Abstract

Information-Centric Networking (ICN) is a paradigm shift from host-to-host Internet Protocol (IP)-based communication to content-based communication. In ICN, the content-retrieval process employs names that are given through different naming schemes such as hierarchical, flat, attribute, and hybrid. Among different ICN architectures, Named-Data Networking (NDN) has gained much interest in the research community and is actively being explored for the Internet of Things (IoT) and sensor networks, and follows a hierarchical naming format. NDN protocol follows a pull-based communication model where the content consumer gets content irrespective of the location of the content provider. The content provider in NDN and sensor networks can be considered to be a distributed database that monitors or controls the environment and caches the sensed data or controls information into their memory. The proposed Name-INtegrated Query (NINQ) framework for NDN-based IoT provides a flexible, expressive, and secure query mechanism that supports content retrieval as well as control and configuration command exchange among various nodes in a smart building. Different use cases are presented in this paper that expand on the behavior of proposed query framework in different scenarios. Simulation results of data collection and exchange of control commands show that proposed query framework significantly improves Interest Satisfaction Rate (ISR), Command Satisfaction Rate (CSR), energy efficiency, and average delay. Moreover, it is evident from the simulation results that proposed query framework significantly reduces the number of transmissions in the network in both data collection and exchange of control command scenarios, which improves the network performance.

Highlights

  • In traditional Internet architecture, communication between a client and a server occurs once a stable connection comprising two client-side steps has been established

  • We propose a name-based query framework that uses Named-Data Networking (NDN) as the network layer protocol to resolve the challenges of efficient heterogenous data extraction from different Internet of Things (IoT) devices in a smart building, of providing a reliable mechanism for the exchange of action-based control commands among different nodes, and of securing the communication flow between devices

  • We find that the Name-INtegrated Query (NINQ) approach achieves significantly better Interest Satisfaction Rate (ISR) in comparison to the hierarchical and flat-based hybrid naming (HFHN) and ISI schemes

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Summary

Introduction

In traditional Internet architecture, communication between a client and a server occurs once a stable connection comprising two client-side steps has been established. The NINQ framework provides a hybrid naming scheme for NDN that incorporate the hierarchical name components, hash-based flat part, and flexible, expressive, and secure query part to gather the heterogeneous data from the IoT devices. The IoT devices are still using conventional host-centric IP-based Internet architecture which is not suitable for them [13] because they are often resource-constrained in terms of computation, communication, and storage, or are deployed in inauspicious environments, sometimes buried under the ground or underwater, with intermittent connectivity that makes it harder to sustain a stable connection To solve such issues in the current IoT era, NDN has appeared as a promising solution.

Related Work
Motivation: A Smart Building Use Case
Name Components
Flat Component
Query Component
Command Component
Communication Scenarios
Simple Pull
Advantages of the NINQ Framework
Simulation Environment
Interest Satisfaction Rate
Command Satisfaction Rate
Number of Packets Processed
Energy Consumption
Average Delay
Future Directions
NINQ Testbed Implementation
Multiple Query Execution
Evaluation and Time Complexity
Augmented Reality and Edge Support
NINQ-Lite for Wireless Sensor Networks
Software-Defined Networking Interoperability
Efficient Caching
DDOS Attack Due to Unsolicited Data
Conclusions

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