Skip to main content
Top
Published in: Journal of Scheduling 2/2019

27-11-2018

Scheduling problems over a network of machines

Authors: Zachary Friggstad, Arnoosh Golestanian, Kamyar Khodamoradi, Christopher Martin, Mirmahdi Rahgoshay, Mohsen Rezapour, Mohammad R. Salavatipour, Yifeng Zhang

Published in: Journal of Scheduling | Issue 2/2019

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

We consider scheduling problems in which jobs must be processed through a (shared) network of machines. The network is given in the form of a graph, the edges of which represent the machines. We are also given a set of jobs, each specified by its processing time and a path in the graph. Every job must be processed in the order of edges specified by its path. We assume that jobs can wait between machines and preemption is not allowed; that is, once a job starts processing on a machine, it must be completed without interruption. Every machine can only process one job at a time. The makespan of a schedule is the earliest time by which all the jobs have finished processing. The completion time of a job in a schedule is defined as the time it finishes processing on its last machine. The total completion time refers to the sum of completion times of all the jobs. Our focus is on finding schedules with the minimum sum of completion times or minimum makespan. In this paper, we develop several algorithms (both approximate and exact) for the problem both on general graphs and when the underlying graph of machines is a tree. Even in the very special case when the underlying network is a simple star, the problem is very interesting as it models a biprocessor scheduling with applications to data migration.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Footnotes
1
They claim a 3-approximation for makespan and a 7-approximation for the min-sum objective, but the sketch of the proof they provide for the latter seems incorrect and there is no full proof for it.
 
2
The mentioned approximation ratios for randomized algorithms are in expectation.
 
3
We ideally want to find the largest set of jobs that can be scheduled at any given time \(t_i\). However, to ensure the tractability of our algorithm, we settle for a proper set as defined instead.
 
