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.
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Matchmaking In Crowd-Shipping Platforms: The Effects Of Mediator Control
A critical design decision for crowdsourcing platforms is the degree to which the platform mediator controls participant interactions. Platforms having a centralized model of mediation optimize for convenience, speed, and security in participant interactions, while platforms operating under decentralized control require greater user effort but offer them greater control and agency. The research described in this paper is a preliminary study using agent-based modeling to evaluate and compare the performance of crowd-shipping platforms with centralized/decentralized control over matchmaking of carriers and senders. Results indicate that centralized matchmaking protects the platform from premature failure when initial carrier/sender participation is low. Furthermore, when the platform’s assignment algorithm is designed to maximize platform revenue, subject to meeting carriers’ profit expectations, centralized matchmaking will tend to outperform decentralized matchmaking for both the mediator and the carriers.
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- Award ID(s):
- 2046632
- PAR ID:
- 10539906
- Publisher / Repository:
- IEEE
- Date Published:
- Journal Name:
- Proceedings Winter Simulation Conference
- ISSN:
- 1558-4305
- ISBN:
- 979-8-3503-6966-3
- Page Range / eLocation ID:
- 303 to 314
- Format(s):
- Medium: X
- Location:
- San Antonio, TX, USA
- Sponsoring Org:
- National Science Foundation
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