# A Survey on Network Optimization Techniques for Blockchain Systems
## 5 Network Optimization Techniques Used in Blockchain Networks
### Network Layer
#### 5.1.2 P2P Topology Optimization
[81] also used a similar approach, their work was susceptible to network partitioning and eclipse attacks since a star topology was used within a cluster. [PERSON] et al. [82] introduced the concept of \"iTracker\". The iTracker is an entity owned and operated by the ISPs that provide internet to peers in the blockchain network. When a node wants to connect to another node in a different cluster, the iTracker of the originating node connects to the iTracker in charge of the destination cluster. The iTracker returns the node with the smallest propagation time to the originating peer. Since the iTracker is  
Figure 6: Clustering of Peers by [PERSON] et al. [80]. responsible for topology, there is better bandwidth usage due to reduced overhead caused by fully distributed topology management. Similar to other techniques that employ this clustering approach, it also offers improved transactional throughput and could also suffer reduced performance at a large scale when intra-cluster crowding is not mitigated. [PERSON] et al. [83] used a centralized approach, as shown in Figure 7, to reduce the overhead incurred by the distributed network management of a vanilla blockchain. Dedicated servers generated the P2P topology and assigned neighbors to each peer. This method provided a flexible way to manage the network and make it possible to tune the topology in real time. The topology generation used both clustering and Random Neighbor Selection, but, unlike other clustering-based approaches, they introduced a constraint to limit intra-cluster crowding. The SDN-inspired topology management resulted in significant savings in bandwidth when compared to traffic generated by topology and network management in distributed approaches. Even though the authors did not evaluate their work in terms of blockchain-related metrics, this approach has the potential to improve transactional throughput. This is because nodes have fewer responsibilities and can, therefore, dedicate all their resources to process more transactions. Moreover, the topology can also be tuned to minimize latency and speed up transaction confirmation. It is, however, noteworthy that topology computation time increases with an increase in network size. Therefore, research consideration should be given to multiple controllers to help the network scale up. [PERSON] et al. [84] used a hybrid architecture to manage the P2P network of blockchain, as shown in Figure 8. One peer is voted into a leadership role to take charge of topology management. Normal peers send their neighbor list to the leader. The leader then uses the neighbor lists to calculate a Minimum Spanning Tree (MST) and sends back the optimum neighbors to each peer. Propagation delay is the cost used to calculate the MST problem. Therefore, each peer receives neighbors who offer the best propagation delay and ultimately leads to an improvement in transactional throughput. Similar to [PERSON] et al., decoupling the P2P management leads to decent savings in bandwidth. However, when a new leader is elected, it will have to request the neighbor list of all peers again and compute the topology. Since this is an inefficient use of bandwidth, measures can be put in place to ensure that topology and membership will not be lost if the current leader becomes unavailable. Moreover, the MST calculation time increases with increasing peer membership. Therefore, multi-leader scenarios should be considered to reduce topology calculation time as the network scales up. Figure 7: SDN-Inspired Topology Management by [PERSON] et al. [83].