Pruhs, Kirk - Department of Computer Science, University of Pittsburgh

• Scalable Dissemination: What's Hot and What's Not Jonathan Beaver \Lambda Nicholas Morsillo \Lambda Kirk Pruhs \Lambda Panos K. Chrysanthis \Lambda
• Dynamic Speed Scaling to Manage Energy and Temperature Nikhil Bansal
• Algorithmic Problems in Power Management Sandy Irani
• An Optimal Deterministic Algorithm for Online bMatching
• Cake Cutting Really is Not a Piece of Cake Jeff Edmonds # Kirk Pruhs +
• Dynamic Spectrum Allocation: The Impotency of Duration Notification
• Speed Scaling to Manage Temperature Nikhil Bansal 1 and Kirk Pruhs 2
• Online Weighted Matching Bala Kalyanasundaram 1 Kirk Pruhs 2
• Middleware Support for Multicast-based Data Dissemination: A Working Reality
• Algorithmic Problems in Power Management Sandy Irani
• Cake Cutting Really is Not a Piece of Cake Jeff Edmonds
• From SIAM News, Volume 38, Number 3, April 2005 Computer Scientists Optimize
• A Constant Approximation Algorithm for Sorting Buffers
• Eliminating Migration in MultiProcessor Scheduling *
• Caching for Web Searching Bala Kalyanasundaram \Lambda
• Scheduling Broadcasts in Wireless Networks Bala Kalyanasundaram \Lambda
• Online Network Optimization Problems Bala Kalyanasundaram and Kirk Pruhs
• Constructing Competitive Tours From Local Information
• A Comparison of Multicast Pull Models Kirk R. Pruhs \Lambda Patchrawat Uthaisombut y
• Competitive Online Scheduling for Server Systems Computer Science Department
• Online Weighted Flow Time and Deadline Scheduling Luca Becchetti \Lambda Stefano Leonardi \Lambda Alberto Marchetti--Spaccamela \Lambda
• Speed Scaling for Weighted Flow Time Nikhil Bansal
• Speed Scaling of Tasks with Precedence Constraints
• Not All Insertion Methods Yield Constant Approximate Tours in the Euclidean Plane
• Maximizing Job Completions Online Bala Kalyanasundaram \Lambda Kirk R. Pruhs y
• An Optimized Multicast-based Data Dissemination Middleware: A Demonstration
• Online Load Balancing of Temporary Tasks \Lambda Yossi Azar y
• The Online Transportation Problem Bala Kalyanasundaram \Lambda Kirk R. Pruhs y
• Online Scheduling Kirk Pruhs \Lambda Jir'i Sgall y Eric Torng z
• Semiclairvoyant Scheduling Luca Becchetti 1 , Stefano Leonardi 1 ,
• Balanced Allocations of Cake Jeff Edmonds
• Evaluating the Local Ratio Algorithm for Dynamic Storage Allocation ?
• Dynamic Speed Scaling to Manage Energy and Temperature Nikhil Bansal
• We introduce resource augmentation as a method for analyzing online scheduling problems. In resource augmentation analysis the online scheduler is given more resources, say faster processors or more pro
• FaultTolerant RealTime Scheduling Bala Kalyanasundaram \Lambda Kirk Pruhs y
• The Multicast Pull Advantage in Dissemination-based Data Jonathan Beaver, Kirk Pruhs, Panos K. Chrysanthis
• Getting the Best Response for Your Erg Kirk Pruhs \Lambda Patchrawat Uthaisombut y Gerhard Woeginger z
• Errata: A New Algorithm for Scheduling Periodic, RealTime Tasks Bala Kalyanasundaram \Lambda
• Server Scheduling in the L p A Rising Tide Lifts All Boat
• Multicast Pull Scheduling: When Fairness is Fine Jeff Edmonds \Lambda Kirk Pruhs y
• Minimizing Flow Time Nonclairvoyantly Bala Kalyanasundaram \Lambda