## 4 Results
### Evolution of Simulation Results with the Number of Hops
Because of the branch selection criteria implemented by CBL, the node-to-relay distance is greatly reduced for the CBL-OLSR clustering protocol. It can also be observed that while a higher-density scenario increases this distance in the case of TFD-OLSR, CBL-OLSR does the opposite and uses even closer relays. The second reason for observing better end-to-end delay through CBL-OLSR is the reduced amount of routing traffic, which leaves more resources available for the benefit of application traffic. However, when the exchanging nodes are three hops away or more, depending on the network density, a diversity may appear in the choice of routes from the source to the destination. In this case, Figure 9 shows that a mesh-like clustering strategy adopted in TFD-OLSR actually achieves a better packet delivery ratio than a backbone-like clustering such as in CBL-OLSR. Indeed, the latter mainly relies on the backbone through branch-branch links, which become single points of failure in the resulting longitudinal structure; in TFD-OLSR, the mesh structure built offers alternative routes. Another explanation relates to a structural problem that is resolved better by TFD-OLSR than by CBL-OLSR. With the latter, when an elected branch node exits the radio range, its leaf nodes must quickly reconnect to an existing branch node or elect one from scratch. Meanwhile, they all miss their single relay. With TFD-OLSR, an MPR node that exits the one-hop neighborhood of a node does not necessarily let all the two-hop neighbors of that node uncovered since multiple MPR nodes can cover them. This result illustrates the redundancy contribution to performance enhancement brought by mesh-like clustering to application traffic. Therefore, these results establish that backbone-like clustering leads to better end-to-end delay and routing traffic overhead, while mesh-like clustering maintains a better packet delivery ratio by increasing both node density and route length in number of IP hops. None of these solutions actually outperforms the other. One way to try to deal with the latter issue is to consider a new metric which we refer to as the \"bit-delay\". The bit-delay is obtained by dividing the amount of the application traffic received by the related end-to-end delay. In this way, the end-to-end delay achieved by each protocol is considered, along with the total amount of application traffic actually delivered within this delay. In medium node density scenarios, TFD-OLSR bit delay is lower than that of CBL-OLSR (Figure 10a), whereas in higher-density CBL-OLSR bit-delay is lower (Figure 10b). This can be interpreted as follows: when a clustering scheme achieves the least bit-delay, its advantage regarding the metric on which it is the best is superior to the advantage of the other protocol on the metric on which the latter is the best. Therefore, the advantage of TFD-OLSR in terms of packet delivery ratio is superior to the end-to-end delay offered by CBL-OLSR in the S2 medium node density scenario, while CBL-OLSR clearly offers an advantage for the end-to-end delay that is superior to the packet delivery ratio offered by TFD-OLSR in high node density scenarios (S3). In this case, for example, if an application requires packets to be delivered at a constant rate, CBL-OLSR could be a better choice since more units of data could be received in less time. Figure 8: Mean node-to-relay distances in medium (S2) and high (S3) node density scenarios. Figure 10: Mean bit-delay in medium (S2) and high (S3) node density scenarios. Figure 9: Delivery ratio in medium (S2) and high (S3) node density.