J
John P. Lehoczky
Researcher at Carnegie Mellon University
Publications - 143
Citations - 16515
John P. Lehoczky is an academic researcher from Carnegie Mellon University. The author has contributed to research in topics: Scheduling (computing) & Dynamic priority scheduling. The author has an hindex of 49, co-authored 143 publications receiving 16054 citations.
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Journal ArticleDOI
Priority inheritance protocols: an approach to real-time synchronization
TL;DR: An investigation is conducted of two protocols belonging to the priority inheritance protocols class; the two are called the basic priority inheritance protocol and the priority ceiling protocol, both of which solve the uncontrolled priority inversion problem.
Proceedings ArticleDOI
The rate monotonic scheduling algorithm: exact characterization and average case behavior
John P. Lehoczky,Lui Sha,Y. Ding +2 more
TL;DR: An exact characterization of the ability of the rate monotonic scheduling algorithm to meet the deadlines of a periodic task set and a stochastic analysis which gives the probability distribution of the breakdown utilization of randomly generated task sets are represented.
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Optimal portfolio and consumption decisions for a “small investor” on a finite horizon
TL;DR: In this paper, a general consumption/investment problem is considered for an agent whose actions cannot affect the market prices, and who strives to maximize total expected discounted utility of both consumption and investment.
Proceedings ArticleDOI
Fixed priority scheduling of periodic task sets with arbitrary deadlines
TL;DR: A general criterion for the schedulability of a fixed priority scheduling of period tasks with arbitrary deadlines is given and the results are shown to provide a basis for developing predictable distributed real-time systems.
Journal ArticleDOI
Martingale and duality methods for utility maximization in a incomplete market
TL;DR: In this paper, the authors studied the problem of maximizing the expected utility from terminal wealth in the context of a complete financial market and showed that there is a way to complete the market by introducing additional "fictitious" stocks so that the optimal portfolio for the thus completed market coincides with the original incomplete market.