We investigate the minimal number of failures that can partition a system where processes communicate both through shared memory and by message passing. We prove that this number precisely captures the resilience that can be achieved by algorithms that implement a variety of shared objects, like registers and atomic snapshots, and solve common tasks, like randomized consensus, approximate agreement and renaming. This has implications for the m&m-model and for the hybrid, cluster-based model.

A popular programming technique that contributes to designing provably-correct distributed applications is to use shared objects for interprocess communication, instead of more low-level techniques. Although shared objects are a convenient abstraction, they are not generally provided in large-scale distributed systems; instead, the processes keep individual copies of the data and communicate by sending messages to keep the copies consistent. Traditional distributed computing considers a static system, with known bounds on the number of fixed computing nodes and the number of possible failures. Dynamic distributed systems allow nodes to enter and leave the system at will, either due to failures and recoveries, moving in the real world, or changes to the systems' composition. Motivating applications include those in peer-to-peer, sensor, mobile, and social networks, as well as server farms.

Blockchain platforms such as Ethereum and several others execute complex transactions in blocks through user-defined scripts known as smart contracts. Normally, a block of the chain consists of multiple transactions of smart contracts which are added by a miner. To append a correct block into the blockchain, miners execute these transactions of smart contracts sequentially. Later the validators serially re-execute the smart contract transactions of the block. If the validators agree with the final state of the block as recorded by the miner, then the block is said to be validated. It is then added to the blockchain using a consensus protocol. In Ethereum and other blockchains that support cryptocurrencies, a miner gets an incentive every time such a valid block successfully added to the blockchain. In most of the current day blockchains the miners and validators execute the smart contract transactions serially. In the current era of multi-core processors, by employing the serial execution of the transactions, the miners and validators fail to utilize the cores properly and as a result, have poor throughput. By adding concurrency to smart contracts execution, we can achieve better efficiency and higher throughput. In this paper, we develop an efficient framework to execute the smart contract transactions concurrently using optimistic Software Transactional Memory systems (STMs). Miners execute smart contract transactions concurrently using multi-threading to generate the final state of blockchain. STM is used to take care of synchronization issues among the transactions and ensure atomicity. Now when the validators also execute the transactions (as a part of validation) concurrently using multi-threading, then the validators may get a different final state depending on the order of execution of conflicting transactions. To avoid this, the miners also generate a block graph of the transactions during the concurrent execution and store it in the block. This graph captures the conflict relations among the transactions and is generated concurrently as the transactions are executed by different threads. The miner proposes a block which consists of set of transactions, block graph, hash of the previous block, and final state of each shared data-objects. Later, the validators re-execute the same smart contract transactions concurrently and deterministically with the help of block graph given by the miner to verify the final state. If the validation is successful then proposed block appended into the blockchain and miner gets incentive otherwise discard the proposed block. We execute the smart contract transactions concurrently using Basic Time stamp Ordering (BTO) and Multi-Version Time stamp Ordering (MVTO) protocols as optimistic STMs. BTO and MVTO miner achieves 3.6x and 3.7x average speedups over serial miner respectively. Along with, BTO and MVTO validator outperform average 40.8x and 47.1x than serial validator respectively.