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Green-PoW: An Energy-Efficient Blockchain Proof-of-Work Consensus Algorithm
Noureddine Lasla, Lina Alsahan, Mohamed Abdallah, Mohamed Younis
TL;DR
PoW’s computational puzzle consumes substantial energy, motivating ways to reduce mining costs without giving up its security level. Green-PoW uses one mining round to select a smaller group for the next, reducing energy use. The paper reports savings of up to 50% and fewer forks.
Problem
PoW’s computational puzzle consumes substantial energy, while alternatives that rationalize energy use may not meet its security level.
Source: §1 · p. 1Method
Green-PoW divides time into two-round epochs, using the first round to select a small subset of miners who exclusively compete in the second.
Source: §1 · pp. 1–2, §4 · p. 4Results
Up to 50% energy saving is reported under an equal distribution of network hashing power, alongside a reduced probability of fork occurrences.
Source: §1 · p. 2Takeaways & Limitations
The paper reports fewer forks and limits the first-round winner’s ability to participate in the next round, giving other miners a chance to win with less competition.
Source: §1 · p. 2, §5.2 · p. 7Because the network is distributed and asynchronous, multiple miners who find a block nearly simultaneously may all qualify as potential runners-up.
Source: §4.1 · p. 5
Abstract
from arXiv · showhide
This paper opts to mitigate the energy-inefficiency of the Blockchain Proof-of-Work (PoW) consensus algorithm by rationally repurposing the power spent during the mining process. The original PoW mining scheme is designed to consider one block at a time and assign a reward to the first place winner of a computation race. To reduce the mining-related energy consumption, we propose to compensate the computation effort of the runner(s)-up of a mining round, by granting them exclusivity of solving the upcoming block in the next round. This will considerably reduce the number of competing nodes in the next round and consequently, the consumed energy. Our proposed scheme divides time into epochs, where each comprises two mining rounds; in the first one, all network nodes can participate in the mining process, whereas in the second round only runners-up can take part. Thus, the overall mining energy consumption can be reduced to nearly $50\%$. To the best of our knowledge, our proposed scheme is the first to considerably improve the energy consumption of the original PoW algorithm. Our analysis demonstrates the effectiveness of our scheme in reducing energy consumption, the probability of fork occurrences, the level of mining centralization presented in the original PoW algorithm, and the effect of transaction censorship attack.
1 INTRODUCTION
Proof-of-Work (PoW) provides permissionless consensus but consumes substantial energy through its computational puzzle. Green-PoW uses first-round effort to select miners for the next round, aiming to lower energy while retaining PoW security.
1 INTRODUCTION
- PoW’s computational puzzle makes attacks costly, while alternatives that rationalize energy use may not meet its security level.The introduction notes that Proof-of-Stake can face a Nothing-at-Stake problem and that some proposed implementations remained in testing.Source: §1 · p. 1
- Green-PoW can reduce overall mining energy to nearly 50% without degrading PoW’s security level.It uses first-round power to select a small subset of miners with exclusive rights to mine in the next round.Source: §1 · pp. 1–2
- Epochs pair two mining rounds: all miners may compete in the first, while only selected runners-up may mine in the second.If the selected miners do not produce a block before a timeout, the waiting nodes resume mining to preserve liveness.Source: §1 · p. 2
- Green-PoW reduces fork probability by limiting participation in even-numbered mining rounds.The paper links the smaller second-round contender set to fewer total fork occurrences than in original PoW.Source: §1 · p. 2
- Excluding the first-round winner from the second round may reduce mining centralization by limiting dominant hash-rate miners’ block-generation potential.The paper identifies mining pools as an example of miners that may hold most of the network hash rate.Source: §1 · p. 2
- The paper evaluates energy reduction through stochastic analysis that models mining as a Poisson process.Its stated contributions also include analysis of fork occurrence, mining centralization, and transaction censorship.Source: §1 · p. 2
2 RELATED WORK
Prior energy-saving approaches either repurpose mining computation or change the consensus mechanism. The paper positions Green-PoW as modifying PoW’s participation rules rather than replacing its puzzle or substantially changing the ledger structure.
