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J. Sedlmeir et al.: The Energy Consumption of Blockchain Technology, Bus Inf Syst Eng 62(6):599–608 (2020) 605 enormous, and, therefore, the contribution to total energy consumption by redundant operations may be significant. Hence, it is not only alternative consensus mechanisms that one should look at to further reduce the energy consump- tion of blockchain technology, but also concepts which allow reduced operation redundancy. Generally speaking, the primary motivations behind all of the concepts pre- sented in this section that may help to reduce redundancy are increased scalability, throughput, and privacy for blockchain solutions. Conveniently, these all happen to reduce the degree of redundancy and, therefore, improve the overall energy consumption. We can distinguish between two approaches to reducing redundancy: reducing the degree of redundancy, i.e., the number of nodes that perform certain operations, and the workload associated with operating a transaction. In attempts to reduce the degree of redundancy, a concept called sharding is often mentioned. Sharding is about splitting the nodes in the network into subsets (‘‘shards’’) and processing each transaction on only one of these sub- sets. How easily sharding can be achieved largely depends on the consensus mechanism. For example, sharding is very difficult to apply to PoW blockchains, because one has to make sure that, within a shard, computing power is roughly equally distributed to maintain a balance of voting weight among the associated nodes. In a PoS blockchain, voting power is tied to the capital deposited by each node. This information is publicly available and can, therefore, be freely used in creation of shards. Other concepts to reduce the degree of redundancy include off-chain payment channels between two parties who repeatedly interact. Such channels usually require a transaction on the blockchain, in the course of which off-chain payment channels are created and terminated. Ideally, however, all interim transactions are operated purely bilateral and do not involve a trans- action on the corresponding blockchain. That is to say that, ideally, only balances, or accumulated deltas signed by the members on the payment hub, are periodically recorded on- chain. Payment hubs, a generalization of payment channels to multiple parties, e.g., Nocust, or connections between them, e.g., Lightning for Bitcoin or Raiden for Ethereum, are the focus of active research (Gudgeon et al. 2019). A similar basic concept is the use of sidechains (e.g., Plasma for Ethereum). These are small blockchain networks which periodically refer to the main chain as a highly reliable root. Generally speaking, however, reducing the degree of redundancy also makes a blockchain network more cen- tralized and must, therefore, be carefully weighed against concerns about security, liveness, and trust. Finding a good compromise between these interests could enable a reduction of the total workload in the system, and, there- fore, a reduction of its total energy consumption. On the other hand, the workload associated with redundant operations, e.g., the verification of new blocks, can be significantly reduced, which also mitigates the redundancy issue. One very straightforward improvement is, therefore, optimization of the computational complexity of the used cryptographic algorithms, e.g., for verifying signatures. Yet, this has some natural limits: Currently, transactions are operated ‘‘naively’’ on all nodes in the sense that all transaction-related data must be provided on- chain and all nodes recompute every step on their own. This could be significantly improved by storing and veri- fying only short correctness proofs on a blockchain and distributing the larger, plaintext data on another layer to the relevant participants. In particular, SNARKS, STARKS, and other (Zero-Knowledge-)Proofs of computational integrity which require much less verification and com- munication overhead on-chain seem very promising (Ben- Sasson et al. 2019). This is because, unlike methods that lower the degree of redundancy, these do likely not have a negative impact on security because every transaction is still verified by every node. In summary, there are various ways to reduce the intrinsic redundancy of blockchains and, therefore, to reduce also their energy consumption. The relative energy saving potential is, however, negligible for PoW block- chains as the energy consumption of mining dominates all other contributions. However, it may still be relatively high for networks in which consensus is not energy-intensive, in particular, if the network is large. 5 A First Comparison of Different Architectures We can now use our results from the previous chapters to make a first comparison of the energy consumption of typical blockchain architectures. The role of consensus has already been discussed in Sect. 3, where we suggested that a major distinction should be made between PoW and non- PoW blockchains, although the differences between other consensus mechanisms might also be significant. On the other hand, for small networks, redundancy does not add much absolute energy consumption, particularly when compared to the scale of PoW blockchains’ energy con- sumption. By contrast, for large systems consisting of many nodes, the natural redundancy in a blockchain can lead to much higher energy consumption. If a PoS or alternative non-PoW blockchain replaces Bitcoin or another PoW cryptocurrency in the future, we have to expect that there will still be tens of thousands of nodes. Although the energy consumption of such a network will be negligible compared to Bitcoin, it will, therefore, remain high compared to a non-blockchain centralized system with minimal redundancy (i.e., because of backups). Figure 2 123PDF Image | The Energy Consumption of Blockchain Technology
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