Blockchain Network Studies
Enabled by SimBlock
Kazuyuki Shudo

Tsuyoshi Hasegawa

Akira Sakurai

Ryohei Banno

Kyoto University

Kyoto University

Tokyo Institute of Technology

Kogakuin University

Abstract—A blockchain network simulator SimBlock was developed to enable large-scale blockchain researches. Since it wasreleased in June 2019, it has facilitated number of studies onblockchain performance and security. We demonstrate how sucha simulator enables blockchain studies by showing experiments
running on SimBlock.

I. I NTRODUCTION
A public blockchain is a large-scale decentralized distributed system operating over Internet. Studies on the network
aspects of blockchain require a simulator. Either operating
thousands of nodes or implementing a newly proposed technique to them are nearly impossible.
We developed a blockchain network simulator SimBlock[1], [2] and made it publicly available in June 2019. Since therelease of SimBlock, it has facilitated number of blockchain
researches by us as well as others. The main topic has been
block propagation performance and how to link it to transaction throughput. Security has also been an important topic
because it is closely related to performance of a blockchain.
In this demonstration, we show experiments for our studies
running on SimBlock. The audience understand how thesimulator facilitates blockchain studies.
II. S IM B LOCK : A BLOCKCHAIN NETWORK SIMULATOR
SimBlock is an event-driven simulator that simulates ablockchain network wherein tens of thousands of nodes relay
blocks over Internet. The followings describe Simblock.
• Simulating Internet– SimBlock treats Internet divided into six regions,
Europe, North America, Asia, Australia, Japan, andSouth Africa.
– The communication time is calculated based onthe bandwidth and latency between two nodes. The
bandwidth and latency depend on the regions wherethe sender and the receiver reside. The current SimBlock provides network parameters of Internet as of2015 and 2019.
• Simulating blockchain nodes– A node generates and broadcasts a block at timings
determined by the algorithm. If nodes run PoW, oneof all the nodes generates a block once per about
defined block interval.
This work was supported by JSPS KAKENHI Grant Number JP21H04872.
978-8-3503-1019-1/23/$31.00 ©2023 IEEEFig. 1. SimBlock visualizer.

– A node relays a received block.
Fig. 1 is a screenshot of the Simblock visualizer. It reads
a simulation log and shows a movie in which nodes communicate with each other. Though results of a study are foundin a simulation log, such visualization allows us to confirm
expected execution of an experience and it gives insights intoexperiments.
III. R ESEARCH ENABLED BY S IM B LOCKThe followings are studies we conducted utilizing SimBlock.
• Improvement of SimBlock itself– Implementation of Compact Block Relay and evaluation of its impacts [3]• Block propagation performance– Neighbor selection [4]– Evaluation of relay networks [5], [6]– Delivery tree [7], and delivery trees [8]– Sender switchover [9]– Block generation notification with a bloom filter [10]• Transaction throughput– Block interval adjustment while keeping fairness [11]– Block interval adjustment for transaction throughput[12]• Security– Simulation of selfish mining [13]– Saving attacks to Ethereum-like PoS blockchains[14]– Precise theoretical fork rate considering hash rate
[15]

Proc. 2023 IEEE Int'l Conf. on Blockchain and Cryptocurrency(IEEE ICBC 2023), May 2023

agation performance as far as messages reach all the nodes
within the time slot. But, once this premise is broken due
to network troubles or attacks, convergence among multiple
nodes becomes a problem. SimBlock could contribute to a
study of such a situation [14].
IV. C ONCLUSION

Fig. 2. Results of experiments enabled by SimBlock.

Our proposed
bloom filter-based method Compact Block Relay (CBR)

Legacy (without CBR)

Graphene

Fig. 3. Experiments visualized.

