MOLStream: A Modular Rapid Development and Evaluation Framework for Live P2P Streaming

Friedman, Roy; Libov, Alexander; Vigfússon, Ýmir

doi:10.1109/icdcs.2014.36

Cited by 2 publications

(3 citation statements)

References 26 publications

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“…Within a single network node, modules may interact with one another through method invocation having a fixed interface. Different implementations of modules can also be mixed and matched, similarly to our earlier work in this area [28].…”

Section: A Ingredients Of P2p Live Streamingmentioning

confidence: 89%

“…Our ingredient abstraction is inspired by these works, while cast in the P2P live streaming environment. MOL-STREAM is our previous system primarily designed for the rapid deployment and evaluating of P2P live streaming protocols, which also sought to modularize these protocols [28]. While we leverage the system for deployment, the built-in MOLSTREAM modules are coarse-grained and mostly lack intercompatibility, whereas the finer-grained ingredients we proposed in STREAMAID are more atomic, intercompatible and shed light on the design decisions involved.…”

Section: Related Workmentioning

confidence: 97%

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Distilling the ingredients of P2P live streaming systems

Friedman

Libov

Vigfussony

2015

2015 IEEE International Conference on Peer-to-Peer Computing (P2P)

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Peer-to-peer live streaming systems involve complex engineering and are difficult to test and to deploy. To cut through the complexity, we advocate such systems be designed by composing ingredients: a novel abstraction denoting the smallest interoperable units of code that each express a single design choice. We present a system, STREAMAID, that provides tools for designing protocols in terms of ingredients, systematically testing the impact of every design decision in a simulator, and deploying them in a wide-area testbed such as PlanetLab for evaluation. We show how to decompose popular P2P live streaming systems, such as CoolStreaming, BitTorrent Live and others, into ingredients and how STREAMAID can help optimize and adapt these protocols. By experimenting with the essential building blocks of which P2P live streaming protocols are comprised, we gain a unique vantage point of their relative quality, their bottlenecks and their potential for future improvement.

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Section: A Ingredients Of P2p Live Streamingmentioning

confidence: 89%

Section: Related Workmentioning

confidence: 97%

Distilling the ingredients of P2P live streaming systems

Friedman

Libov

Vigfussony

2015

2015 IEEE International Conference on Peer-to-Peer Computing (P2P)

Self Cite

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“…SEINE is also related to a significant body of work in the area of languages and tools for building and testing dependable distributed systems. In particular, practical frameworks such as Mace [16], Splay [19], and MOLStream [9] provide language support that enables developers to work on the different concerns that comprise a distributed system in isolation, thereby simplifying the overall process. Although performance and dependability concerns are also taken into account by these frameworks (e.g., fault handling support, performance and correctness analysis), there is no explicit guidance for addressing selfishness-related issues.…”

Section: Related Workmentioning

confidence: 99%

Analysing Selfishness Flooding with SEINE

Cota

Mokhtar

Gianini

et al. 2017

2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)

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Selfishness is one of the key problems that confronts developers of cooperative distributed systems (e.g., filesharing networks, voluntary computing). It has the potential to severely degrade system performance and to lead to instability and failures. Current techniques for understanding the impact of selfish behaviours and designing effective countermeasures remain manual and time-consuming, requiring multi-domain expertise. To overcome these difficulties, we propose SEINE, a simulation framework for rapid modelling and evaluation of selfish behaviours in a cooperative system. SEINE relies on a domain-specific language (SEINE-L) for specifying selfishness scenarios, and provides semi-automatic support for their implementation and study in a state-of-the-art simulator. We show in this paper that (1) SEINE-L is expressive enough to specify fifteen selfishness scenarios taken from the literature, (2) SEINE is accurate in predicting the impact of selfishness compared to real experiments, and (3) SEINE substantially reduces the development effort compared to traditional manual approaches.

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MOLStream: A Modular Rapid Development and Evaluation Framework for Live P2P Streaming

Cited by 2 publications

References 26 publications

Distilling the ingredients of P2P live streaming systems

Distilling the ingredients of P2P live streaming systems

Analysing Selfishness Flooding with SEINE

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