Self-Tuning, Bandwidth-Aware Monitoring for Dynamic Data Streams
Self-Tuning, Bandwidth-Aware Monitoring for Dynamic Data Streams
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DOI：
10.1109/icde.2009.134
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发表时间：
2009-03
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通讯作者：
Navendu Jain;P. Yalagandula;M. Dahlin;Yin Zhang
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作者：
Navendu Jain;P. Yalagandula;M. Dahlin;Yin Zhang
我们提出了智能，一个自我调整，带宽感知的监测系统，最大限度地提高结果精度的连续聚合查询动态数据流。虽然现有方法在固定精度约束下使带宽成本最小化，但是它们仍然可能在业务突发期间使监视系统过载。为了促进监测系统的实际部署，SMART因此限制了过载弹性的最坏情况带宽成本。SMART的主要挑战是如何在每个节点上动态选择更新，以最大限度地提高查询精度，同时保持每个节点的监控带宽低于指定的预算。为了应对这一挑战，SMART的分层算法（1）以耳最佳方式分配带宽预算，以最大限度地提高全局精度，（2）自调整带宽设置，以提高动态工作负载下的精度。我们的SMART原型实现提供了关键的解决方案，（a）优先处理多属性查询的未决更新，（B）构建有界扇入，负载感知聚合树，以提高准确性，（c）联合收割机结合时间序列与算术过滤，以减少负载和量化结果陈旧。我们使用模拟和网络监控应用程序的评估表明，SMART招致低开销，提高精度的数量级相比，均匀的带宽分配，并执行接近最佳算法下适度的带宽预算。
We present SMART, a self-tuning, bandwidth-aware monitoring system that maximizes result precision of continuous aggregate queries over dynamic data streams. While prior approaches minimize bandwidth cost under fixed precision constraints, they may still overload a monitoring system during traffic bursts. To facilitate practical deployment of monitoring systems, SMART therefore bounds the worst-case bandwidth cost for overload resilience. The primary challenge for SMART is how to dynamically select updates at each node to maximize query precision while keeping per-node monitoring bandwidth below a specified budget. To address this challenge, SMART’s hierarchical algorithm (1) allocates bandwidth budgets in an ear-optimal manner to maximize global precision and (2) selftunes bandwidth settings to improve precision under dynamic workloads. Our prototype implementation of SMART provides key solutions to (a) prioritize pending updates for multi-attribute queries, (b) build bounded fan-in, load-aware aggregation trees to improve accuracy, and (c) combine temporal batching with arithmetic filtering to reduce load and to quantify result staleness. Our evaluation using simulations and a network monitoring application shows that SMART incurs low overheads, improves accuracy by up to an order of magnitude compared to uniform bandwidth allocation, and performs close to the optimal algorithm under modest bandwidth budgets.