A Modeling Framework for Gossip-based Information Spread

Bakhshi, Rena; Gavidia, Daniela; Fokkink, Wan; Steen, Maarten van

doi:10.1109/qest.2011.39

Cited by 6 publications

(11 citation statements)

References 25 publications

(38 reference statements)

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“…The model is derived under the assumption of lossless communication, where nodes exhibit homogeneous and uniform behavior over the network. In case the underlying system layers do not provide lossless communication, the nodes do not exhibit uniform behavior and the gossiping model has to be calibrated with experimental results [10]. Model calibration integrally captures the effects of communication aspects and their interaction with the gossiping protocol.…”

Section: Related Workmentioning

confidence: 99%

“…The cache update process is deterministic, but dependent on the data item versions present in the cache. A stochastic abstraction describing cache content from the perspective of an individual data item cannot be obtained easily [10]. Instead, we propose an approach that first models item dissemination without considering suppression of data items by newer versions and incorporate this effect later on when we integrate the dissemination of individual items (Section 6.3).…”

Section: Propositionmentioning

confidence: 99%

“…DSE requires a fast and adequately accurate method to evaluate the network QoS for specific configuration parameters. A lot of modeling efforts in recent years have been focused on the evaluation of individual system aspects: radio [5,6], data link [7,8], gossiping [9,10], hardware platform [11], and so forth. In this paper, we develop an approach that combines the individual aspect models into an integral system-level model (Figure 1a).…”

Section: Introductionmentioning

confidence: 99%

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Fast-performance simulation for Gossip-based Wireless Sensor Networks

et al. 2014

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Gossip-based Wireless Sensor Networks (GWSN) are complex systems of inherently random nature. Planning and designing GWSN requires a fast and adequately accurate mechanism to estimate system performance. As a first contribution, we propose a performance analysis technique that simulates the gossip-based propagation of each single piece of data in isolation. This technique applies to GWSN in which the dissemination of data from a specific sensor does not depend on dissemination of data generated by other sensors. We model the dissemination of a piece of data with a Stochastic-Variable Graph Model (SVGM). SVGM is a weighted graph abstraction in which the edges represent stochastic variables that model propagation delays between neighboring nodes. Latency and reliability performance properties are obtained efficiently through a stochastic shortest path analysis on the SVGM model using Monte Carlo (MC) simulation. The method is accurate and fast, applicable for both partial and complete system analysis. It outperforms traditional discreteevent simulation. As a second contribution, we propose a centrality-based stratification method that combines structural network analysis and MC partial simulation, to further increase efficiency of the system-level analysis while maintaining adequate accuracy. We analyzed the proposed performance evaluation techniques through an extensive set of experiments, using a real deployment and simulations at different levels of abstraction.

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Section: Related Workmentioning

confidence: 99%

Section: Propositionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Fast-performance simulation for Gossip-based Wireless Sensor Networks

et al. 2014

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“…It is therefore not surprising that the dominant technique for performance evaluation for GWSN is simulation. Most alternative methods either cannot cope with system complexity (typically analytic models [2], [3]) or bring a lot of computation overhead (model-checking approaches [20], [12], [14] [32]) to the WSN specifics. The speed of such an approach is acceptable for analyzing system behavior and gaining insight in the interaction between system parts, but it is not sufficiently fast for SPO.…”

Section: Related Workmentioning

confidence: 99%

“…GWSNs are complex systems of inherently random nature [3], [4]. Gossip protocols rely on a probabilistic mechanism for disseminating data throughout the network.…”

Section: Introductionmentioning

confidence: 99%

Fast sink placement for Gossip-based Wireless Sensor Networks

Blagojević

Geilen

Basten³

et al. 2012

2012 IEEE 31st International Performance Computing and Communications Conference (IPCCC)

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Abstract-In this paper we address the problem of sink placement for Gossip-based Wireless Sensor Networks (GWSN). Sink placement plays an important role in planning and deployment of sensor networks. It is an efficient means to improve performance and achieve design objectives. Sink deployment requires an optimization strategy to search a space of possible placement options, and a performance evaluation method to assess the quality of different sink placements. The stochastic nature of the gossip protocol makes this task challenging for GWSN. Simulation is the most common way to accurately evaluate gossiping performance; however, the time required to obtain statistically significant results is considerable and limits the scalability of the sink deployment process. We use a fast and accurate performance evaluation technique, which exploits specifics of the sink placement problem and significantly reduces evaluation time. In order to further improve the speed of the sink placement procedure we propose a greedy simulated annealing search heuristic that converges fast to a near-optimal placement. We have performed an extensive set of experiments to evaluate the performance of the proposed sink placement framework.

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Refined Mean Field Analysis: The Gossip Shuffle Protocol Revisited

Gast¹,

Latella²,

Massink³

2020

Lecture Notes in Computer Science

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Gossip protocols form the basis of many smart collective adaptive systems. They are a class of fully decentralised, simple but robust protocols for the distribution of information throughout large scale networks with hundreds or thousands of nodes. Mean field analysis methods have made it possible to approximate and analyse performance aspects of such large scale protocols in an efficient way that is independent of the number of nodes in the network. Taking the gossip shuffle protocol as a benchmark, we evaluate a recently developed refined mean field approach. We illustrate the gain in accuracy this can provide for the analysis of medium size models analysing two key performance measures: replication and coverage. We also show that refined mean field analysis requires special attention to correctly capture the coordination aspects of the gossip shuffle protocol. Keywords: Mean field • Collective adaptive systems • Discrete time Markov chains • Gossip protocols • Self-organisation This research has been partially supported by the Italian MIUR project PRIN 2017FTXR7S "IT-MaTTerS" (Methods and Tools for Trustworthy Smart Systems).

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A Modeling Framework for Gossip-based Information Spread

Cited by 6 publications

References 25 publications

Fast-performance simulation for Gossip-based Wireless Sensor Networks

Fast-performance simulation for Gossip-based Wireless Sensor Networks

Fast sink placement for Gossip-based Wireless Sensor Networks

Refined Mean Field Analysis: The Gossip Shuffle Protocol Revisited

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