Large-scale heterogeneous service systems with general packing constraints
Alexander Stolyar

TL;DR
This paper analyzes large-scale heterogeneous service systems with complex packing constraints, proving asymptotic optimality of a greedy algorithm for infinite-server models and demonstrating stability and zero blocking probability in finite-server systems.
Contribution
It introduces and proves the optimality of the GRAND algorithm for infinite-server systems and extends it to finite-server systems, establishing stability and potential zero blocking in large-scale regimes.
Findings
Grand algorithm is asymptotically optimal for infinite-server models.
Existence and stability of equilibrium in finite-server models with no blocking.
Potential for vanishing blocking probability in large-scale finite-server systems.
Abstract
A service system with multiple types of customers, arriving according to Poisson processes, is considered. The system is heterogeneous in that the servers also can be of multiple types. Each customer has an independent exponentially distributed service time, with the mean determined by its type. Multiple customers (possibly of different types) can be placed for service into one server, subject to "packing" constraints, which depend on the server type. Service times of different customers are independent, even if served simultaneously by the same server. The large-scale asymptotic regime is considered such that the customer arrival rates grow to infinity. We consider two variants of the model. For the {\em infinite-server} model, we prove asymptotic optimality of the {\em Greedy Random} (GRAND) algorithm in the sense of minimizing the weighted (by type) number of occupied servers in…
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