network edge provide addressable services at the application layer, but they do not perform network-level services. !NetServ blurs the distinction between routers and servers by providing a common platform for both types of network services. Our vision is to provide a common API, virtualized execution environment, and signaling protocol. Network services implemented as !NetServ modules are freely installed, removed, and migrated among Internet nodes of all kinds – from backbone routers to set-top boxes. |
| 26 | |
| 27 | GENI and !NetServ share a mutually beneficial relationship. GENI makes at-scale experiments of !NetServ possible. !NetServ potentially provides an alternative method for researchers to interact with GENI nodes, allowing rapid and convenient creation of experiments. We demonstrate two network services implemented as !NetServ modules at GEC9. ActiveCDN is a dynamic content distribution network (CDN) service. Unlike traditional CDN, ActiveCDN can incorporate content processing logic specific to a content provider. SIP Remote Agent shows how a Voice-over-IP (VoIP) service provider can offload server processing to routers at the network edge. The module can respond to NAT keep-alive messages or throttle incoming traffic during a distributed denial of service (DDoS) attack. |
23 | | Internet traffic is increasing at a tremendous rate. Recent reports suggest that the total amount of traffic might grow 5X by 2013. This is expected to put tremendous strain on installed network capacity. If left unaddressed, this issue can severely impact user experience, particularly in accessing multimedia content. Unfortunately, the obvious solution of upgrading link speeds is too expensive and cannot keep up with the rapid traffic growth. |
24 | | We propose universal redundancy elimination (RE) to improve network efficiency and support robust user experience. In our RE framework, network elements keep track of recently forwarded packets in a local store, and strip redundant content from packets on the fly by comparing against the recently forwarded packets. The downstream network elements reconstruct full packets by substituting content from their store. Our approach expands the scope of existing duplicate suppression techniques (for example, Web caches) to the entire Internet as well as to all applications, including hitherto unforeseen ones. |
| 42 | Distributed applications have become a core component of the Internet's infrastructure. However, many undergraduate curriculums do not offer courses that focus on the design and implementation of distributed systems. The courses that are offered often focus on the theoretical aspects of system design, but fail to provide students with the opportunity to develop and evaluate distributed applications in real-world environments, leaving students unprepared for graduate study or careers in industry. Historically, one main reason for this lack of preparation is a lack of computing infrastructure. Moving forward, the availability of GENI resources will address this limitation, making it possible to perform large-scale experimentation even at small colleges. |
31 | | Jae Woo Lee, ''Columbia University'' |
32 | | |
33 | | We present !NetServ, a framework for deploying in-network services in the next generation Internet. Traditionally Internet nodes fall into one of two categories. Routers in the network core provide packet processing – forwarding, monitoring, and manipulating packets – but they do not normally provide addressable services. Servers at the network edge provide addressable services at the application layer, but they do not perform network-level services. !NetServ blurs the distinction between routers and servers by providing a common platform for both types of network services. Our vision is to provide a common API, virtualized execution environment, and signaling protocol. Network services implemented as !NetServ modules are freely installed, removed, and migrated among Internet nodes of all kinds – from backbone routers to set-top boxes. |
34 | | |
35 | | GENI and !NetServ share a mutually beneficial relationship. GENI makes at-scale experiments of !NetServ possible. !NetServ potentially provides an alternative method for researchers to interact with GENI nodes, allowing rapid and convenient creation of experiments. We demonstrate two network services implemented as !NetServ modules at GEC9. ActiveCDN is a dynamic content distribution network (CDN) service. Unlike traditional CDN, ActiveCDN can incorporate content processing logic specific to a content provider. SIP Remote Agent shows how a Voice-over-IP (VoIP) service provider can offload server processing to routers at the network edge. The module can respond to NAT keep-alive messages or throttle incoming traffic during a distributed denial of service (DDoS) attack. |
36 | | |
37 | | === Resilient Routing in the Pathlet Architecture === |
38 | | |
39 | | Brighten Godfrey, ''University of Illinois'' |
40 | | |
41 | | Many of the key shortcomings in the Internet---including unreliability, inefficiency, and security against traffic attraction attacks---can be traced to inflexible routing decisions that are fixed within the network. The Internet offers only a single path to each destination, and this path may be broken, congested, or insecure. An alternate approach is to decouple routing decisions from the network, allowing devices at the edge, such as source end-hosts or edge routers, to select paths on a per-packet basis informed by observed performance. |
42 | | |
