Queueing Systems

, Volume 72, Issue 3–4, pp 193–218 | Cite as

On distributed scheduling with heterogeneously delayed network-state information

  • Akula Aneesh Reddy
  • Siddhartha Banerjee
  • Aditya Gopalan
  • Sanjay Shakkottai
  • Lei Ying


We study the problem of distributed scheduling in wireless networks, where each node makes individual scheduling decisions based on heterogeneously delayed network state information (NSI). This leads to inconsistency in the views of the network across nodes, which, coupled with interference, makes it challenging to schedule for high throughputs.

We characterize the network throughput region for this setup, and develop optimal scheduling policies to achieve the same. Our scheduling policies have a threshold-based structure and, moreover, require the nodes to use only the “smallest critical subset” of the available delayed NSI to make decisions. In addition, using Markov chain mixing techniques, we quantify the impact of delayed NSI on the throughput region. This not only highlights the value of extra NSI for scheduling, but also characterizes the loss in throughput incurred by lower complexity scheduling policies which use homogeneously delayed NSI.


Wireless networks Scheduling algorithms Delayed information 

Mathematics Subject Classification




This work was partially supported by NSF grants CNS-0721380, CNS-0831756, CNS-1017549, the DARPA ITMANET program, and DTRA grant HDTRA1-09-1-0055. We thank the anonymous reviewers for their valuable comments and suggestions.


