# A Geographical Heuristic Routing Protocol for VANETs
## 6 Conclusions and Future Work  
In this paper, we have proposed a generic Geographical Heuristic Routing (GHR) protocol. GHR is inspired by simulated annealing and Tabu search meta-heuristics [39]. We divide the GHR operation according to the operation in forwarding and recovery. The forwarding heuristics are used when an improvement to reach the destination is feasible. The recovery heuristics are thought to be used with the carry and forwarding approach. GHR can adapt its forwarding criterion depending on the application requirements. We use the traffic-aware MMMR [20] protocol in the core of our proposed GHR to validate and score the neighbors of the current node in the forwarding process. Nonetheless, GHR could use any other routing protocol for the validation and scoring tasks.  
An extensive performance evaluation of our proposed GHR indicates that the use of a Tabu list contributes to improving the packet delivery ratio by around 5% to 10%. However, this better performance comes at the price of an additional delay (2 s) because of the more restrictive selection process of the next forwarding node. Nonetheless, the non-real-time applications, which are objective of our work (e.g., report of traffic notifications), could cope with this delay. On the other hand, we show that the classical selection of the best node to forward a packet (i.e., the node with the best metric) and the carry and forwarding recovery are only adequate when the use of Tabu is not possible. On the contrary, if the routing process enables a Tabu list, then a forwarding strategy selection based on simulated annealing and a recovery procedure that does not use the buffer frequently are preferred.  
There are some interesting variants of the heuristics presented in this work that we believe are worth testing. Among these variants we highlight the possibility to redefine the numerator of the simulated annealing probability function by considering some function of the distances among candidate nodes. In this way, when candidates are close to each other, random selection would be preferred. Another variant in simulated annealing is not to select, with probability \(p\), a random node to forward the packet. Instead, a node will prefer, with probability \(p\), a backup node (chosen by some function) rather than the best candidate in the forwarding process.  
In our performance evaluation, we have used a single AP, which makes multi-hop communications more challenging. We could achieve a more efficient reporting service through anycast communications. Some of them constitute part of our future work, including: an optimal placement of access points, an efficient procedure to select the member of the anycast group to which the packets will be forwarded and the use of summarizing messages to reduce the rate of reports. Currently, we are developing some algorithms to select the anycast member in the routing protocol based on some of the ideas presented in this work.  
This work was partly supported by the Spanish Government through the project TEC2014-54335-C4-1-R INcident monitoRing In Smart COmmunities, QoS and Privacy (INRISCO ) and by the Universidad Autonoma de Sinaloa (Mexico) through the project PROFAPI 2014/215. [PERSON] is the recipient of a full scholarship from the Secretaria Nacional de Educacion Superior, Ciencia y Tecnologia (SENESCYT) with the sponsorship of Escuela Politecnica Nacional (EPN) (Ecuador).  
[PERSON] of the routing proposal. [PERSON], [PERSON] and [PERSON] designed the simulation tests. [PERSON] and [PERSON] performed the simulation. [PERSON], [PERSON] and [PERSON] analyzed the results. [PERSON] ran the statistical tests. [PERSON], [PERSON] and [PERSON] wrote the paper. [PERSON] supervised the entire research process.  
The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses or interpretation of data; in the writing of the manuscript; nor in the decision to publish the results.