You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.

Main Abstract:
Proof-of-Stake systems randomly choose, on each round, one of the participants as a consensus leader that extends the chain with the next block such that the selection probability is proportional to the owned stake. However, distributed random number generation is notoriously difficult. Systems that derive randomness from the previous blocks are completely insecure; solutions that provide secure random selection are inefficient due to their high communication complexity; and approaches that balance security and performance exhibit selection bias. When block creation is rewarded with new stake, even a minor bias can have a severe cumulative effect. In this paper, we propose Robust Round Robin, a new consensus scheme that addresses this selection problem. We create reliable long-term identities by bootstrapping from an existing infrastructure, such as Intel's SGX processors, or by mining them starting from an initial fair distribution. For leader selection we use a deterministic approach. On each round, we select a set of the previously created identities as consensus leader candidates in round robin manner. Because simple round-robin alone is vulnerable to attacks and offers poor liveness, we complement such deterministic selection policy with a lightweight endorsement mechanism that is an interactive protocol between the leader candidates and a small subset of other system participants. Our solution has low good efficiency as it requires no expensive distributed randomness generation and it provides block creation fairness which is crucial in deployments that reward it with new stake.

Cited Abstract(s):
[1]: The DFINITY blockchain computer provides a secure, performant and flexible consensus mechanism. At its core, DFINITY contains a decentralized randomness beacon which acts as a verifiable random function (VRF) that produces a stream of outputs over time. The novel technique behind the beacon relies on the existence of a unique-deterministic, non-interactive, DKG-friendly threshold signatures scheme. The only known examples of such a scheme are pairing-based and derived from BLS. The DFINITY blockchain is layered on top of the DFINITY beacon and uses the beacon as its source of randomness for leader selection and leader ranking. A "weight" is attributed to a chain based on the ranks of the leaders who propose the blocks in the chain, and that weight is used to select between competing chains. The DFINITY blockchain is layered on top of the DFINITY beacon and uses the beacon as its source of randomness for leader selection and leader ranking blockchain is further hardened by a notarization process which dramatically improves the time to finality and eliminates the nothing-at-stake and selfish mining attacks. DFINITY consensus algorithm is made to scale through continuous quorum selections driven by the random beacon. In practice, DFINITY achieves block times of a few seconds and transaction finality after only two confirmations. The system gracefully handles temporary losses of network synchrony including network splits, while it is provably secure under synchrony.
DFINITY [1] introduces a novel decentralized an random beacon that leverages BLS threshold signatures for periodic unbiased random values generation. This scheme requires a setup phase during which an expensive distributed key generation (DKG) protocol is run. Once this is done, new random values can be derived by collecting signature shares from sufficiently many participants. In this approach, the per round or per epoch randomness generation has low communication complexity, but the main cost is the expensive DKG protocol in the setup phase that needs to be repeated when new participants join or leave the system.