Marlin-Preis 

POND

Marlin is the brainchild of developers Siddhartha, Prateesh and Roshan, all of whom have extensive experience in peer-to-peer networking.

Responsible for the development of Zilliqa, the first high-throughput blockchain to employ sharding in production, Siddhartha has had expexrience working at Microsoft and Adobe and is the author of the 2 US patents. Prateesh is a PhD candidate at the Massachusetts Institute of Technology (MIT) with a focus on Computer Networks and Roshan, an avid open-source enthusiast, was a contributor to the Boost C++ libraries.

The project employs former researchers at Ethereum Foundation, International Collegiate Programming Contest (ICPC) world medallists and developers with experience at Facebook, Cisco and Bosch. It counts the former CEO of Bittorrent and professors at MIT and Princeton amongst its advisors including authors of seminal P2P papers such as Chord DHT. Marlin is backed by the likes of Binance Labs, Electric Capital and Michael Arrington.

Marlin is one of the few layer-0 projects focussed on network layer optimizations. Similar to Filecoin which is incentivized IPFS, Marlin claims to be the equivalent of an incentived libp2p. This makes Marlin ubiquitous in the decentralized web as any peer-to-peer application relies on networking between distributed nodes to function.

Marlin is thus blockchain-agnostic. It offers gateways built for several layer-1 as well as layer-2 platforms. Unlike several other scaling solutions which suffer from the scalability trilemma where either one of performance, decentralization or security is sacrificed, improvements in the network layer are not subject to such constraints which primarily govern consensus layers.

Built atop Ethereum, the correctness of execution of the Marlin smart contracts is protected by the network of Ethereum nodes.

In addition- * The Marlin network consisting of Metanodes risk having their staked MPOND and delegated POND being slashed if the network faces DDoS and spam attacks due to their failure to verify content that they introduce into the network. * Not unlike Proof-of-Work, the network uses tunable redundancy via erasure coding to ensure users receive performance and availability guarantees with the SLAs they demand and are proportionately charged for it. * A network of third-party auditors with probes across the globe, pre-approved by the Pond DAO, provide constant performance and coverage monitoring for applications that demand higher reliability. An insurance fund backed by the DAO is used to compensate users who incur a loss due to the network’s inability to meet its SLA guarantees.