The so-called scalability problem of blockchains is shortageof transaction throughput. It is famous that initial Bitcoin
provided only 7 TPS. Naive solutions to the problem areincreasing block size and decreasing block interval. But theysacrifice security by increasing fork rate [16].
Increasing transaction throughput without sacrificing security requires faster block propagation. It has been one of
our research topics. Our latest proposal is block generation
notification with a bloom filter [10]. Fig. 2 shows the effect of
the technique. It achieves a propagation delay of 302 millisecond, less than half that of state-of-the-art methods. SimBlockenabled the experiments and its visualizer demonstrates thedifferences of propagation performance as shown in Fig. 3.
Faster block propagation itself does not improve transaction
throughput. It rather enables shorter block interval or larger
block size without sacrificing security. So we next worked
on shortening the block interval. The first work focuses on
keeping fairness [11], and the next work focuses on keeping
security [12].
SimBlock also enabled security studies [13], [14], [15].
Ethereum-like PoS blockchains do not care about block prop-

A blockchain network simulator SimBlock has enabled
number of studies from performance to security.
The current SimBlock deals with blocks, not transactions.
Simulation of transactions requires introduction of a transaction generation model, in which each node broadcasts transactions in its own frequency. Another possible improvement
is consideration of Tor. In case of today’s Bitcoin, over a halfof nodes communicate over Tor [17]. Tor will make communication slow much and Bitcoin simulation could consider it.
R EFERENCES[1] Y. Aoki, K. Otsuki, T. Kaneko, R. Banno, and K. Shudo, “SimBlock:A blockchain network simulator,” in Proc. IEEE INFOCOM 2019
Workshops (CryBlock 2019), Apr. 2019.
[2] R. Banno and K. Shudo, “Simulating a blockchain network withSimBlock,” in Proc. IEEE ICBC 2019, May 2019, pp. 3–4.
[3] R. Nagayama, R. Banno, and K. Shudo, “Identifying impacts of protocol
and Internet development on the Bitcoin network,” in Proc. IEEE ISCC
2020, Jul. 2020, pp. 506–510.
[4] Y. Aoki and K. Shudo, “Proximity neighbor selection in blockchainnetworks,” in Proc. IEEE Blockchain 2019, Jul. 2019, pp. 52–58.
[5] K. Otsuki, Y. Aoki, R. Banno, and K. Shudo, “Effects of a simple relay
network on the Bitcoin network,” in Proc. AINTEC 2019, Aug. 2019,pp. 41–46.
[6] K. Otsuki, R. Banno, and K. Shudo, “Quantitatively analyzing relay
networks in Bitcoin,” in Proc. IEEE Blockchain 2020, Nov. 2020, pp.
214–220.
[7] Y. Kitagawa, K. Shudo, O. Mizuno, and R. Banno, “Verification ofapplying Plumtree algorithm for blockchain networks,” in Proc. ICETC
2021, Dec. 2021.
[8] ——, “Simulation evaluation of multiple Plumtree application inblockchain networks,” in IEICE technical report NS2022, Mar. 2023,(unrefereed, and in Japanese).
[9] A. Sakurai and K. Shudo, “Accelerating block propagation by senderswitchover in a blockchain,” in IEICE technical report IA2021-67, Mar.
2021, pp. 52–57, (unrefereed, and in Japanese).
[10] T. Hasegawa, A. Sakurai, and K. Shudo, “Optimizing block generation
notification using bloom filter in a blockchain,” in Proc. DEIM 2023,
Mar. 2023, (unrefereed, and in Japanese).
[11] R. Kanda and K. Shudo, “Block interval adjustment toward fair Proofof-Work blockchains,” in Proc. ICDE 2020 Workshops (BlockDM 2020),
Apr. 2020, pp. 1–6.
[12] M. Arakawa and K. Shudo, “Block interval adjustment based on blockpropagation time in a blockchain,” in Proc. IEEE Blockchain 2022, Aug.
2022, pp. 202–207.
[13] R. Nagayama and K. Shudo, “Simulating Ethereum network withSimBlock,” lightning talk, Devcon 5, Ethereum Foundation, Oct. 2019.
[14] K. Otsuki, R. Nakamura, and K. Shudo, “Impact of saving attacks onblockchain consensus,” IEEE Access, vol. 9, pp. 133 011–133 022, Sep.
2021.
[15] A. Sakurai and K. Shudo, “Impact of the hash rate on the theoreticalfork rate of blockchain,” in Proc. IEEE ICCE 2023, Jan. 2023.
[16] Y. Sompolinsky and A. Zohar, “Secure high-rate transaction in Bitcoin,”in Proc. FC 2015, Jan. 2015, pp. 507–527.
[17] “Bitnodes,” https://bitnodes.io (accessed Apr. 4, 2023).

Proc. 2023 IEEE Int'l Conf. on Blockchain and Cryptocurrency(IEEE ICBC 2023), May 2023