Literature
go back to reference Antoniadis, A., Barcelo, N., Cole, D., Fox, K., Moseley, B., Nugent, M., & Pruhs, K. (2014). Packet forwarding algorithms in a line network. In LATIN 2014: Theoretical informatics—11th Latin American symposium, Montevideo, Uruguay, March 31—April 4, 2014. Proceedings (pp. 610–621). Antoniadis, A., Barcelo, N., Cole, D., Fox, K., Moseley, B., Nugent, M., & Pruhs, K. (2014). Packet forwarding algorithms in a line network. In LATIN 2014: Theoretical informatics—11th Latin American symposium, Montevideo, Uruguay, March 31—April 4, 2014. Proceedings (pp. 610–621).
go back to reference Bansal, N., Kimbrel, T., & Sviridenko, M. (2006). Job shop scheduling with unit processing times. Mathematics of Operations Research, 31(2), 381–389.CrossRef Bansal, N., Kimbrel, T., & Sviridenko, M. (2006). Job shop scheduling with unit processing times. Mathematics of Operations Research, 31(2), 381–389.CrossRef
go back to reference Bhattacharya, S., Kulkarni, J. & Mirrokni, V. S. (2014). Coordination mechanisms for selfish routing over time on a tree. In Automata, languages, and programming—41st international colloquium, ICALP 2014, Copenhagen, Denmark, July 8–11, 2014, Proceedings, Part I (pp. 186–197). Bhattacharya, S., Kulkarni, J. & Mirrokni, V. S. (2014). Coordination mechanisms for selfish routing over time on a tree. In Automata, languages, and programming—41st international colloquium, ICALP 2014, Copenhagen, Denmark, July 8–11, 2014, Proceedings, Part I (pp. 186–197).
go back to reference Chaudhuri, K., Godfrey, B., Rao, S., & Talwar, K. (2003). Paths, trees, and minimum latency tours. In 44th symposium on foundations of computer science (FOCS 2003), October 11–14, 2003, Cambridge, MA, USA, proceedings (pp. 36–45). Chaudhuri, K., Godfrey, B., Rao, S., & Talwar, K. (2003). Paths, trees, and minimum latency tours. In 44th symposium on foundations of computer science (FOCS 2003), October 11–14, 2003, Cambridge, MA, USA, proceedings (pp. 36–45).
go back to reference Cook, W. J., Cunningham, W. H., Pulleyblank, W. R., & Schrijver, A. (1998). Combinatorial optimization. New York, NY: Wiley. Cook, W. J., Cunningham, W. H., Pulleyblank, W. R., & Schrijver, A. (1998). Combinatorial optimization. New York, NY: Wiley.
go back to reference Feige, Uriel, & Scheideler, Christian. (2002). Improved bounds for acyclic job shop scheduling. Combinatorica, 22(3), 361–399.CrossRef Feige, Uriel, & Scheideler, Christian. (2002). Improved bounds for acyclic job shop scheduling. Combinatorica, 22(3), 361–399.CrossRef
go back to reference Gandhi, R., Halldórsson, M. M., Kortsarz, G., & Shachnai, H. (2008). Improved bounds for scheduling conflicting jobs with minsum criteria. ACM Transactions on Algorithms, 4(1), 11:1–11:20.CrossRef Gandhi, R., Halldórsson, M. M., Kortsarz, G., & Shachnai, H. (2008). Improved bounds for scheduling conflicting jobs with minsum criteria. ACM Transactions on Algorithms, 4(1), 11:1–11:20.CrossRef
go back to reference Gandhi, R., & Mestre, J. (2009). Combinatorial algorithms for data migration to minimize average completion time. Algorithmica, 54(1), 54–71.CrossRef Gandhi, R., & Mestre, J. (2009). Combinatorial algorithms for data migration to minimize average completion time. Algorithmica, 54(1), 54–71.CrossRef
go back to reference Halldórsson, M. M., Kortsarz, G., & Sviridenko, M. (2011). Sum edge coloring of multigraphs via configuration LP. ACM Transactions on Algorithms, 7(2), 22:1–22:21.CrossRef Halldórsson, M. M., Kortsarz, G., & Sviridenko, M. (2011). Sum edge coloring of multigraphs via configuration LP. ACM Transactions on Algorithms, 7(2), 22:1–22:21.CrossRef
go back to reference Harris, D.G., & Srinivasan, A. (2013). Constraint satisfaction, packet routing, and the lovasz local lemma. In Symposium on theory of computing conference, STOC’13, Palo Alto, CA, USA, June 1–4, 2013 (pp. 685–694). Harris, D.G., & Srinivasan, A. (2013). Constraint satisfaction, packet routing, and the lovasz local lemma. In Symposium on theory of computing conference, STOC’13, Palo Alto, CA, USA, June 1–4, 2013 (pp. 685–694).
go back to reference Im, S., & Moseley, B. (2015). Scheduling in bandwidth constrained tree networks. In Proceedings of the 27th ACM on symposium on parallelism in algorithms and architectures, SPAA 2015, Portland, OR, USA, June 13–15, 2015 (pp. 171–180). Im, S., & Moseley, B. (2015). Scheduling in bandwidth constrained tree networks. In Proceedings of the 27th ACM on symposium on parallelism in algorithms and architectures, SPAA 2015, Portland, OR, USA, June 13–15, 2015 (pp. 171–180).
go back to reference Kowalski, D. R., Nussbaum, E., Segal, M., & Milyeykovski, V. (2014). Scheduling problems in transportation networks of line topology. Optimization Letters, 8(2), 777–799.CrossRef Kowalski, D. R., Nussbaum, E., Segal, M., & Milyeykovski, V. (2014). Scheduling problems in transportation networks of line topology. Optimization Letters, 8(2), 777–799.CrossRef
go back to reference Kowalski, D. R., Nutov, Z., & Segal, M. (2012). Scheduling of vehicles in transportation networks. In Communication technologies for vehicles—4th international workshop, Nets4Cars/Nets4Trains 2012, Vilnius, Lithuania, April 25–27, 2012. Proceedings (pp. 124–136). Kowalski, D. R., Nutov, Z., & Segal, M. (2012). Scheduling of vehicles in transportation networks. In Communication technologies for vehicles—4th international workshop, Nets4Cars/Nets4Trains 2012, Vilnius, Lithuania, April 25–27, 2012. Proceedings (pp. 124–136).
