# CoNTe: A Core Network Temporal Blockchain for 5G
## 3 Federated Byzantine Agreement Consensus
### Transaction and Protocol Messages
The first simulation that is depicted in Figure 6 shows total block throughput and network efficiency for three rates of block contribution: one block per hour, one block per minute, and one block per second. Simulating block contribution at orders of magnitude is done to reflect a wide range of update frequencies possible across 5G core network functions. At 1500 km, block throughput scales up to handle network updates at rates as fast as 1 block per second without significant degradation. Network efficiency, measured as the percent of packets transmitted successfully as compared to total packets, reduces as low as 69% at this peak load. At 1500 km, both block throughput and network efficiency scale linearly at rates below one block per second. At 15,000 km, Figure 7 shows the performance roll off as a result of the additional network delay. In this simulation, as delay increases an order of magnitude, block contribution capacity drops correspondingly, with the network only able to scale to 1 block per minute without significant degradation. Network efficiency above this rate falls as low as 50%, with the additional overhead of retransmissions causing sustained reductions in block throughput beyond four graph hops at the one block per second rate. The one block per second contributed rate also shows how the system degrades under abnormally large network delays. Increasing node sizes to 50 at 1500 km (Figure 8) shows marginal impact at block rates of one per hour, while network efficiency begins to fall sooner, seeing reductions at the 1 block per minute

Figure 6: Performance and scalability of Conte at 1500 km node distances and maximum hops to graph edge of 10. Block Throughput (**left**) and Network Efficiency (**right**). transmission rate that was previously little impacted at smaller node sizes. It is important to note that overall throughput does continue to improve, and remains above the peak of the initial simulation set which capped node sizes at 10. With one block per second rates at 1500 km, we see the system become overwhelmed with block throughput dropping sharply, having a throughput rate at 50 nodes that is below that of a system having only three in the first simulation. Simulation results at 15,000 km (Figure 9) exhibit similar behavior, and they continue a downward trend already present at smaller node sizes. An interesting behavior we can see in aggregate is that network efficiency measures do not drop to levels suggested by the raw block throughput numbers. This can be explained by the CSMA/CD algorithm implementation being assigned a maximum retransmission attempt value of 10. Network efficiency as reflected here, does not consider a packet dropped, until it has already attempted transmission 10 times. Adjusting this maximum retransmission attempts also has potential to impact performance, but this is outside the scope of this writing. Figure 7: Performance and scalability of Conte at 15,000 km node distances and maximum hops to graph edge of 10. Block Throughput (**left**) and Network Efficiency (**right**). virtualization technology. 5G adopts virtualization approaches commonplace in cloud data centers to realize virtual network functions (VNF), as opposed to relying on traditional network functions with a tight coupling between software and hardware, as mentioned previously. VNFs, or more generally, a Virtual Function (VF) can be thought of as a block of functionality running within a virtualization container (e.g., Virtual Machine, containers), which can then be connected together via Virtual Links (VL) and Software Defined Networks (SDN) to provide a service (e.g., 5G Core). In 5G, the way VF is described, deployed, managed, and destroyed has been defined by the ETSI NFV group [34]. Furthermore, resource and service isolation in multi-service multi-tenant environments is achieved via the concept of 3 GPP Network Slices, which effectively treats a collection of VFs as a single administrative entity, allowing for administrators to scale VFs individually, destroy or create multi-VF services [35].