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Redefining Resource Allocation in Computing Systems
By Jacob Chasan
A new kernel1 is in town. The current industry-standard for resource allocation on computers does not take the user’s preferences into account, rather programs are given access to resources based on the time that each requested to be run. Although this system can lead to solutions that minimize the time it takes for a program to receive an allocation, it often leads to an incentive misalignment between the programs and the user. This misalignment is exacerbated as the current queue based systems have no inherent mechanism to prevent a tragedy of the commons issue, whereby programs take more resources from the system than the value they provide to the user. By shifting to a market-based approach, where computing resources are allocated to programs based on how much utility the user receives from each program, the incentives of the programs and the users align. With inherent market mechanisms to keep the incentives aligned, this new paradigm leads to at least superior levels of utility for a user.
1As described in subsequent parts of this paper, the kernel is the core program within an operating system which is given the authority to allocate the hardware resources amongst the programs on the computer.
Advisors: Professor Benjamin C. Lee, Professor Atila Abdulkadiroglu, Professor Michelle Connolly | JEL Codes: C8, C80
Structural Estimation of FCC Bidder Valuation
By Renhao Tan, Zachary Lim, and Jackie Xiao
We modify a method introduced in Fox and Bajari (2013) which structurally estimates the deterministic component of bidder valuations in FCC spectrum auctions based on a pairwise stability condition: two bidders cannot exchange two licenses in a way that increases the sum of their valuations, and we apply it to C block auctions 5, 22, 35 and 58. Our modifications improve the fit of the Fox and Bajari (2013)’s estimator especially in similar auctions involving big bidders. We find that there is evidence of significant “cross-auction” complementaries between licenses sold in a particular auction and those already owned by these endowed bidders.
Advisor: Michelle Connolly | JEL Codes: D44, D45, H82, L82
