On coding for real-time streaming under packet erasures

Leong, Derek; Qureshi, Asma; Ho, Tracey

doi:10.1109/isit.2013.6620379

Cited by 46 publications

(29 citation statements)

References 6 publications

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“…Extending this phenomenon to a general case, the real-time streams are classified into Symmetric Real-time streams and Asymmetric Real-time streams. Fig.1 [3]. If the delay deadline is a multiple of the message creation period, the RST capacity is equal to the Shannon capacity.…”

Section: Definitions Of Symmetric Real-time Stream Andmentioning

confidence: 99%

“…The performance of Symmetric Time-invariant Intra-session Code (STIC) from [3] is also compared in Fig.6. Since STIC is proposed for real-time stream with uniform messages, for STIC we set s h = s l .…”

Section: Performance Evaluationmentioning

confidence: 99%

“…So far only a few works tried to find the accurate RST capacity and design corresponding codes. Leong and Ho [3] [4] presented a symmetric intra-session code for real-time streams. Another coding scheme presented by Martinian and Badr in [5] [6] can adjust the delay deadline according to the channel quality.…”

Section: Introductionmentioning

confidence: 99%

“…Prioritized real-time streaming system for (c, d) =(3,6). The source creates one high priority message followed by c − 1 low priority messages periodically.…”

mentioning

confidence: 99%

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Priority-Based Real-Time Stream Coding under Burst Erasures

Wei¹,

Mao²,

Leng³

et al. 2014

2015 IEEE Global Communications Conference (GLOBECOM)

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The real-time streams play an increasingly important role in both traditional and emerging networks. Whereas, transmitting such streams requires vast channel resources, posing a huge challenge to the networks. Motivated by this problem, this paper considers a real-time stream system, where realtime messages with different importance should be transmitted through a burst erasure channel, and be decoded by the receiver within a fixed delay. We introduce the concepts of Symmetric Real-time (SR) stream and Asymmetric Real-time (AR) stream according to the stream characteristics. Different from the classical Shannon capacity, the channel transmission capacities are derived for SR and AR streams respectively, which can be used to guide the design of efficient real-time stream coding approaches. The capacity for SR streams is shown asymptotically achievable with a Proportional Time-invariant Intra-session Code (PTIC). Moreover, a Maximum Time-invariant Intra-session Code (MTIC) is presented for AR streams, which can also asymptotically achieve the capacity. Finally, the performances of PTIC and MTIC are verified by simulation experiments.

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Section: Definitions Of Symmetric Real-time Stream Andmentioning

confidence: 99%

Section: Performance Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Prioritized real-time streaming system for (c, d) =(3,6). The source creates one high priority message followed by c − 1 low priority messages periodically.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Priority-Based Real-Time Stream Coding under Burst Erasures

Wei¹,

Mao²,

Leng³

et al. 2014

2015 IEEE Global Communications Conference (GLOBECOM)

Self Cite

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show abstract

“…In addition to distributed storage, the symmetric allocation algorithms can also be applied to the problem of code design for real-time streaming [7], [8], where messages arrive sequentially at the source and are encoded for transmission over a packet erasure channel to a sink, which needs to decode the messages sequentially within a specified delay. In various network scenarios, packet delay exhibits variation, causing the probability of packet reception to increase with delay.…”

Section: Algorithm Application: Symmetric Time-invariant Intrasessmentioning

confidence: 99%

Distributed storage allocation for heterogeneous systems

Zhao

Leong

et al. 2013

2013 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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We consider a distributed storage system where the storage nodes have heterogeneous access probabilities. The problem is to allocate a given storage budget across the nodes so as to store a unit-size data object with maximum reliability. We propose efficient algorithms for optimizing over several classes of allocations. In the basic one-level symmetric allocation, the storage budget is spread evenly over an appropriately chosen subset of nodes. In the multi k-level symmetric allocation, the budget is divided into k parts, each spread evenly over a different subset of nodes, such that the amount allocated to each node in the higher levels is multiple times that of the last level. These allocations are simpler and are shown to outperform existing methods in numerical experiments. We also describe an application of the symmetric allocations to the design of streaming codes.

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Fed-DIC: Diagonally Interleaved Coding in a Federated Cloud Environment

Tzouros¹,

Kalogeraki²

2020

Distributed Applications and Interoperable Systems

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Coping with failures in modern distributed storage systems that handle massive volumes of heterogeneous and potentially rapidly changing data, has become a very important challenge. A common practice is to utilize fault tolerance methods like Replication and Erasure Coding for maximizing data availability. However, while erasure codes provide better fault tolerance compared to replication with a more affordable storage overhead, they frequently suffer from high reconstruction cost as they require to access all available nodes when a data block needs to be repaired, and also can repair up to a limited number of unavailable data blocks, depending on the number of the code's parity block capabilities. Furthermore, storing and placing the encoded data in the federated storage system also remains a challenge. In this paper we present Fed-DIC, a framework which combines Diagonally Interleaved Coding on client devices at the edge of the network with organized storage of encoded data in a federated cloud system comprised of multiple independent storage clusters. The erasure coding operations are performed on client devices at the edge while they interact with the federated cloud to store the encoded data. We describe how our solution integrates the functionality of federated clouds alongside erasure coding implemented on edge devices for maximizing data availability and we evaluate the working and benefits of our approach in terms of read access cost, data availability, storage overhead, load balancing and network bandwidth rate compared to popular Replication and Erasure Coding schemes.

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On coding for real-time streaming under packet erasures

Cited by 46 publications

References 6 publications

Priority-Based Real-Time Stream Coding under Burst Erasures

Priority-Based Real-Time Stream Coding under Burst Erasures

Distributed storage allocation for heterogeneous systems

Fed-DIC: Diagonally Interleaved Coding in a Federated Cloud Environment

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