UUSee: Large-Scale Operational On-Demand Streaming with Random Network Coding

Liu, Zimu; Wu, Chuan; Li, Baochun; Zhao, Shuqiao

doi:10.1109/infcom.2010.5462030

Cited by 152 publications

(135 citation statements)

References 16 publications

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“…However, if peers require a large file, they have to download very small pieces of a file several times and it increases overheads. In [7] the authors present a new protocol with network coding for segment scheduling in the UUSee for P2P-VoD systems. In terms of reducing server bandwidth usage it proves that network coding combined with segment scheduling strategy can improve performance.…”

Section: Related Workmentioning

confidence: 99%

A new mechanism to improve video streaming in P2P networks using helper nodes

Kargar¹,

Ghasemi²

2017

Turk J Elec Eng & Comp Sci

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Peer-to-peer video on demand (P2P-VoD) is a solution to provide video service to a large number of users on the Internet. Due to the upload bandwidth bottleneck of VoD servers, the streaming capacity in the P2P-VoD system is limited. This paper proposes a new mechanism to improve the video streaming in P2P networks by using the idle peers upload bandwidth and storage, which are called helpers. The proposed method uses an XOR mechanism in the VoD server to encode chunks and reduce bandwidth use. The helpers receive encoded chunks from the VoD server and save them in their storage spaces and cooperate in sharing these chunks with the other peers. Simulation results using OMNET++ are provided to show the efficiency of the proposed mechanism in terms of the required upload capacity requirement of the server and deploying the storage and bandwidth of helpers. The results of simulation show that the upload bandwidth usage of the server has been reduced. On the other hand, the proposed method increases the memory usage of helpers.

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Section: Related Workmentioning

confidence: 99%

A new mechanism to improve video streaming in P2P networks using helper nodes

Kargar¹,

Ghasemi²

2017

Turk J Elec Eng & Comp Sci

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“…After the introduction of random linear NC (RLNC) [11], the concept of NC has been widely applied in practical content distribution systems [12]. With RLNC, the to-be-disseminated content is divided into k original blocks of the same size.…”

Section: Related Workmentioning

confidence: 99%

Optimal rate allocation and scheduling in cooperative streaming

Zakerinasab

Wang

2014

39th Annual IEEE Conference on Local Computer Networks

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Abstract-The demand for multimedia streaming, especially from mobile devices, is growing rapidly, mostly due to the increasing deployment of broadband cellular technologies and the growing computing power on modern mobile devices. While cellular carriers strive to meet the demand, mobile devices are challenged by the variable transmission rate in wireless channels and limited battery capacity. To this end, we propose an energyefficient cooperative streaming system. In the proposed system, mobile devices collectively stream a copy of the multimedia content from the source over cellular links. The devices form a cooperative group and share received content with each other over short-range links. The design of the system is guided by the optimal rate allocation and scheduling (RAS) algorithm that determines the amount of data and the data to be transmitted on each link. The actual data scheduled to be transmitted on each link is delivered in coded form for efficient loss detection and recovery. Overall, the system minimizes both the streaming traffic in the cellular network and the energy consumed by streaming applications on mobile devices. Our experimental results show that significant energy saving is achieved in the proposed system. Moreover, our RAS algorithm prolongs the streaming session for the entire cooperative group. I. INTRODUCTIONThe demand for high quality video streaming on mobile devices grows along with the deployment of 3G/4G technologies and the increasing computing power on mobile devices. Currently, video streaming traffic accounts for more than 53% of the cellular Internet traffic, and is expected to reach 66% in the next four years [1]. While cellular carriers strive to meet the expected growth, mobile devices are also challenged by the variable transmission rate in wireless channels and limited battery capacity. Reducing the loss rate and bandwidth fluctuation is a straightforward, but not easy, way to improve cellular networks for multimedia streaming. The alternative approach is to encourage cooperation among mobile devices by utilizing short-range links such as WiFi and Bluetooth [2]. The use of short-range links in addition to cellular links not only alleviates the workload in cellular networks, but also increases the overall link capacity around individual mobile devices.The cooperative system is formed by groups of mobile devices that are within the same WiFi network and are interested in viewing the same video at the same time. As shown in Fig. 1, there are groups of mobile devices, where within each group the mobile devices communicate over short-range (WiFi, in this case) links and form a swarming session to exchange multimedia content received from the cellular network [2]. In this cooperative streaming system, mobile devices of the same group contact the source regarding the video of their interest. The video source prepares and serves the multimedia content over cellular links. Upon receiving the multimedia content, a mobile device broadcasts the content in the local shortrange n...

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“…This reduces the overhead to the size of the seed, but also reduces the number of unique coding vectors to the size of the seed. This approach is not suitable for recoding [12]. The reason is that during recoding the coding vector is not drawn randomly but instead computed asg =ĝ × h where h is random.…”

Section: Coding Vector Representationmentioning

confidence: 99%

On Code Parameters and Coding Vector Representation for Practical RLNC

Heide

Pedersen

Fitzek

et al. 2011

2011 IEEE International Conference on Communications (ICC)

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Abstract-Random Linear Network Coding (RLNC) provides a theoretically efficient method for coding. The drawbacks associated with it are the complexity of the decoding and the overhead resulting from the encoding vector. Increasing the field size and generation size presents a fundamental trade-off between packetbased throughput and operational overhead. On the one hand, decreasing the probability of transmitting redundant packets is beneficial for throughput and, consequently, reduces transmission energy. On the other hand, the decoding complexity and amount of header overhead increase with field size and generation length, leading to higher energy consumption. Therefore, the optimal trade-off is system and topology dependent, as it depends on the cost in energy of performing coding operations versus transmitting data. We show that moderate field sizes are the correct choice when trade-offs are considered. The results show that sparse binary codes perform the best, unless the generation size is very low.

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UUSee: Large-Scale Operational On-Demand Streaming with Random Network Coding

Cited by 152 publications

References 16 publications

A new mechanism to improve video streaming in P2P networks using helper nodes

A new mechanism to improve video streaming in P2P networks using helper nodes

Optimal rate allocation and scheduling in cooperative streaming

On Code Parameters and Coding Vector Representation for Practical RLNC

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