| | 62 | ==== Load Balancing Approach for Adaptive Bit-Rate Streaming in Information Centric Networks ==== |
| | 63 | |
| | 64 | The Information Centric Networking (ICN) paradigm promises deconstraining the current Internet architecture by allowing clients to directly address the desired content throughout the network. For the Internet, this is an evolutionary step from the idea of a narrow-waist core that only transports requests/replies to an intelligent architecture searching for and providing content. Multi-sourcing, which is one of the core ideas of ICN, constitutes a serious challenge for prevalent Internet applications such as video streaming. In this work we show how prominent adaptive video streaming protocols can benefit from the load balancing capabilities that are native to ICN. We examine the performance of content retrieval in ICN over Ethernet in a real-world testbed showing the impact of multi-sourcing and content size variation on the content transfer times. |
| | 65 | |
| | 66 | Participants: |
| | 67 | * Divyashri Bhat, dbhat@umass.edu, University of Massachusetts |
| | 68 | * Cong Wang |
| | 69 | * Amr Rizk |
| | 70 | * Mike Zink, zink@ecs.umass.edu, University of Massachusetts |
| | 71 | |
| | 72 | ==== Efficient Caching for Dash ==== |
| | 73 | |
| | 74 | Dynamic Adaptive Streaming over HTTP (DASH) is a recent technology that delivers high quality streaming media content over the Internet using HTTP servers. A DASH server contains multiple representations for every video, with each representation varying in bitrate, resolution etc. Each of these representations are divided into smaller segments of fixed playback duration. the client downloads the individual segments during playback. The client employs an Adaptive Bitrate Algorithm (ABR) that determines the appropriate quality for the next segment based on the network conditions. |
| | 75 | The current Internet architecture utilizes in-network caching to improve content availability and performance. We identify the areas where DASH differs from other web requests, and propose an Adaptation Aware Cache (AAC) framework that optimizes serving DASH video streams by using bandwidth measurement at the cache and the knowledge of the adaptation scheme used at the client to predict the next segment request. This technique could be used to improve the cache performance by maximizing the byte-hits in cache and minimizing the unnecessary prefetches, thus improving the Quality of Experience (QoE) at the client-end. |
| | 76 | |
| | 77 | To evaluate our proposal we used GENI testbed a web-server that host multiple DASH videos with several representations. All the segment request from the client are serviced using a single machine acting as a cache. The cache measures the current bandwidth based on one of the three throughput estimations: average of all values, average of last five values, and Harmonic average of all values. |
| | 78 | |
| | 79 | Participants: |
| | 80 | * Sheyda Kiani Mehr, skkv6@mail.umkc.edu, University of Missouri-Kansas City |
| | 81 | * Parikshit Juluri |
| | 82 | * Rohit Abhishek |
| | 83 | * Deep Medhi |
| | 84 | |
| | 85 | === Network Protocols === |
| | 86 | |
| | 87 | ==== A Flexible and Lightweight BGP Route Injector to Multiple Peers ==== |
| | 88 | |
| | 89 | The demo proposes and implements a flexible and lightweight BGP injector (mBGPInjector) that can announce both offline and real-time BGP routes to multiple peers with various filtering options. mBGPInjector also supports dynamical BGP configuration changes, such as online bringing a peer down or up, applying custom filtering rules and announcing or withdrawing arbitrary BGP routes. The implemented mBGPInjector is a lightweight perl program that consists of a few functions to read, analyze and direct BGP routes to corresponding connected BGP peers in a large size of network (eBGP or iBGP). Experiments with our mBGPInjector tool satisfy the requirements we need for research and education and demonstrate effectiveness under realistic workloads. In addition, we designed and tested the tool in Global Environment for Network Innovations (GENI) environment, where researchers and educators can take advantage of shared resource request files to repeat the same experiments without involvement of ponderous settings and configurations. |
| | 90 | |
| | 91 | Participants: |
| | 92 | * Yaoqing Liu, liu@clarkson.edu, Clarkson University |
| | 93 | * Jialiang Pan |
| | 94 | |
| | 95 | ==== WiFi Multicast to Very Large Groups - Experimentation on the ORBIT Testbed ==== |
| | 96 | |
| | 97 | While WiFi has been proposed for multimedia content distribution, its lack of adequate support for multicast services hinders its ability to provide multimedia content distribution to a large number of devices. In our recent papers we proposed AMuSe, a scalable and adaptive system for WiFi multicast which is based on accurate receiver feedback and that incurs a small control overhead. Specifically, the system includes a scheme for dynamic selection of a subset of the multicast receivers as feedback nodes, which periodically send information, such as channel quality or received packet statistics, to the multicast sender.We implemented the AMuSe system in the ORBIT testbed and evaluated its performance in large groups with 150-200 receivers. We present a dynamic web-based application that demonstrates the operation of the system based on actual traces collected on the testbed in several experiments. It demonstrates the operation of AMuSe in various setting and environments. |
| | 98 | |
| | 99 | Participants: |
| | 100 | * Varun Gupta, vg2297@columbia.edu, Columbia University |
| | 101 | * Raphael Norwitz |
| | 102 | * Savvas Petridis |
| | 103 | * Craig Gutterman |
| | 104 | * Gil Zussman |
| | 105 | * Yigal Bejerano |
| | 106 | |
| | 107 | === Next Generation Applications === |
| | 108 | |
| | 109 | ==== A Cyber Physical Test Bed for Advanced Manufacturing ==== |
| | 110 | |
| | 111 | This demonstration will be a milestone in the area of Digital Manufacturing and involves showcasing a GENI based cyber physical framework for advanced manufacturing. This Next Internet based framework will enable globally distributed software and manufacturing resources to be accessed from different locations accomplish a complex set of life cycle activities including design analysis, assembly planning, and simulation. The advent of the Next Internet holds the promise of ushering in a new era in Information Centric engineering and digital manufacturing activities. The focus will be on the emerging domain of micro devices assembly, which involves the assembly of micron sized parts using automated micro assembly work cells. |
| | 112 | |
| | 113 | Participants: |
| | 114 | * J. Cecil |
| | 115 | * Yajun Lu, yajun.lu@okstate.edu, Oklahoma State University |
| | 116 | * Zak Zafar |
| | 117 | * Esma Yahia |
