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The Evolution of Cloud Computing
Published in John W. Rittinghouse, James F. Ransome, Cloud Computing, 2017
John W. Rittinghouse, James F. Ransome
In 1941, the introduction of Konrad Zuse’s Z3 at the German Laboratory for Aviation in Berlin was one of the most significant events in the evolution of computers because this machine supported both floating-point and binary arithmetic. Because it was a “Turing-complete” device,2 it is considered to be the very first computer that was fully operational. A programming language is considered Turing-complete if it falls into the same computational class as a Turing machine, meaning that it can perform any calculation a universal Turing machine can perform. This is especially significant because, under the Church-Turing thesis,3 a Turing machine is the embodiment of the intuitive notion of an algorithm. Over the course of the next two years, computer prototypes were built to decode secret German messages by the U.S. Army.
Sleptsov Net Computing resolves problems of modern supercomputing revealed by Jack Dongarra in his Turing Award talk in November 2022
Published in International Journal of Parallel, Emergent and Distributed Systems, 2023
The paper also gives an impartial historical view of the parallel software schemata development. Firstly, parallel processes schemata appeared in the early works of Frank and Lilian Gilbreth dated 1921 and were standardized in 1947. In 1958, Gill started using bipartite-directed graphs to specify parallel computations. In 1962, Petri further develops the model of place-transitions nets adding tokens and transition firing rule. Agerwala and Hack extend the model with inhibitor arcs in 70-ties. Salwicki and Sleptsov in 80-ties generated ideas of the maximal parallel and the multiple transition firing, further developed and published in the works of Burkhard and Zaitsev. Turing complete place-transition nets represent a perfect graphical language for concurrent computing, though they run exponentially slower compared to a Turing machine. Finally, Sleptsov net mends this flaw running fast and opening prospects for hardware implementation of a homogenous massive parallel supercomputer. The prospective direction is implemented in prototypes awaiting investments for its full-scale implementation. Let us apply at least 10% of wasted 99.2% of investment into modern USA supercomputers (the number taken from Jack Dongarra Turing Award Talk) to SNC implementation project to obtain a new record of real-life efficiency of computations.
Microgrid trading mechanism enhancement for smart contract considering reputation values
Published in Cyber-Physical Systems, 2023
Zhikang Wang, Wendi Wu, Zhengtian Wu, Baochuan Fu
Nick Szabo introduced smart contracts in 1994, which are computer programs that can repeat physical/traditional contract [31]. In a blockchain, a smart contract cannot be modified once it is completed and uploaded, while its contents can be easily observed, verified and automatically executed due to the open and transparent nature of the blockchain [9] thus providing a decentralised, traceable, tamperproof, open and transparent solution to the high risk and cost of transactions caused by centralisation [32]. It was created in 2015 by Vitalik Buterin and is a blockchain platform with decentralised payments and a Turing-complete programming language that allows smart contracts to be written on the blockchain [33]. Lua and Solidity are two programming languages used to develop smart contracts [34]. Developers define transaction rules within smart contracts on platforms such as Ether, and then publish the smart contract on the blockchain and make them available for common use by all users participating in the blockchain. Algorithm 1 shows the main functional code snippet of a smart contract in energy trading.
‘Un’-blocking the industry 4.0 value chain with cyber-physical social thinking
Published in Enterprise Information Systems, 2023
Subodh Mendhurwar, Rajhans Mishra
Arbitrary state transition function (enabled through a Turing complete programming language, which enables smart contracts and mark advent of Blockchain 2.0 era – Li et al. 2020) provides open-ended design for both financial and non-financial protocols (Buterin 2014a). Smart contracts can’t be unilaterally altered by any participant, thereby providing autonomy and transparency beyond traditional code (De Filippi 2018), can help maintain transactional privacy (e.g., Kosba et al. 2016), and are a possible way out (albeit added-complexity) to address the Blockchain Paxos anomaly (Natoli and Gramoli 2016). Blockchain systems support smart contracts (lightweight decentralised application dAPP) via a variety of Contract Languages like (i) EVM Bytecode (Ethereum, Counterparty, Monax), (ii) Solidity (RSK), (iii) Transaction Chains (Stellar), (iv) JavaScript (Lisk), etc. (Li et al. 2020). DAPP and its Internet communication processes face privacy leakage risks (Li et al. 2020).