IoT Data Discovery: Routing Table and Summarization Techniques

TL;DR

This paper addresses IoT data discovery in large networks by proposing space-efficient routing table designs and summarization algorithms, significantly reducing routing table size while maintaining lookup efficiency and outperforming existing methods.

Contribution

It introduces novel summarization algorithms and routing table designs tailored for IoT data discovery, balancing compression and accuracy in unstructured networks.

Findings

Routing table size reduced by 20-30 times with minimal latency increase

Outperforms DHT-based approaches by 2-6 times in latency and traffic

Effective summarization balances compression and misleading routing risk

Abstract

In this paper, we consider the IoT data discovery problem in very large and growing scale networks. Through analysis, examples, and experimental studies, we show the importance of peer-to-peer, unstructured routing for IoT data discovery and point out the space efficiency issue that has been overlooked in keyword-based routing algorithms in unstructured networks. Specifically, as the first in the field, this paper investigates routing table designs and various compression techniques to support effective and space-efficient IoT data discovery routing. Novel summarization algorithms, including alphabetical, hash, and meaning-based summarization and their corresponding coding schemes, are proposed. We also consider routing table design to support summarization without degrading lookup efficiency for discovery query routing. The issue of potentially misleading routing due to summarization is also investigated. Subsequently, we analyze the strategy of when to summarize to balance the tradeoff between the routing table compression rate and the chance of causing misleading routing. For the experimental study, we have collected 100K IoT data streams from various IoT databases as the input dataset. Experimental results show that our summarization solution can reduce the routing table size by 20 to 30 folds with a 2-5% increase in latency compared with similar peer-to-peer discovery routing algorithms without summarization. Also, our approach outperforms DHT-based approaches by 2 to 6 folds in terms of latency and traffic.