Alper Alimoğlu successfully defended his thesis titled “EBlocBroker: An Autonomous Blockchain-Based Computational Broker for E-Science” under the supervision of Prof. Dr. Can Özturan on 24 July 2024. We heartily congratulate him!
Abstract:
Blockchain infrastructures have emerged as a disruptive technology and have led to the realization of cryptocurrencies (peer-to-peer payment systems) and smart contracts. They can have a wide range of application areas in e-Science due to their open, public nature and global accessibility in a trustless manner. We propose and implement a smart contract called eBlocBroker, which is an autonomous blockchainbased middleware system for selling computing power and providing data resources for e-Science. The eBlocBroker infrastructure connects requesters who need to combine applications (jobs) with datasets and run them via an Ethereum-based private blockchain network (Bloxberg) on providers that utilize computational and data resources on clouds or home servers. It uses cloud storage, such as B2DROP, IPFS, or Google Drive, to store and transfer data between requesters and providers. Each provider utilizes the Slurm workload manager to execute jobs submitted through eBlocBroker. In this thesis, we demonstrate how an autonomous organization programmed as a smart contract can be used to deploy a marketplace that
supports data and computation-intensive research projects. We propose a cost model implemented as a function in the smart contract that calculates and records computation, transfer, storage, and cache usage costs. We develop a Python-based system to communicate with eBlocBroker and orchestrate the execution of jobs on the provider’s end. We present eBlocBroker’s features, infrastructure, implementation, algorithms, and experimental results. Furthermore, scientific workflows are essential for many applications, enabling the configuration and execution of complex tasks across distributed resources. We contribute an Ethereum blockchain-based scientific workflow execution manager, which distributes workflows to run on cluster computing providers.
We extended eBlocBroker by providing distributed workflow execution via blockchain. Through various tests, we demonstrate how our eBlockBroker autonomous organization, which is programmed as a smart contract, can manage scientific workflow submission, scheduling, and execution on cluster computing providers. The utilization of blockchain for distributed workflow execution is a new concept. We are motivated because our system has been developed with e-Science in mind, where scientific workflows are widely utilized. Finally, we contribute a decentralized autonomous software organization model and an Ethereum blockchain-based smart contract named AutonomousSoftwareOrg that provides a continuously operating virtual organization for software development communities and users. AutonomousSoftwareOrg provides a project funding mechanism based on crypto-currencies, a decision-making mechanism based on voting, and recordkeeping for software usage citations and executions. Furthermore, software executions, along with their input and output data files, can also be transactionally recorded in AutonomousSoftwareOrg. This enables software execution graphs to be constructed for analysis. In addition, a model of input/output data and software executions is presented using an AND/OR graph. AutonomousSoftwareOrg is deployed and tested on the Ethereum-based Bloxberg blockchain network that is run by
academic and research institutions.
Journal Papers:
- Alimoglu, A. and C. Ozturan, “An autonomous blockchain-based computational broker for e-science”, Concurrency and Computation: Practice and Experience, Vol. 36, No. 13, p. e8087, 2024.
- Alimoglu, A. and C. Ozturan, “An autonomous blockchain-based workflow execution broker for e-science”, Cluster Computing, May 2024.
Conference Paper:
- Alimoglu, A. and C. Ozturan, “Design of a Smart Contract Based Autonomous Organization for Sustainable Software”, 13th IEEE International Conference on e-Science, e-Science 2017, Auckland, New Zealand, October 24-27, 2017, pp. 471476, IEEE Computer Society, 2017.
