# 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  
RNS is mainly replaced by more informed selection criteria in the P2P topology optimization. This modification helps to improve blockchain metrics, such as average finality time. The average finality time measures how long it takes for most peers to get a newly created block. Because a long time equals a lower transactional throughput, these strategies choose neighbors with the shortest communication delay. The authors in [69; 76] used a score-based algorithm to influence how the underlying peer-to-peer of the bitcoin network is formed. Peers with the smallest propagation delay were given a high score and also selected as neighbors. After receiving ten blocks, each peer updates its neighbors by randomly selecting new neighbors and only adding if it has high scores as determined by the algorithm. By shortening block propagation time, [PERSON] et al. [69] realized a reduction in latency by about 12.5%, whereas [PERSON] et al. [76] reduced latency by 75%. At a higher scale, however, this could lead to too much reliance on a peer when it has the shortest propagation times and can consequently degrade the node's performance. In high-throughput networks, the periodic peer update process could increase the network'soverall bandwidth. This approach can be made more efficient by putting in measures to prevent any peer from having too many neighbors (crowding). Bandwidth-efficient peer update techniques could also be introduced to minimize excessive consumption of network resources at high scale. [PERSON] et al. [77] developed a scheme to improve data broadcasting in a blockchain network. Their approach organized the peer-to-peer network into a tree structure. When a node receives a new block from its parent node, it broadcasts it to its children node. Since there is no interconnection between children nodes of any two parent nodes, their method ensured that duplicate transmissions did not occur. This tree structure can, therefore, simultaneously increase bandwidth efficiency, transactional throughput and also scales well with network size. Using a DHT, [PERSON] et al. [78] reduced redundancy by 7%. [PERSON] et al. [79] proposed the Ari protocol as a solution that modeled the peer-to-peer network as an inter-crossing net instead of other approaches that employed a unidirectional tree-based P2P topology [77]. Blocks are first split into equal parts, and a serial number is assigned to each piece before they are broadcast into the network. The transmitted blocks take the shortest path in the inter-crossing net to their destination peers; this improved network-wide latency by about 50%. The splitting technique applied also helped achieve some savings in bandwidth. However, when it grows, the split-and-scatter technique can bottleneck the blockchain's performance since nodes may have to wait a longer time to receive all parts of blocks that have been scattered in the network. It will also make inefficient use of bandwidth since more peers will have to frequently request block parts from different peers. BlockP2P by [PERSON] et al. [80] is a technique proposed to improve transactional throughput by minimizing latency in the blockchain network. As shown in Figure 6, the main idea behind this approach is to group blockchain peers into a cluster based on the geographical location. This technique leads to a cluster of small diameter and, therefore, reduces propagation time within the cluster. Furthermore, since the network consists of several clusters, the authors designated some nodes, called routing nodes, which connect to routing nodes of other clusters to ensure full connectivity. The authors gained a net increase in transactional throughput due to the reduced latency of about 90%. When a small network size is considered, the clustering approach has better bandwidth efficiency than Random Neighbor Selection. However, when the network grows, crowding can occur in a cluster and reduce intra-cluster efficiency. Although [PERSON] et al.