# 3D Void Handling Geographic P2P-RPL for Indoor Multi-Hop IR-UWB Networks
## 5 Conclusions  
In this paper, 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. Based on the idea of benefiting from both the P2P-RPL's high reliability in real-life implementation and geographic routing's high energy efficiency in intuitive simple routing operation, GVA-P2P-RPL shows the high performance of reducing the huge routing overheads, keeping the high level of route discovery capability, and decreasing the route discovery time in both void-free and void-apparent 3D indoor IR-UWB-based multi-hop LLNs environments. The proposed ATT algorithm enabled faster route discovery by using a smaller minimum trickle timer interval value and adaptively shortening the nodes'  
Figure 23: Route discovery time (ms).  
Figure 22: Energy consumption (mJ) and hop count.  
listen-only periods. Accurate location information is provided to nodes with the presented 3D multi-hop self-positioning scheme in advance of the greedy forwarding procedure. The simulation results for GVA-P2P-RPL show significantly improved performance evaluations, compared with P2P-RPL, PF-P2P-RPL and ER-RPL in terms of low overhead, high route discovery success rate and short route discovery time in real-life 3D indoor environments. In a void-apparent network scenario, GVA-P2P-RPL's energy consumption from transmitting and receiving P2P-DIO messages is reduced about 91.3% compared to ER-RPL, the state-of-the-art RPL-based P2P routing protocol. The 99.4% route discovery success ratio of GVA-P2P-RPL is only 0.3% lower than the 99.7% of P2P-RPL, which proves GVA-P2P-RPL's high reliability in the routing procedure. The route discovery time of GVA-P2P-RPL is about 41.1% shorter than that of ER-RPL, which shows its fast routing ability in real-time implementation. As future work, we aim to improve our current work by developing it into a context-based routing protocol, using the \"Context Histories\" and \"Context Prediction\" concepts [27; 28; 29; 30]. A context-based application utilizes any relevant information that describes its surrounding environment and circumstances, and adapts its behavior to changes in that relevant information. GVA-P2P-RPL only uses the geographical location information of nodes in its routing decisions. In future, we plan to observe and analyze the information of more varied contexts, such as the mobility of nodes, remaining battery power, and behavior of users, which are collected from the past to the present for the provision of better routing decisions.  
Conceptualization, D.K.; methodology, D.K.; validation, D.K.; formal analysis, D.K. and Y.K.; investigation, D.K. and J.J.; resources, D.K. and J.J.; data curation, D.K.; writing--original draft preparation, D.K. and J.J.; writing--review and editing D.K. and Y.K.; visualization, D.K.; supervision, Y.K.; project administration, Y.K. All authors have read and agreed to the published version of the manuscript. This research received no external funding. This paper was supported by the Korea Institute for Advancement of Technology (KIAT) grant funded by the Korea Government (MOTIE) (N0002428, The Competency Development Program for Industry Specialist). The authors declare no conflict of interest.