By Wolfgang Effelsberg, Ralf Steinmetz, Thorsten Strufe
Peer-to-peer structures are actually general and became the focal point of realization for lots of researchers during the last decade. a few algorithms for decentralized seek, content material distribution, and media streaming were built. This publication presents basic techniques for the benchmarking of these algorithms in peer-to-peer platforms. It additionally incorporates a selection of attribute benchmarking effects. The chapters of the booklet were geared up in 3 topical sections on: basics of Benchmarking in P2P platforms; artificial Benchmarks for Peer-to-Peer structures; and alertness Benchmarks for Peer-to-Peer structures. they're preceded by means of a close advent to the subject.
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Extra info for Benchmarking Peer-to-Peer Systems: Understanding Quality of Service in Large-Scale Distributed Systems
In addition, the returned results to initiated queries should fulfill the validity criterion described above. 40 K. Saller, K. Panitzek, and M. Lehn Robustness Robustness of peer-to-peer systems is the capability of the system to handle unpredicted external events or failures like high churn, massive crashes, or attacks. Quantifying robustness is a difficult task, since different external events might have different effects on the peer-to-peer system and cannot be measured with only one metric.
Scenario 9: Increasing Network Delay. The increase in the message delay over a communication link puts stress on the peer-to-peer system as messages might arrive too late, potentially causing timeouts. • Scenario 10: Decreasing Bandwidth. In this workload scenario the bandwidth of the links between the peers is decreased. This in turn might result in messages getting dropped. 2 Synthetic Workloads A synthetic workload is specifically designed for benchmarking purposes; it does not need to share any similarity with workloads found in the real world.
In the case of peer-to-peer systems this includes churn, discovery of a service or data object and retrieval of a service or data object. A workload can be configured by its workload parameters. These describe, for example, the intensity or the operation mix of the workload. Workload factors are a subset of the workload parameters that are varied during the benchmark, typically those that have the greatest impact on the system performance. A workload can be categorized as synthetic or real-world.