# Adaptive Downward/Upward Routing Protocol for Mobile-Sensor Networks
## 5 Conclusions  
In this paper, we proposed ADUP, a routing protocol that concurrently supports upward and downward routing in mobile scenarios. It is suitable for application where all nodes are mobile and send periodical data packets to a control station that is called the sink. In addition, this sink needs to periodically contact other nodes of the network. This is the case for many monitoring and surveillance applications.  
The support of upward routing in mobility is based on our previous work, RRD+, which copes well with mobility and helps nodes make decisions on the selection of next-hops. The support of downward routing in mobility is extension work on RRD+. Nodes embed the best next-hop of nodes in the packet headers and send it to the sink inside the periodical data packets. Once the sink receives the data packets, it builds a next-hop table. Based on this table, the sink is able to build the route to reach any node in the network. Due to the fact that the best next-hop is periodically selected from a dynamic parent set, the next-hop table is also dynamic and could adapt to mobility in a timely manner. The end result for downward routing is low on overhead because the only overhead is from the embedded information in the headers of collected data packets.  
We implemented our work in Cooja and compared it with two other generic routing protocols, AODV and Flooding. Results show that ADUP outperformed AODV and Flooding on different performance metrics in mobility scenarios. Results also show that ADUP simultaneously supports upward and downward routing in dense and highly mobile scenarios. In the upward-routing process, ADUP helps nodes detect next-hops with good link quality. In the downward-routing process, ADUP helps the sink node build routes to reach any node in the network (given that this node is generating traffic towards the sink).  
In our future work, we plan to implement ADUP on a testbed or in a real outdoor scenario in order to test its efficiency when faced with real-life radio-link conditions. Even though we included link instability in our simulator in order to emulate real-life links, in a real scenario nodes also suffer from interference coming from other nearby active technologies. Emulating interference in the simulator is a difficult challenge and it will be interesting to see how ADUP reacts to this in real life. Moreover, in order to support large-scale networks with hundreds of nodes, it is necessary to introduce a similar mechanism to bloom filter in order to encode downward routes in ADUP, which could reduce the length of packet headers. In addition, we plan on supporting duty cycling and evaluating the impact of energy saving on network performance.  
Figure 9: Number of control packets.  
**Author Contributions:** Conceptualization, J.W. and G.C.; methodology, J.W. and G.C.; software, [PERSON]; validation, [PERSON] and [PERSON]; investigation, [PERSON] and G.C.; resources, [PERSON] and G.C.; data curation, [PERSON]; writing--original draft preparation, [PERSON] and G.C.; writing--review and editing, [PERSON] and G.C.; visualization, [PERSON]; supervision, [PERSON]; project administration, G.C. and M.M.; funding acquisition, G.C. and M.M.  
**Funding:** This research was conducted with the support of the European Regional Development Funds (FEDER) program of 2014-2020 and the regional council of Auvergne.  
**Conflicts of Interest:** The authors declare no conflict of interest.