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Information Centric Networking in the IoT: Experiments with NDN in the Wild (1406.6608v2)

Published 25 Jun 2014 in cs.NI

Abstract: This paper explores the feasibility, advantages, and challenges of an ICN-based approach in the Internet of Things. We report on the first NDN experiments in a life-size IoT deployment, spread over tens of rooms on several floors of a building. Based on the insights gained with these experiments, the paper analyses the shortcomings of CCN applied to IoT. Several interoperable CCN enhancements are then proposed and evaluated. We significantly decreased control traffic (i.e., interest messages) and leverage data path and caching to match IoT requirements in terms of energy and bandwidth constraints. Our optimizations increase content availability in case of IoT nodes with intermittent activity. This paper also provides the first experimental comparison of CCN with the common IoT standards 6LoWPAN/RPL/UDP.

Citations (308)

Summary

  • The paper presents the first real-world deployment and evaluation of Named Data Networking (NDN) in a full-scale building automation IoT environment.
  • Experiments showed NDN competitive or superior to 6LoWPAN/RPL/UDP in memory usage, energy consumption, and responsiveness due to optimizations like RONR.
  • While demonstrating NDN's applicability, the study identifies scalability, efficient naming, and security integration as critical challenges for large-scale IoT deployments.

Information Centric Networking in the IoT: Experiments with NDN in the Wild

The paper "Information Centric Networking in the IoT: Experiments with NDN in the Wild" offers an empirical exploration and evaluation of Named Data Networking (NDN) as a foundational solution for the Internet of Things (IoT). The research primarily underscores the tension between the potential of Information Centric Networking (ICN) and the constraints inherent in IoT devices, notably regarding memory, computational power, and energy efficiency.

Key Findings and Methodology

Conducted as the first real-world implementation, the experiments were set in a full-scale IoT deployment within an actual building environment, compliant with typical building automation standards. This paper forms a baseline comparison with traditional IoT approaches such as 6LoWPAN/RPL/UDP, providing critical insights into the feasibility of NDN within these constrained settings.

The authors pinpoint the challenge of model alignment, where ICN’s architectural benefits must be reconciled with the stringent resource limitations of IoT devices. These include constrained energy sources, minimal processing capabilities, and limited memory. The experimental setup involved 60 nodes using a wireless communication network to evaluate three configurations: Vanilla Interest Flooding (VIF), Reactive Optimistic Name-based Routing (RONR), and a combination of caching with RONR.

Technical Contributions

The analysis revealed significant opportunities for leveraging NDN in IoT deployments:

  • Control Traffic Reduction and Caching: By adopting various NDN-specific optimizations, the paper significantly attenuates control traffic and enhances energy/bandwidth efficiency. Reactive Optimistic Name-based Routing (RONR) reduces unnecessary packet transfers, thus conserving energy—a critical consideration for battery-dependent devices.
  • Comparison with Existing Protocols: The research provided a comparative evaluation of CCN against 6LoWPAN/RPL/UDP. NDN demonstrated competitive advantages, including a leaner footprint in both ROM and RAM usage and reduced energy consumption alongside improved network responsiveness.
  • Scalability Considerations: Scalability emerges as a pivotal concern in the deployment of NDN. The authors identify the efficient handling of naming, interest forwarding, and routing information as integral to maintaining low memory usage while still addressing the coverage needs of sprawling IoT networks.

Implications and Future Directions

The paper further discusses critical challenges, particularly regarding bidirectional links and varying wireless link conditions in dynamic IoT environments. It posits that enhanced adaptation layers for header compression and frame fragmentation akin to 6LoWPAN could optimize NDN for constrained devices in heterogeneous IoT deployments.

As a step forward, the authors recommend further inquiry into efficient naming conventions and security integration, emphasizing that names must be both compact and capable of supporting hierarchical aggregation without inducing unnecessary overhead. The undetermined balance between the overheads caused by name-based routing and the benefits of ICN mandates detailed algorithmic advancements targeted at energy-efficient communication models.

Conclusion

The research convincingly demonstrates the applicability of ICN and its potential enhancements through NDN in IoT ecosystems. These insights contribute to a growing understanding that information-centric designs may yield substantial benefits in constrained settings—notably in energy efficiency, scalability, and memory use. However, persistent challenges such as large-scale deployment and sustainable caching strategies necessitate ongoing research to validate ICN as a practical alternative to traditional layer-based networking approaches in IoT scenarios.