2 RELATED WORK
- Prior approaches either repurpose PoW computation or use different consensus mechanisms, which can save energy but may not match PoW security.The paper groups its own approach with efforts to improve PoW while retaining the cryptographic puzzle.Source: §2 · p. 2
- REM uses SGX to process client workloads, but depends on Intel’s server for workload validation.Other public-problem schemes can adjust difficulty but cover only predefined problem types, limiting workload utility.Source: §2 · p. 2
- Proof-of-learning uses public training and testing data, while a federated-learning variant uses local training data and homomorphic-encryption-based verification.The paper notes that the public-data approach provides no confidentiality guarantees.Source: §2 · p. 2
- Outsourced PoW can restrict lightweight clients because their limited resources may delay or prevent puzzle solving.The paper connects this constraint to fairness and service reliability concerns.Source: §2 · pp. 2–3
- Bitcoin-NG separates leader election from transaction processing, but concurrent micro-block production can create forks and expose the network to fork-related attacks.The paper concludes that this approach optimizes energy and transaction throughput while diminishing original Bitcoin’s security level.Source: §2 · p. 3
- The surveyed approaches either add complexity by replacing the crypto-puzzle or alter ledger structure and consensus flow in ways the paper says degrade security.Green-PoW is presented as seeking energy reduction while sustaining the security properties of PoW-based consensus.Source: §2 · p. 3
3 PRELIMINARIES
The preliminaries describe PoW mining, difficulty adjustment, and chain forks. Together, these concepts explain how miners create blocks, how the puzzle’s difficulty is recalibrated, and how simultaneous valid blocks can branch the chain.
3.1.1 Block mining
- Bitcoin blocks record transactions and header data, and link to the previous block through its hash.Miners race to find a 32-bit nonce yielding a block hash below the target; the first to succeed announces the block and receives newly generated Bitcoins.Source: §3.1.1 · p. 3
3.1.2 Mining difficulty
- Mining difficulty is recalculated every two weeks using the previous 2016 blocks’ average time to maintain a fixed block-generation interval.Difficulty rises when blocks arrive faster than expected and falls when network computational power drops.Source: §3.1.2 · pp. 3–4
- Difficulty adjustment can encourage investment in more powerful mining rigs, contributing to PoW’s continuing energy use as the miner network grows.Miners continue to spend despite operating costs because of the expected reward for winning the race.Source: §3.1.2 · p. 4
3.1.3 Chain forks
- A fork occurs when multiple valid blocks are broadcast simultaneously, leaving nodes with different chain heads until they adopt the longest chain.Propagation delays are a major cause; frequent forks can enable attacks that degrade blockchain security.Source: §3.1.3 · p. 4
4 ENERGY-EFFICIENT CONSENSUS ALGORITHM
Green-PoW pairs mining rounds: all miners can compete in the first, while only elected runners-up are eligible for the second. The design aims to reduce computation to nearly 50%, with timeout and difficulty rules addressing liveness and differing mining power across rounds.
4 ENERGY-EFFICIENT CONSENSUS ALGORITHM
- Nearly 50% lower computation is the stated goal of Green-PoW, which divides time into two-round epochs and limits second-round mining to elected runners-up.All miners can participate in the first round; miners outside the eligible subset wait until the block is appended.Source: §4 · p. 4
4.1 Runner(s)-up Election
- After the first-place winner is elected, mining continues to identify runner-up miners, who alone are eligible to mine in the second round.A miner may announce runner-up status or add another runner-up to the eligible set and enter mining-save mode.Source: §4.1 · p. 5
- Allowing multiple nodes to qualify as runners-up does not affect consistency and increases the chance that a block is mined in round two.The paper describes multiple runners-up as possible when nodes find the block at nearly the same time.Source: §4.1 · p. 5
4.2 Second Round Timeout
- If eligible second-round miners are isolated, block production may stall; after a timeout, inactive nodes resume mining to support liveness.The timeout should exceed the average time needed to generate a new block.Source: §4.2 · p. 5
- The timeout and η balance liveness against energy efficiency: larger η admits more runners-up but reduces efficiency, while frequent timeout fallback can also increase energy use.The paper notes that a very short timeout can cause frequent timeouts of the second round.Source: §4.2 · p. 6
4.3 Second Round Mining Difficulty
- Green-PoW uses separate difficulties for the two rounds, updating them from their respective average block times; timeout-generated blocks count toward D1, not D2.TE is the expected average block time, and TAvg1 and TAvg2 are the observed averages for the respective rounds.Source: §4.3 · pp. 6–7
5 SECURITY ANALYSIS
Green-PoW’s round restrictions are presented as reducing censorship duration and limiting powerful miners’ dominance. The analysis also connects the smaller active-miner share in round two with a lower ratio of miners unaware of a new block.