43 | | This project is developing and experimenting with pathlet routing, a highly flexible routing architecture that enables policy-compliant, scalable source-controlled routing. Specifically, we are studying how edge devices can effectively use multipath routing flexibility in the face of network dynamics via end-to-end performance observations. The project utilizes GENI's ProtoGENI and OpenFlow resources, whose deep programmability is essential for performance-sensitive measurements of the system, to enable novel experiments within the network. In our demo, we show how a streaming real-time media application can use the pathlet substrate's flexibility to weather "storms" on the network. |
44 | | |
45 | | === Can I use all the diverse wireless capacity around me? === |
46 | | |
47 | | KK Yap, ''Stanford University'' |
48 | | |
49 | | There is a common perception that wireless capacity is scarce and in short-supply. This is not true. Yet we are surrounded by abundant capacity that is off-limits to us. A cell phone can typically "see" 5-6 service providers, and a laptop can often see 10 or more WiFi networks. But because of long-term contracts, and WPA passwords, most wireless networks are not available for us to use. In my research, I am trying to change that, by allowing users to use any, or even many, wireless networks around them. To start with, I have built a platform to try out many techniques, such as fast, seamless handoff between WiFi and WiMAX networks. I discovered that the GENI testbed is a perfect place for me to try out my ideas, in a real network with real users and real applications. In this demo I will show you an experiment I have created on a GENI testbed at Stanford. |
| 50 | ---- |
| 60 | |
| 61 | === Can I use all the diverse wireless capacity around me? === |
| 62 | |
| 63 | KK Yap, ''Stanford University'' |
| 64 | |
| 65 | There is a common perception that wireless capacity is scarce and in short-supply. This is not true. Yet we are surrounded by abundant capacity that is off-limits to us. A cell phone can typically "see" 5-6 service providers, and a laptop can often see 10 or more !WiFi networks. But because of long-term contracts, and WPA passwords, most wireless networks are not available for us to use. In my research, I am trying to change that, by allowing users to use any, or even many, wireless networks around them. To start with, I have built a platform to try out many techniques, such as fast, seamless handoff between !WiFi and WiMAX networks. I discovered that the GENI testbed is a perfect place for me to try out my ideas, in a real network with real users and real applications. In this demo I will show you an experiment I have created on a GENI testbed at Stanford. |
| 66 | |
| 67 | |
| 68 | ---- |
| 69 | |
| 70 | === !NowCasting: UMass/CASA Weather Radar Demonstration === |
| 71 | |
| 72 | Michael Zink, David Irwin, ''University of Massachusetts, Amherst'' |
| 73 | |
| 74 | The foundation of better weather forecasting is better data. Scientists in CASA, an NSF Engineering Research Center, are studying experimental radar systems that comprise dense networks of small, controllable radars. These networks supplement and enhance NEXRAD by accurately sensing conditions close to ground where inclement weather often occurs. As a driving example, we show data from CASA's off-the-grid student testbed in Mayaguez, Puerto Rico. Last July, the testbed successfully detected the severe windstorms that delayed the Central American Games earlier than otherwise possible, which also enabled earlier warnings. |
| 75 | |
| 76 | As a result of their accuracy, these systems produce vast amounts of streaming data from a multitude of geographically disparate sites. To be useful at scale, especially in time-critical situations, this data must quickly flow to processing centers that merge it to execute complex forecasting algorithms that predict the movements of weather patterns in real-time. Since inclement weather is rare, maintaining dedicated network/computing resources is a significant barrier to deployment at scale. This demonstration highlights an array of GENI technologies to remove this barrier, by experimenting with the execution of radar workflows and forecasting algorithms, developed by CASA scientists, on GENI and cloud networks that also include computing and sensing resources reserved on-demand. |
| 77 | |
| 78 | |
69 | | === !NowCasting: UMass/CASA Weather Radar Demonstration === |
70 | | |
71 | | Michael Zink, David Irwin, ''University of Massachusetts, Amherst'' |
72 | | |
73 | | The foundation of better weather forecasting is better data. Scientists in CASA, an NSF Engineering Research Center, are studying experimental radar systems that comprise dense networks of small, controllable radars. These networks supplement and enhance NEXRAD by accurately sensing conditions close to ground where inclement weather often occurs. As a driving example, we show data from CASA's off-the-grid student testbed in Mayaguez, Puerto Rico. Last July, the testbed successfully detected the severe windstorms that delayed the Central American Games earlier than otherwise possible, which also enabled earlier warnings. |
74 | | |
75 | | As a result of their accuracy, these systems produce vast amounts of streaming data from a multitude of geographically disparate sites. To be useful at scale, especially in time-critical situations, this data must quickly flow to processing centers that merge it to execute complex forecasting algorithms that predict the movements of weather patterns in real-time. Since inclement weather is rare, maintaining dedicated network/computing resources is a significant barrier to deployment at scale. This demonstration highlights an array of GENI technologies to remove this barrier, by experimenting with the execution of radar workflows and forecasting algorithms, developed by CASA scientists, on GENI and cloud networks that also include computing and sensing resources reserved on-demand. |