Ecole Polytechnique, Nov 11, 2007 1 List Scheduling on Related Machines processors 1 2 3 Related machines: machines may have different speeds  0.25 

Slides:



Advertisements
Similar presentations
On Designing Truthful Mechanisms for Online Scheduling V. Auletta, R. De Prisco, P.P. and G. Persiano Università di Salerno.
Advertisements

Tight Bounds for Online Class- constrained Packing Hadas Shachnai Bell Labs and The Technion IIT Tami Tamir The Technion IIT.
1 SOFSEM 2007 Weighted Nearest Neighbor Algorithms for the Graph Exploration Problem on Cycles Eiji Miyano Kyushu Institute of Technology, Japan Joint.
Branch and Bound Example. Initial lower bound Jrpd Use 1 machine preemptive schedule as lower bound Job 2 has a lateness of 5,
Online Scheduling with Known Arrival Times Nicholas G Hall (Ohio State University) Marc E Posner (Ohio State University) Chris N Potts (University of Southampton)
Dynamic Wavelength Allocation in All-optical Ring Networks Ori Gerstel and Shay Kutten Proceedings of ICC'97.
Characterizing the Distribution of Low- Makespan Schedules in the Job Shop Scheduling Problem Matthew J. Streeter Stephen F. Smith Carnegie Mellon University.
PTAS for Bin-Packing. Special Cases of Bin Packing 1. All item sizes smaller than Claim 1: Proof: If then So assume Therefore:
Ecole Polytechnique, Nov 7, Minimizing Total Completion Time Each job specified by  procesing time (length p j )  release time r j Goal: compute.
1 Ecole Polytechnque, Nov 7, 2007 Scheduling Unit Jobs to Maximize Throughput Jobs:  all have processing time (length) = 1  release time r j  deadline.
Transactional contention Management as a Non- Clairvoyant Scheduling Problem Hagit Attiya, Leah Epstein, Hadas Shachnai, Tami Tamir Presented by Anastasia.
Worst-case Equilibria Elias Koutsoupias and Christos Papadimitriou Presenter: Yishay Mansour Tight Bounds for Worst-case Equilibria Artur Czumaj and Berthold.
Online Algorithms Motivation and Definitions Paging Problem Competitive Analysis Online Load Balancing.
Wroclaw University, Sept 18, Approximation via Doubling (Part II) Marek Chrobak University of California, Riverside Joint work with Claire Kenyon-Mathieu.
Krakow, Jan. 9, Outline: 1. Online bidding 2. Cow-path 3. Incremental medians (size approximation) 4. Incremental medians (cost approximation) 5.
Resource augmentation and on-line scheduling on multiprocessors Phillips, Stein, Torng, and Wein. Optimal time-critical scheduling via resource augmentation.
1 Set # 3 Dr. LEE Heung Wing Joseph Phone: Office : HJ639.
Load Balancing, Multicast routing, Price of Anarchy and Strong Equilibrium Computational game theory Spring 2008 Michal Feldman.
Truthful Mechanisms for One-parameter Agents Aaron Archer, Eva Tardos Presented by: Ittai Abraham.
Convergence Time to Nash Equilibria in Load Balancing Eyal Even-Dar, Tel-Aviv University Alex Kesselman, Tel-Aviv University Yishay Mansour, Tel-Aviv University.
CSE 421 Algorithms Richard Anderson Lecture 6 Greedy Algorithms.
1 Worst-Case Equilibria Elias Koutsoupias and Christos Papadimitriou Proceedings of the 16th Annual Symposium on Theoretical Aspects of Computer Science.
Ecole Polytechnique, Nov 7, Online Job Scheduling Marek Chrobak University of California, Riverside.
Randomized Competitive Analysis for Two Server Problems Wolfgang Bein Kazuo Iwama Jun Kawahara.
Job Scheduling Lecture 19: March 19. Job Scheduling: Unrelated Multiple Machines There are n jobs, each job has: a processing time p(i,j) (the time to.
1 Krakow, Jan. 9, 2008 Approximation via Doubling Marek Chrobak University of California, Riverside Joint work with Claire Kenyon-Mathieu.
Price of Anarchy Bounds Price of Anarchy Convergence Based on Slides by Amir Epstein and by Svetlana Olonetsky Modified/Corrupted by Michal Feldman and.
Iterative Flattening in Cumulative Scheduling. Cumulative Scheduling Problem Set of Jobs Each job consists of a sequence of activities Each activity has.
