Strong approximations for time-dependent queues
Mathematics of Operations Research
Modelling the performance of distributed admission control for adaptive applications
ACM SIGMETRICS Performance Evaluation Review
Queueing Systems: Theory and Applications
Diffusion Approximation in Overloaded Switching Queueing Models
Queueing Systems: Theory and Applications
Predictive routing to enhance QoS for stream-based flows sharing excess bandwidth
Computer Networks: The International Journal of Computer and Telecommunications Networking - Small and home networks
Queueing Systems: Theory and Applications
Proceedings of the 35th conference on Winter simulation: driving innovation
Variational optimization for call center staffing
Proceedings of the 2005 conference on Diversity in computing
Queueing Systems: Theory and Applications
Integrating streaming and file-transfer Internet traffic: fluid and diffusion approximations
Queueing Systems: Theory and Applications
Queueing Systems: Theory and Applications
A time-varying call center design via lagrangian mechanics
Probability in the Engineering and Informational Sciences
Pointwise Stationary Fluid Models for Stochastic Processing Networks
Manufacturing & Service Operations Management
Multiserver Loss Systems with Subscribers
Mathematics of Operations Research
Controlled jump Markov processes with local transitions and their fluid approximation
WSEAS Transactions on Systems and Control
Two-parameter heavy-traffic limits for infinite-server queues
Queueing Systems: Theory and Applications
Control of systems with flexible multi-server pools: a shadow routing approach
Queueing Systems: Theory and Applications
The cμ/θ Rule for Many-Server Queues with Abandonment
Operations Research
Large-time asymptotics for the Gt/Mt/st+GIt many-server fluid queue with abandonment
Queueing Systems: Theory and Applications
Epidemic-based information dissemination in wireless mobile sensor networks
IEEE/ACM Transactions on Networking (TON)
State Space Collapse in Many-Server Diffusion Limits of Parallel Server Systems
Mathematics of Operations Research
Poster: skewness variance approximation for dynamic rate MultiServer queues with abandonment
ACM SIGMETRICS Performance Evaluation Review - Special Issue on IFIP PERFORMANCE 2011- 29th International Symposium on Computer Performance, Modeling, Measurement and Evaluation
A Network of Time-Varying Many-Server Fluid Queues with Customer Abandonment
Operations Research
Predicting departure times in multi-stage queueing systems
Computers and Operations Research
Decomposition approximations for time-dependent Markovian queueing networks
Operations Research Letters
Estimating file-spread in delay tolerant networks under two-hop routing
IFIP'12 Proceedings of the 11th international IFIP TC 6 conference on Networking - Volume Part II
Separation of timescales in a two-layered network
Proceedings of the 24th International Teletraffic Congress
Critically Loaded Time-Varying Multiserver Queues: Computational Challenges and Approximations
INFORMS Journal on Computing
Gaussian skewness approximation for dynamic rate multi-server queues with abandonment
Queueing Systems: Theory and Applications
Data-stories about (im)patient customers in tele-queues
Queueing Systems: Theory and Applications
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Inspired by service systems such as telephone call centers, we develop limit theorems for a large class of stochastic service network models. They are a special family of nonstationary Markov processes where parameters like arrival and service rates, routing topologies for the network, and the number of servers at a given node are all functions of time as well as the current state of the system. Included in our modeling framework are networks of M_t/M_t/n_t queues with abandonment and retrials. The asymptotic limiting regime that we explore for these networks has a natural interpretation of scaling up the number of servers in response to a similar scaling up of the arrival rate for the customers. The individual service rates, however, are not scaled. We employ the theory of strong approximations to obtain functional strong laws of large numbers and functional central limit theorems for these networks. This gives us a tractable set of network fluid and diffusion approximations. A common theme for service network models with features like many servers, priorities, or abandonment is “non-smooth” state dependence that has not been covered systematically by previous work. We prove our central limit theorems in the presence of this non-smoothness by using a new notion of derivative.