Flow Sampling: Network Monitoring in Large-Scale Software-Defined IoT Networks
نویسندگان
چکیده
Software-defined Internet-of-Things networking (SDIoT) greatly simplifies the network monitoring in large-scale IoT networks by per-flow sampling, wherein controller keeps track of all active flows and samples devices on each flow path to collect real-time statistics. There is a tradeoff between controller’s sampling preference balancing loads among devices. On one hand, may prefer sample some because they yield more accurate other it desirable uniformly so that their energy consumptions lifespan are balanced. This paper formulates problem SDIoT means Markov decision process devises policies strike good balance these two goals. Three classes investigated: optimal policy, state-independent policies, index (including Whittle second-order policies). The policy most desired all: 1) terms performance, an equal footing with outperforms much; 2) complexity, much simpler than comparable policy; 3) realizability, requires no prior information dynamics, hence easier implement practice.
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ژورنال
عنوان ژورنال: IEEE Transactions on Communications
سال: 2021
ISSN: ['1558-0857', '0090-6778']
DOI: https://doi.org/10.1109/tcomm.2021.3093320