go back to reference Lau, L.-C., Ravi, R., & Singh, M. (2011). Iterative methods in combinatorial optimization (1st ed.). New York, NY: Cambridge University Press.CrossRef Lau, L.-C., Ravi, R., & Singh, M. (2011). Iterative methods in combinatorial optimization (1st ed.). New York, NY: Cambridge University Press.CrossRef
go back to reference Leighton, F. T., Maggs, B. M., & Rao, S. (1994). Packet routing and job-shop scheduling in O(congestion + dilation) steps. Combinatorica, 14(2), 167–186.CrossRef Leighton, F. T., Maggs, B. M., & Rao, S. (1994). Packet routing and job-shop scheduling in O(congestion + dilation) steps. Combinatorica, 14(2), 167–186.CrossRef
go back to reference Leighton, F. T., Maggs, B. M., & Richa, A. W. (1999). Fast algorithms for finding O(congestion + dilation) packet routing schedules. Combinatorica, 19(3), 375–401.CrossRef Leighton, F. T., Maggs, B. M., & Richa, A. W. (1999). Fast algorithms for finding O(congestion + dilation) packet routing schedules. Combinatorica, 19(3), 375–401.CrossRef
go back to reference Leung, J. Y.-T., Tam, T. W., & Young, G. H. (1996). On-line routing of real-time messages. Journal of Parallel and Distributed Computing, 34(2), 211–217.CrossRef Leung, J. Y.-T., Tam, T. W., & Young, G. H. (1996). On-line routing of real-time messages. Journal of Parallel and Distributed Computing, 34(2), 211–217.CrossRef
go back to reference Li, W., Queyranne, M., Sviridenko, M., & Yuan, J. (2006). Approximation algorithms for shop scheduling problems with minsum objective: A correction. Journal of Scheduling, 9(6), 569–570.CrossRef Li, W., Queyranne, M., Sviridenko, M., & Yuan, J. (2006). Approximation algorithms for shop scheduling problems with minsum objective: A correction. Journal of Scheduling, 9(6), 569–570.CrossRef
go back to reference Mastrolilli, M., & Svensson, O. (2011). Hardness of approximating flow and job shop scheduling problems. Journal of the ACM, 58(5), 20:1–20:32.CrossRef Mastrolilli, M., & Svensson, O. (2011). Hardness of approximating flow and job shop scheduling problems. Journal of the ACM, 58(5), 20:1–20:32.CrossRef
go back to reference Peis, B., Skutella, M., & Wiese, A. (2009). Packet routing: Complexity and algorithms. In 7th international workshop on approximation and online algorithms, WAOA 2009, Copenhagen, Denmark, September 10–11, 2009. Revised papers (pp. 217–228). Peis, B., Skutella, M., & Wiese, A. (2009). Packet routing: Complexity and algorithms. In 7th international workshop on approximation and online algorithms, WAOA 2009, Copenhagen, Denmark, September 10–11, 2009. Revised papers (pp. 217–228).
go back to reference Peis, B., Skutella,, M., & Wiese, A. (2010). Packet routing on the grid. In LATIN 2010: Theoretical informatics, 9th Latin American symposium, Oaxaca, Mexico, April 19–23, 2010. Proceedings (pp. 120–130). Peis, B., Skutella,, M., & Wiese, A. (2010). Packet routing on the grid. In LATIN 2010: Theoretical informatics, 9th Latin American symposium, Oaxaca, Mexico, April 19–23, 2010. Proceedings (pp. 120–130).
go back to reference Petersen, J. (1891). Die theorie der regul aren graphs. Acta Mathematica, 15, 193–220.CrossRef Petersen, J. (1891). Die theorie der regul aren graphs. Acta Mathematica, 15, 193–220.CrossRef
go back to reference Queyranne, M., & Sviridenko, M. (2002). Approximation algorithms for shop scheduling problems with minsum objective. Journal of Scheduling, 5(4), 287–305.CrossRef Queyranne, M., & Sviridenko, M. (2002). Approximation algorithms for shop scheduling problems with minsum objective. Journal of Scheduling, 5(4), 287–305.CrossRef
go back to reference Shakhlevich, N., Hoogeveen, H., & Pinedo, M. (1998). Minimizing total weighted completion time in a proportionate flow shop. Journal of Scheduling, 1(3), 157–168.CrossRef Shakhlevich, N., Hoogeveen, H., & Pinedo, M. (1998). Minimizing total weighted completion time in a proportionate flow shop. Journal of Scheduling, 1(3), 157–168.CrossRef
go back to reference Shepherd, F. B., & Vetta, A. (2002). The demand matching problem. In Integer programming and combinatorial optimization: 9th international IPCO conference, Cambridge, MA, USA, May 27–29, 2002, Proceedings (pp. 457–474). Shepherd, F. B., & Vetta, A. (2002). The demand matching problem. In Integer programming and combinatorial optimization: 9th international IPCO conference, Cambridge, MA, USA, May 27–29, 2002, Proceedings (pp. 457–474).
go back to reference Shmoys, D. B., Stein, C., & Wein, J. (1994). Improved approximation algorithms for shop scheduling problems. SIAM Journal on Computing, 23(3), 617–632.CrossRef Shmoys, D. B., Stein, C., & Wein, J. (1994). Improved approximation algorithms for shop scheduling problems. SIAM Journal on Computing, 23(3), 617–632.CrossRef
Metadata
Title
Scheduling problems over a network of machines
Authors
Zachary Friggstad
Arnoosh Golestanian
Kamyar Khodamoradi
Christopher Martin
Mirmahdi Rahgoshay
Mohsen Rezapour
Mohammad R. Salavatipour
Yifeng Zhang
Publication date
27-11-2018
Publisher
Springer US
Published in
Journal of Scheduling / Issue 2/2019
Print ISSN: 1094-6136
Electronic ISSN: 1099-1425
DOI
https://doi.org/10.1007/s10951-018-0591-z

Other articles of this Issue 2/2019

Journal of Scheduling 2/2019 Go to the issue

Premium Partner