Publications Database

Welcome to the new Schulich Peer-Reviewed Publication Database!

The database is currently in beta-testing and will be updated with more features as time goes on. In the meantime, stakeholders are free to explore our faculty’s numerous works. The left-hand panel affords the ability to search by the following:

  • Faculty Member’s Name;
  • Area of Expertise;
  • Whether the Publication is Open-Access (free for public download);
  • Journal Name; and
  • Date Range.

At present, the database covers publications from 2012 to 2020, but will extend further back in the future. In addition to listing publications, the database includes two types of impact metrics: Altmetrics and Plum. The database will be updated annually with most recent publications from our faculty.

If you have any questions or input, please don’t hesitate to get in touch.

 

Search Results

Andrei Tara, Hjalmar K. Turesson, Nicolae Natea, Henry M. Kim (2023). "An Evaluation of Storage Alternatives for Service Interfaces Supporting a Decentralized AI Marketplace", IEEE Access, 11, 116919 - 116931.

Open Access Download

Keywords
Abstract Given the exploding interest in generative AI and the concern that a few companies like Microsoft will monopolize access to such models, we address this centralization risk in the context of a DApp that matches buyers and sellers of various AI services. A key question for a decentralized marketplace is where and how to store the metadata that specifies the services’ properties in human and machine-readable formats. Having one or a few actors controlling access to that data constitutes undesirable centralization. We explore data storage alternatives to ensure decentralization, equitable match-making, and efficiency. Classifying decentralized storage alternatives as simple peer-to-peer replication, replication governed by a permissionless consensus, and replication governed by a private consensus, we select an exemplar for each category: IPFS, Tendermint Cosmos and Hyperledger Fabric. We conduct experiments on performance and find that read and write speeds are fastest for IPFS, about two times slower for Tendermint and slowest for Hyperledger. Writing using IPFS and Tendermint takes significantly longer than reading, and finally, specifically with IPFS, write speeds strongly depend on configuration. Given these results and the properties of the storage technologies, we conclude that simple peer-to-peer storage is the best option for the proposed AI marketplace.

Saxena, Shivam, Hany Farag, Aidan Brookson, Hjalmar Turesson, and Henry M. Kim (2020). "A Permissioned Blockchain System to Reduce Peak Demand in Residential Communities via Energy Trading: A Real-World Case Study", IEEE Access, 9, 5517-5530.

Open Access Download

Keywords
Abstract Residential energy trading systems (RETS) enable homeowners with distributed energy resources (DERs) to participate in virtualized energy markets that have the potential to reduce the peak demand of residential communities. Blockchains are key enablers of RETS, by virtue of providing a decentralized, self-governed network that mitigates concerns regarding privacy and transparency. However, more real-world case studies are needed to evaluate the techno-economic viability of blockchain-based RETS to improve their positive uptake. Thus, this article develops a permissioned blockchain-based RETS, which enables homeowners to select bidding strategies that consider the individual preferences of their DERs, and further evaluates the impact of the bidding strategies on reducing the peak demand of the community. The proposed system is implemented on the permissioned Hyperledger Fabric platform, where a decentralized ledger is used to store all energy bids, and a smart contract is used to execute a double auction mechanism and dispatch the homeowner DERs. The proposed system is validated by conducting simulations on a 8-home community using real-world data, and also by deploying the system to a Canadian microgrid, where the smart contract execution time is benchmarked. Simulation results demonstrate the efficacy of the proposed system by achieving a peak demand reduction of up to 48 kW (62%), which leads to an average savings of $1.02 M for the distribution system operator by avoiding transformer upgrades. Also, the simulation results show that the execution time of the proposed smart contract is 17.12 seconds across 12 nodes, which is sufficient for RETS.