Minimizing Flow Time on Multiple Machines Nikhil Bansal IBM Research, T.J. Watson.
 On-line problem  Input arrives one at a time, and a decision is made (and cannot be changed).  In the minADM problem: lightpaths arrive one at a time,
Paging for Multi-Core Shared Caches Alejandro López-Ortiz, Alejandro Salinger ITCS, January 8 th, 2012.
Minimizing Makespan and Preemption Costs on a System of Uniform Machines Hadas Shachnai Bell Labs and The Technion IIT Tami Tamir Univ. of Washington Gerhard.
International Graduate School of Dynamic Intelligent Systems, University of Paderborn Improved Algorithms for Dynamic Page Migration Marcin Bieńkowski.
Competitive On-Line Admission Control and Routing By: Gabi Kliot Presentation version.
Throughput Competitive Online Routing Baruch Awerbuch Yossi Azar Serge Plotkin.
Yossi Azar Tel Aviv University Joint work with Ilan Cohen Serving in the Dark 1.
Approximation schemes Bin packing problem. Bin Packing problem Given n items with sizes a 1,…,a n  (0,1]. Find a packing in unit-sized bins that minimizes.
1 By: MOSES CHARIKAR, CHANDRA CHEKURI, TOMAS FEDER, AND RAJEEV MOTWANI Presented By: Sarah Hegab.
© 2009 IBM Corporation 1 Improving Consolidation of Virtual Machines with Risk-aware Bandwidth Oversubscription in Compute Clouds Amir Epstein Joint work.
1 Server Scheduling in the L p norm Nikhil Bansal (CMU) Kirk Pruhs (Univ. of Pittsburgh)
Techniques for truthful scheduling Rob van Stee Max Planck Institute for Informatics (MPII) Germany.
Department of Computer Science Stanley P. Y. Fung Online Preemptive Scheduling with Immediate Decision or Notification and Penalties.
Princeton University COS 423 Theory of Algorithms Spring 2001 Kevin Wayne Approximation Algorithms These lecture slides are adapted from CLRS.
Approximation Schemes Open Shop Problem. O||C max and Om||C max {J 1,..., J n } is set of jobs. {M 1,..., M m } is set of machines. J i : {O i1,..., O.
1 Wroclaw University, Sept 18, 2007 Approximation via Doubling Marek Chrobak University of California, Riverside Joint work with Claire Kenyon-Mathieu.
Outline Introduction Minimizing the makespan Minimizing total flowtime
Instructor Neelima Gupta Table of Contents Factor 2 algorithm for Bin Packing Factor 2 algorithm for Minimum Makespan Scheduling Reference:
A Optimal On-line Algorithm for k Servers on Trees Author : Marek Chrobak Lawrence L. Larmore 報告人:羅正偉.
Loss-Bounded Analysis for Differentiated Services. By Alexander Kesselman and Yishay Mansour Presented By Sharon Lubasz
Analysis of cooperation in multi-organization Scheduling Pierre-François Dutot (Grenoble University) Krzysztof Rzadca (Polish-Japanese school, Warsaw)
1 Fault-Tolerant Consensus. 2 Communication Model Complete graph Synchronous, network.
Tight Bounds for Online Vector Bin Packing Ilan Cohen Joint work with : Yossi Azar,Bruce Shepherd, Seny Kamara.
Online Bipartite Matching with Augmentations Presentation by Henry Lin Joint work with Kamalika Chaudhuri, Costis Daskalakis, and Robert Kleinberg.
Approximation Algorithms for Scheduling Lecture 11.
Lecture 8: Dispatch Rules
Maximum Matching in the Online Batch-Arrival Model
Load Balancing: List Scheduling
An Optimal Lower Bound for Anonymous Scheduling Mechanisms
On Scheduling in Map-Reduce and Flow-Shops
Chapter 16: Greedy Algorithms
Polynomial time approximation scheme
Richard Anderson Lecture 6 Greedy Algorithms
Richard Anderson Autumn 2016 Lecture 7
Richard Anderson Lecture 7 Greedy Algorithms
Selfish Load Balancing
Branch and Bound Example
György Dósa – M. Grazia Speranza – Zsolt Tuza:
Richard Anderson Winter 2019 Lecture 7
List Scheduling Given a list of jobs (each with a specified processing time), assign them to processors to minimize makespan (max load) In Graham’s notation:
Richard Anderson Autumn 2019 Lecture 7
Presentation transcript:

