Dynamic grid-based multicast group assignment in data distribution management

Boukerche, Azzedine; Roy, Amber Joyce; Thomas, Navin

doi:10.1109/disrta.2000.874063

Cited by 31 publications

(27 citation statements)

References 8 publications

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“…The three DDM methods we implement for our experiments are region-based [6,10,14,18,19], fixed grid-based [3,9,[19][20][21][22], and dynamic grid-based schemes [4,17]. To further our understanding of the potential performance gains and possible communication overhead reduction, we implement two variations of each of the grid-based DDM techniques and run various experiments to compare the effects on performance and communication overhead of those variations.…”

Section: Ddm Methodsmentioning

confidence: 99%

“…In a large-scale distributed simulation environment, where many simulated entities across many different hosts may be involved, these actions can result in an increased communication overhead across a network on the scale of O(N 2 ), where N is the number of simulated hosts [1]. The aim of Data Distribution Management (DDM) is to limit and control the volume of data exchanged during a simulation, and reduce the processing requirements of simulation hosts by relaying events and state information only to those applications that require them [2][3][4][5][6][7][8][9][10]. DDM is also…”

Section: Introductionmentioning

confidence: 99%

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Performance evaluation of Data Distribution Management strategies

Boukerche

Dzermajko

2004

Concurrency and Computation

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SUMMARYData Distribution Management (DDM) is a High Level Architecture/Run-Time Infrastructure (HLA/RTI) service that manages the distribution of state updates and interaction information in large-scale distributed simulations and limits and controls the volume of data exchanged during the simulation.In this paper, we describe a mini-RTI framework that we have developed in an effort to determine the most efficient model for applying the DDM service and the limitations of the scalability of various DDM methods. We study and compare the performance of the following five DDM strategies: two variations of the fixed-based method, two variations of the dynamics grid-based scheme and the region-based method. Due to a lack of accepted benchmarks, we also propose a variety of workloads and scenarios, which we hope will become a standards benchmark within the distributed simulation communities.

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Section: Ddm Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance evaluation of Data Distribution Management strategies

Boukerche

Dzermajko

2004

Concurrency and Computation

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“…However, the content of sensor data streams is determined by individual queries rather than channels. Although extensions have been proposed to map queries to channels [7], the resulting false positives incur prohibitively high load on the network. Content-based pub/sub systems [9] as the second category aim to establish a containment relationship between the data sources and sinks, i.e.…”

Section: Related Workmentioning

confidence: 99%

Bandwidth-Minimized Distribution of Measurements in Global Sensor Networks

Benzing

Koldehofe

Rothermel

2014

Distributed Applications and Interoperable Systems

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Abstract. Global sensor networks (GSN) allow applications to integrate huge amounts of data using real-time streams from virtually anywhere. Queries to a GSN offer many degrees of freedom, e.g. the resolution and the geographic origin of data, and scaling optimization of data streams to many applications is highly challenging. Existing solutions hence either limit the flexibility with additional constraints or ignore the characteristics of sensor streams where data points are produced synchronously.In this paper, we present a new approach to bandwidth-minimized distribution of real-time sensor streams in a GSN. Using a distributed index structure, we partition queries for bandwidth management and quickly identify overlapping queries. Based on this information, our relay strategy determines an optimized distribution structure which minimizes traffic while being adaptive to changing conditions. Simulations show that total traffic and user perceived delay can be reduced by more than 50%.

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“…The main goal of this standard was to increase interoperability and reuse of simulations. In the simulations compliant with the standard, the proximity detection is demanded to the Data Distribution Management (DDM) module [7]. The DDM is based on a publish/subscribe mechanism.…”

Section: Background and Related Workmentioning

confidence: 99%

Proximity detection in distributed simulation of wireless mobile systems

Bononi

Bracuto

D’Angelo

et al. 2006

Proceedings of the 9th ACM International Symposium on Modeling Analysis and Simulation of Wireless and Mobile Systems

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The distributed and the Grid Computing architectures for the simulation of massively populated wireless systems have recently been considered of interest, mainly for cost reasons. Solutions for generalized proximity detection for mobile objects is a relevant problem, with a big impact on the design and the implementation of parallel and distributed simulations of wireless mobile systems. In this paper, a set of solutions based on tailored data structures, new techniques and enhancements of the existing algorithms for generalized proximity detection are proposed and analyzed, to increase the efficiency of distributed simulations. The paper includes the analysis of computation complexity of the proposed solutions and the performance evaluation of a testbed distributed simulation of ad hoc network models. Recent works have shown that the performance of distributed simulation of dynamic complex systems could benefit from a runtime migration mechanism of model entities, which reduces the communication overheads. Such migration mechanisms may interfere with the generalized proximity detection implementations. The analysis performed in this paper illustrates the effects of many possible compositions of the proposed solutions, in a real testbed simulation framework.

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Dynamic grid-based multicast group assignment in data distribution management

Abstract: With the need to do increasingly complex distributed simulations, a considerable amount of effort in the Distributed

Cited by 31 publications

References 8 publications

Performance evaluation of Data Distribution Management strategies

Performance evaluation of Data Distribution Management strategies

Bandwidth-Minimized Distribution of Measurements in Global Sensor Networks

Proximity detection in distributed simulation of wireless mobile systems

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