5.1 Transaction Censorship
- Nearly 50% lower censorship time is reported because a first-round winner cannot participate in the second round, limiting ordinary censorship to one round.The paper notes an exception after a second-round timeout under specific conditions, such as isolation of the eligible miners from the rest of the network.Source: §5.1 · p. 7
5.2 Mining Centralization
- Because a first-round winner cannot join the second-round race, other miners get a chance to win with less competition, limiting powerful miners’ dominance.A first-round winner may participate again only after a second-round timeout.Source: §5.2 · p. 7
5.3 Fork Occurrences
- The small active-miner share in round two also makes the ratio of miners unaware of a new block very small, which the analysis associates with fewer forks.The cited fork model relates fork probability to the ratio of unaware miners.Source: §5.3 · p. 7
5.2 Mining Centralization
- The most powerful miner’s share falls by 5% in the Green-PoW comparison, with the reduction redistributed among other nodes.The comparison uses 7,437 blocks from 50 days of Ethereum main-network data and adjusts for half of the two-consecutive-block cases.Source: §5.2 · p. 7, Figure 4 · p. 8
6 PERFORMANCE EVALUATION
The evaluation models PoW mining stochastically and uses simulations to assess Green-PoW’s energy use, hash-power distribution, runner-up selection, and timeout choices. It reports substantial savings, with outcomes depending on the second-round cohort and its hash-power distribution.
6.1 Average Power Saving in Green-PoW
- The analysis models Bitcoin mining as a Poisson process with rate λ, while miner m_i with hash-power share h_i mines at rate h_iλ.The modeled inter-arrival times follow an exponential distribution with rate λ.Source: §6 · p. 8, §6.1 · p. 8
- Selecting runners-up adds first-round energy, while second-round energy scales with their total hash power and block-mining time; the calculation excludes runner-up failure and timeout recovery.The first-round calculation accounts for the runners-up’ times to find blocks.Source: §6.1 · p. 8
6.2 Experimental Setup
- Simulations average power savings over 100,000 blocks across networks of 100, 200, and 300 miners with uniform or normal hash-power distributions.Table 1 summarizes the simulation parameters.Source: §6.2 · p. 9, Table 1 · p. 9
6.3 Results
- With one second-round miner, energy saving is nearly 50%; with more, it falls to 32%, 41%, and 44% for networks of 100, 200, and 300 miners.The comparisons are Green-PoW versus original PoW.Source: §6.3 · p. 9, Figure 5 · p. 9
- For 100 miners, Green-PoW’s second-round consumption is nearly 10% of its first-round use, and the two-round average is 30–50% below PoW.PoW’s average energy consumption is 8–10 times the second-round consumption of Green-PoW; Green-PoW uses more energy in the first round while selecting runners-up.Source: §6.3 · p. 9, Figure 6 · p. 9
- With five second-round miners in a 200-miner network, savings are minimal when 2% of miners hold 50% of hash power and maximal when hash power is equally distributed.The analysis varies the share of miners holding half the network’s hash power.Source: §6.3 · p. 9, Figure 7 · p. 10
6.4 Time-out and η Selection
- Under uniform hash power, η changes little as the second-round cohort grows; when 5% of miners hold 50% of hash power, η increases significantly.The paper attributes the increase to waiting longer for less-powerful nodes to mine and join the second-round cohort.Source: §6.4 · p. 10, Figure 8 · p. 10
- A 12–23 minute wait corresponds to a 0.7–0.9 probability of mining a second-round block, and hash-power distribution does not affect block-generation time.The paper identifies that interval as a possible timeout range; difficulty is set to maintain the average block-generation rate.Source: §6.4 · p. 10
7 CONCLUSION
Green-PoW repurposes first-round mining to select a small cohort that exclusively mines the next block, reducing overall mining energy by up to 50%. Simulations and security-property analyses report energy savings and advantages concerning forks, censorship attacks, and mining centralization.
7 CONCLUSION
- Green-PoW uses energy spent mining one block to elect a small group of miners with exclusive rights to mine the next block.Each epoch has two rounds; the first adds a small amount of power to qualify the second-round cohort.Source: §7 · p. 10
- Simulations report up to 50% mining-energy savings for a large network with equally distributed hash power.The comparison is with the original PoW algorithm.Source: §7 · p. 10
- The paper reports advantages in reducing fork occurrences, censorship-attack effects, and mining centralization.Source: §7 · p. 10