Abstract

IETF has standardized the point-to-point RPL (P2P-RPL) to ensure reliable and optimal P2P route discovery for low-power and lossy networks (LLNs). P2P-RPL propagates route discovery packets to all nodes in the network, which results in high routing communication overheads. Recently, other RPL-based P2P routing algorithms have been proposed to reduce such overheads, but still, quite an amount of overheads occur due to their flooding-based approach. In real life 3D environments, a larger number of nodes should be deployed to guarantee the full network connectivity, and thus the flooding strategy incurs higher overheads. In effort to alleviate high overheads, geographic routing is an attractive solution that exploits the nodes’ geographic locations in its next-hop routing selection. However, geographic routing inherently suffers from the local minimum (void) problem following greedy next-hop selection. Local minima occur more often in 3D space, and therefore, a reliable 3D void handling technique is required. In this paper, we propose greedy forwarding and void handling point-to-point RPL with adaptive trickle timer (GVA-P2P-RPL), which is a novel RPL-based P2P routing protocol that quickly discovers energy-efficient and reliable P2P routes in 3D networks. In GVA-P2P-RPL, P2P-RPL is modified to greedily forward routing packets when it is possible. IR-UWB-based 3D multi-hop self-positioning is conducted in advance to obtain the geographical location of each node. When local minima are encountered, routing packets are temporarily broadcast just like in the traditional P2P-RPL. A new trickle algorithm called adaptive trickle timer (ATT) is also presented to reduce route discovery time and provide better collision avoidance effects. The performance of GVA-P2P-RPL is compared with that of P2P-RPL, partial flooding-based P2P-RPL (PF-P2P-RPL) and ER-RPL. It shows significant improvements in route discovery overheads and route discovery time against these state-of-the-art RPL-based P2P routing methods in 3D environments. Performance evaluation in the special network case where a huge 3D void volume exists in the center is also presented to show the strong void recovery capability of the proposed GVA-P2P-RPL in 3D environments.

Highlights

  • Reliable and energy-efficient point-to-point (P2P) routing is strongly demanded, especially for low-power and lossy networks (LLNs) due to LLNs’ lossy network configuration and resource-constraint characteristics

  • We present the adaptive trickle timer (ATT) in 3D GVA-P2P-RPL, which uses a shorter minimum trickle timer interval Imin parameter value by adaptively changing the listen-only periods to reduce the long route discovery time

  • We present the GVA-P2P-RPL which significantly improves the P2P-RPL standard’s energy efficiency and route discovery time in 3D indoor LLNs environments

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Summary

Introduction

Reliable and energy-efficient point-to-point (P2P) routing is strongly demanded, especially for low-power and lossy networks (LLNs) due to LLNs’ lossy network configuration and resource-constraint characteristics. Other RPL-based P2P routing protocols, such as LA-P2P-RPL [2] and ER-RPL [3], have been proposed, which only allow a portion of network nodes to participate in the flooding procedure These are experimentally proven to be reliable and energy saving, compared to P2P-RPL but still produce quite an amount of overheads due to the flooding strategy. We propose a reactive 3D geographic P2P routing protocol called greedy forwarding and void handling point-to-point RPL with adaptive trickle timer (GVA-P2PRPL) for indoor 3D IR-UWB (impulse radio ultra-wideband) networks. When a local minimum is encountered, GVA-P2P-RPL switches its mode to the void recovery mode and temporarily broadcasts routing packets until a node closer to the destination is discovered.

Related Works
IR-UWB Based 3D Multi-Hop Self Localization with Bounding-Box and Mobile Tracking Scheme
Greedy Forwarding and Void Handling Point-to-Point RPL in 3D Indoor Environments
Performance Evaluation
Findings
Conclusions
Full Text
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