  1. 1.
    Reddy, A., Banerjee, S., Gopalan, A., Shakkottai, S., Ying, L.: Wireless scheduling with heterogeneously delayed network-state information. In: Proc. Ann. Allerton Conf. Communication, Control and Computing (2010) Google Scholar
  2. 2.
    Tassiulas, L., Ephremides, A.: Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks. IEEE Trans. Autom. Control, 1936–1948 (1992) Google Scholar
  3. 3.
    Andrews, M., Kumaran, K., Ramanan, K., Stolyar, A.L., Vijayakumar, R., Whiting, P.: CDMA data QoS scheduling on the forward link with variable channel conditions. Bell Labs Tech. Memo (2000) Google Scholar
  4. 4.
    Tassiulas, L., Ephremides, A.: Dynamic server allocation to parallel queues with randomly varying connectivity. IEEE Trans. Inf. Theory 39, 466–478 (1993) CrossRefGoogle Scholar
  5. 5.
    Shakkottai, S., Stolyar, A.: Scheduling for multiple flows sharing a time-varying channel: the exponential rule. Ann. Math. Stat. 207, 185–202 (2001) Google Scholar
  6. 6.
    Stolyar, A.: Maximizing queueing network utility subject to stability: greedy primal–dual algorithm. Queueing Syst. 50, 401–457 (2005) CrossRefGoogle Scholar
  7. 7.
    Eryilmaz, A., Srikant, R., Perkins, J.: Stable scheduling policies for fading wireless channels. IEEE/ACM Trans. Netw. 13, 411–424 (2005) CrossRefGoogle Scholar
  8. 8.
    Neely, M.J., Modiano, E., Rohrs, C.E.: Power and server allocation in a multi-beam satellite with time varying channels. Proc. IEEE INFOCOM 3, 1451–1460 (2002) Google Scholar
  9. 9.
    Neely, M.J., Modiano, E., Li, C.: Fairness and optimal stochastic control for heterogeneous networks. Proc. IEEE INFOCOM 3, 1723–1734 (2005) Google Scholar
  10. 10.
    Lin, X., Rasool, S.: Constant-time distributed scheduling policies for ad HocWireless networks. In: Proc. Conf. on Decision and Control (2006) Google Scholar
  11. 11.
    Joo, C., Shroff, N.: Performance of random access scheduling schemes in multihop wireless networks. Proc. IEEE INFOCOM (2007) Google Scholar
  12. 12.
    Rajagopalan, S., Shin, J., Shah, D.: Network adiabatic theorem: an efficient randomized protocol for contention resolution. In: Proc. Ann. ACM SIGMETRICS Conf. (2009) Google Scholar
  13. 13.
    Jiang, L., Walrand, J.: A distributed CSMA algorithm for throughput and utility maximization in wireless networks. In: Proc. Ann. Allerton Conf. Communication, Control and Computing (2008) Google Scholar
  14. 14.
    Liu, J., Yi, Y., Proutiere, A., Chiang, M., Poor, H.V.: Maximizing utility via random access without message passing. Microsoft Research Technical Report (2008) Google Scholar
  15. 15.
    Rajagopalan, S., Shah, D., Shin, J.: Network adiabatic theorem: an efficient randomized protocol for contention resolution. In: Proc. Ann. ACM SIGMETRICS Conf., pp. 133–144 (2009) Google Scholar
  16. 16.
    Ni, J., Tan, B., Srikant, R.: Q-CSMA: Queue-length based CSMA/CA algorithms for achieving maximum throughput and low delay in wireless networks. In: Proceedings of IEEE INFOCOM Mini-Conference (2010) Google Scholar
  17. 17.
    Ahmad, S., Mingyan, L., Javidi, T., Zhao, Q., Krishnamachari, B.: Optimality of myopic sensing in multichannel opportunistic access. IEEE Trans. Inf. Theory 55, 4040–4050 (2009) CrossRefGoogle Scholar
  18. 18.
    Guha, S., Munagala, K., Sarkar, S.: Performance guarantees through partial information based control in multichannel wireless networks (2006). http://www.seas.upenn.edu/~swati/report.pdf
  19. 19.
    Chang, N., Liu, M.: Optimal channel probing and transmission scheduling for opportunistic spectrum access. In: ACM Int. Conf. on Mobile Computing and Networking (MobiCom) (2007) Google Scholar
  20. 20.
    Gopalan, A., Caramanis, C., Shakkottai, S.: On wireless scheduling with partial channel state information. IEEE Trans. Inf. Theory (2011) Google Scholar
  21. 21.
    Chaporkar, P., Proutiere, A., Asnani, H., Karandikar, A.: Scheduling with limited information in wireless systems. In: ACM Mobihoc, pp. 75–84 (2009) CrossRefGoogle Scholar
  22. 22.
    Pantelidou, A., Ephremides, A., Tits, A.: Joint scheduling and routing for ad-hoc networks under channel state uncertainty. In: Intl. Symposium on Modeling and Optimization in Mobile, Ad-Hoc and Wireless Networks (WiOpt), pp. 1–8 (2007) CrossRefGoogle Scholar
  23. 23.
    Kar, K., Luo, X., Sarkar, S.: Throughput-optimal scheduling in multichannel access point networks under infrequent channel measurements. In: Proceedings of IEEE INFOCOM (2007) Google Scholar
  24. 24.
    Chen, J., Berry, R.A., Honig, M.L.: Limited feedback schemes for downlink OFDMA based on sub-channel groups. IEEE J. Sel. Areas Commun. 26, 1451–1461 (2008) CrossRefGoogle Scholar
  25. 25.
    Ouyang, M., Ying, L.: On scheduling in multi-channel wireless downlink networks with limited feedback. In: Proc. Ann. Allerton Conf. Communication, Control and Computing, pp. 455–469 (2009) Google Scholar
  26. 26.
    Ouyang, M., Ying, L.: On optimal feedback allocation in multichannel wireless downlinks. In: ACM Mobihoc (2010) Google Scholar
  27. 27.
    Ying, L., Shakkottai, S.: On throughput optimality with delayed network-state information. Technical report (2008) Google Scholar
  28. 28.
    Ying, L., Shakkottai, S.: Scheduling in mobile ad hoc networks with topology and channel-state uncertainty. In: Proc. IEEE INFOCOM, pp. 2347–2355 (2009) Google Scholar
  29. 29.
    Billingsley, P.: Probability and Measure. Wiley, New York (1994) Google Scholar
  30. 30.
    Asmussen, S.: Applied Probability and Queues. Springer, New York (2003) Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Akula Aneesh Reddy
    • 1
  • Siddhartha Banerjee
    • 1
  • Aditya Gopalan
    • 1
  • Sanjay Shakkottai
    • 1
  • Lei Ying
    • 2
  1. 1.The University of Texas at AustinAustinUSA
  2. 2.Iowa State UniversityAmesUSA

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