Mechanisms for Outsourcing Computation via a Decentralized Market
July 2020·
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Scott Eisele
Taha Eghtesad
Nicholas Troutman
Aron Laszka
Abhishek Dubey
Abstract
As the number of personal computing and IoT devices grows rapidly, so does the amount of computational power that is available at the edge. Since many of these devices are often idle, there is a vast amount of computational power that is currently untapped, and which could be used for outsourcing computation. Existing solutions for harnessing this power, such as volunteer computing (e.g., BOINC), are centralized platforms in which a single organization or company can control participation and pricing. By contrast, an open market of computational resources, where resource owners and resource users trade directly with each other, could lead to greater participation and more competitive pricing. To provide an open market, we introduce MODiCuM, a decentralized system for outsourcing computation. MODiCuM deters participants from misbehaving—which is a key problem in decentralized systems—by resolving disputes via dedicated mediators and by imposing enforceable fines. However, unlike other decentralized outsourcing solutions, MODiCuM minimizes computational overhead since it does not require global trust in mediation results. We provide analytical results proving that MODiCuM can deter misbehavior, and we evaluate the overhead of MODiCuM using experimental results based on an implementation of our platform.
Type
Venue
14th ACM International Conference on Distributed and Event-Based Systems (DEBS 2020), 61–72
Authors
Ph.D. 2026
Taha Eghtesad joined the Applied Artificial Intelligence Lab as a Ph.D. student in Fall 2018 and received his Ph.D.
in 2026 under the supervision of Dr. Aron Laszka. He received a B.S. degree in Computer Engineering, with a minor in
Software Engineering, from Shahid Beheshti University, Tehran, Iran. His research lies at the intersection of
machine learning, game theory, cyber-physical systems, and systems security. In particular, his Ph.D. research
focused on using artificial intelligence and machine learning to make cyber-physical systems more secure.
Associate Professor
Aron Laszka is an Associate Professor in the College of Information Sciences and Technology at the Pennsylvania State University. Previously, he was an Assistant Professor at the University of Houston, a Research Assistant Professor at Vanderbilt University, and a Postdoctoral Scholar at the University of California, Berkeley.
His research interests revolve around artificial intelligence and cyber-physical systems, focusing on machine learning for decision making and optimization, with applications in smart and connected communities, critical infrastructure, and cybersecurity.
His research is funded by the National Science Foundation, the Department of Energy, the Department of Transportation, and other agencies.