Collaboration and Multitasking in Networks: Prioritization and Achievable Capacity

Published Online:https://doi.org/10.1287/mnsc.2017.2722

References

  • Bonald T, Massoulié L (2001) Impact of fairness on Internet performance. SIGMETRICS Performance Evaluation Rev. 29(1):82–91.CrossrefGoogle Scholar
  • Borst SC (1996) Polling Systems (Centrum voor Wiskunde en Informatica, Amsterdam).Google Scholar
  • Courcoubetis CA, Reiman MI (1987) Optimal control of a queueing system with simultaneous service requirements. IEEE Trans. Automatic Control 32(8):717–727.CrossrefGoogle Scholar
  • Dacre M, Glazebrook K, Niño-Mora J (1999) The achievable region approach to the optimal control of stochastic systems. J. Roy. Statist. Soc. Ser. B Statist. Methodol. 61(4):747–791.CrossrefGoogle Scholar
  • Dai JG, Lin W (2005) Maximum pressure policies in stochastic processing networks. Oper. Res. 53(2):197–218.LinkGoogle Scholar
  • Dobson G, Lee H, Sainathan A, Tilson V (2012) A queueing model to evaluate the impact of patient “batching” on throughput and flow time in a medical teaching facility. Manufacturing Service Oper. Management 14(4):584–599.LinkGoogle Scholar
  • Gurvich I, Van Mieghem JA (2015) Collaboration and multitasking in networks: Architectures, bottlenecks, and capacity. Manufacturing Service Oper. Management 17(1):16–33.LinkGoogle Scholar
  • Gurvich I, Van Mieghem JA, Wang L, O’Leary KJ, Soulakis ND (2016) The effect of digital and physical teams on individual productivity: A study of hospitalists. Working paper, Northwestern University, Evanston.Google Scholar
  • Harrison JM (2000) Brownian models of open processing networks: Canonical representation of workload. Ann. Appl. Probab. 10(1):75–103.CrossrefGoogle Scholar
  • Harrison JM, López MJ (1999) Heavy traffic resource pooling in parallel-server systems. Queueing Systems 33(4):339–368.CrossrefGoogle Scholar
  • Harrison JM, Van Mieghem JA (1997) Dynamic control of Brownian networks: State space collapse and equivalent workload formulations. Ann. Appl. Probab. 7(3):747–771.CrossrefGoogle Scholar
  • Harrison JM, Mandayam CV, Shah D, Yang Y (2014) Resource sharing networks: Overview and an open problem. Stochastic Systems 4(2):524–555.LinkGoogle Scholar
  • Hopp WJ, Iravani SM, Liu F (2009) Managing white-collar work: An operations-oriented survey. Production Oper. Management 18(1):1–32.CrossrefGoogle Scholar
  • Kang WN, Williams RJ (2012) Diffusion approximation for an input-queued switch operating under a maximum weight matching policy. Stochastic Systems 2(2):277–321.LinkGoogle Scholar
  • Krishnamoorthy A, Pramod PK, Chakravarthy SR (2014) Queues with interruptions: A survey. TOP 22(1):290–320.CrossrefGoogle Scholar
  • Lan W, Olsen TL (2006) Multiproduct systems with both setup times and costs: Fluid bounds and schedules. Oper. Res. 54(3):505–522.LinkGoogle Scholar
  • Reiman M, Wein L (1998) Dynamic scheduling of a two-class queue with setups. Oper. Res. 46(4):532–547.LinkGoogle Scholar
  • Shah D, Walton N, Zhong Y (2014) Optimal queue-size scaling in switched networks. Ann. Appl. Probab. 24(6):2207–2245.CrossrefGoogle Scholar
  • Shah D, Wischik D (2012) Switched networks with maximum weight policies: Fluid approximation and multiplicative state space collapse. Ann. Appl. Probab. 22(1):70–127.CrossrefGoogle Scholar
  • Simatos F, Bouman N, Borst S (2014) Lingering issues in distributed scheduling. Queueing Systems 77(2):243–273.CrossrefGoogle Scholar
  • Stidham S Jr (2009) Optimal Design of Queueing Systems (CRC Press, Boca Raton, FL).CrossrefGoogle Scholar
  • Stolyar AL (2004) Maxweight scheduling in a generalized switch: State space collapse and workload minimization in heavy traffic. Ann. Appl. Probab. 14(1):1–53.CrossrefGoogle Scholar
  • Tassiulas L, Ephremides A (1992) Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks. IEEE Trans. Automatic Control 37(12):1936–1948.CrossrefGoogle Scholar
  • Walton N (2015) Concave switching in single-hop and multihop networks. Queueing Systems 81(2):1–35.Google Scholar
  • Wang L, Gurvich I, O’Leary KJ, Van Mieghem JA (2016) Collaboration, interruptions and setup times: Model and empirical study of hospitalist workload. Working paper, Northwestern University, Evanston, IL.Google Scholar
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