Ecole Polytechnique, Nov 11, List Scheduling on Related Machines processors Related machines: machines may have different speeds  0.25  0.5  1 1 1 jobs 1 1 1

Ecole Polytechnique, Nov 11,  0.25  0.5  1 jobs Algorithm 2PACK(L): schedule each job on the slowest machine whose load will not exceed 2L L 2L2L processors Hey, the opt makespan is at most L

Ecole Polytechnique, Nov 11, Lemma: If the little birdie is right (opt makespan ≤ L) then 2PACK will succeed. Proof: Suppose 2PACK fails on job h h’s length on processor 1 ≤ L, so load of processor 1 > L r = first processor with load ≤ L (or m+1, if no such processor) 1 2 … … m L 2L2L Claim: if opt executes k on a machine in {r,r+1,…,m} then so does 2PACK optimum 2PACK r r

Ecole Polytechnique, Nov 11, … … m L 2L2L k so k‘s length here ≤ L so k fits on r k r r optimum 2PACK k suppose k executed here Lemma: If the little birdie is right (opt makespan ≤ L) then 2PACK will succeed. Proof: Suppose 2PACK fails on job h h’s length on processor 1 ≤ L, so load of processor 1 > L r = first processor with load ≤ L (or m+1, if no such processor) Claim: if opt executes k on a machine in {r,r+1,…,m} then so does 2PACK

Ecole Polytechnique, Nov 11, … … m L 2L2L r r optimum 2PACK So opt’s (speed-weighted) total load on processors {1,2,…,r-1} is > (r-1)L Lemma: If the little birdie is right (opt makespan ≤ L) then 2PACK will succeed. Proof: Suppose 2PACK fails on job h h’s length on processor 1 ≤ L, so load of processor 1 > L r = first processor with load ≤ L (or m+1, if no such processor) In other words: if 2PACK executes k on a machine in {1,2,…,r-1} then so does opt So some opt’s processor has load > L -- contradiction

Ecole Polytechnique, Nov 11, Algorithm: 1. Let B j = 2·( … + 2 j ) = 2(2 j+1 -1) “bucket” j : time interval [B j-1, B j ] (of length 2·2 j ) 2. j = 0 while there are unassigned jobs apply 2PACK with L = 2 j in bucket j if 2PACK fails on job k let j = j+1 and continue (starting with job k)

Ecole Polytechnique, Nov 11, k bucket j 1 2 m … processor B1B1 B2B2 B j-1 BjBj B j+1 … k k’

Ecole Polytechnique, Nov 11, Analysis: Suppose the optimal makespan is u Choose j such that 2 j-1 < u ≤ 2 j Then 2PACK will succeed in j ’th bucket (L = 2 j ) so algorithm’s makespan ≤ 2·( … +2 j ) and We get competitive ratio 8

Ecole Polytechnique, Nov 11, Theorem: There is an 8-competitive online algorithm for list scheduling on related machines (to minimize makespan). With randomization the ratio can be improved to 2e. [Aspnes, Azar, Fiat, Plotkin, Waarts ‘06] World records: upper bound ≈ (4.311 randomized) lower bound ≈ (2 randomized) [Berman, Charikar, Karpinski ‘97] [Epstein, Sgall ‘00] List Scheduling on Related Machines