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Centralized content delivery infrastructure exploiting resource pools : performance models and asymptotics
textWe consider a centralized content delivery infrastructure where a large number of storage-intensive files are replicated across several collocated servers. To achieve scalable delays in file downloads under stochastic loads, we allow multiple servers to work together as a pooled resource to meet individual download requests. In such systems basic questions include: How and where to replicate files? How significant are the gains of resource pooling over policies which use single server per request? What are the tradeoffs among conflicting metrics such as delays, reliability and recovery costs, and power? How robust is performance to heterogeneity and choice of fairness criterion? In this thesis we provide a simple performance model for large systems towards addressing these basic questions. For large systems where the overall system load is proportional to the number of servers, we establish scaling laws among delays, system load, number of file replicas, demand heterogeneity, power, and network capacity.Electrical and Computer Engineerin
Approximating multiple class queueing models with loss models
Multiple class queueing models arise in situations where some flexibility is sought through pooling of demands for different services. Earlier research has shown that most of the benefits of flexibility can be obtained with only a small proportion of cross-trained operators. Predicting the performance of a system with different types of demands and operator pools with different skills is very difficult. We present an approximation method that is based on equivalent loss systems. We successively develop approximations for the waiting probability, The average waiting time and the service level. Our approximations are validated using a series of simulations. Along the way we present some interesting insights into some similarities between queueing systems and equivalent loss systems that have to our knowledge never been reported in the literature.
Routing and Staffing when Servers are Strategic
Traditionally, research focusing on the design of routing and staffing
policies for service systems has modeled servers as having fixed (possibly
heterogeneous) service rates. However, service systems are generally staffed by
people. Furthermore, people respond to workload incentives; that is, how hard a
person works can depend both on how much work there is, and how the work is
divided between the people responsible for it. In a service system, the routing
and staffing policies control such workload incentives; and so the rate servers
work will be impacted by the system's routing and staffing policies. This
observation has consequences when modeling service system performance, and our
objective is to investigate those consequences.
We do this in the context of the M/M/N queue, which is the canonical model
for large service systems. First, we present a model for "strategic" servers
that choose their service rate in order to maximize a trade-off between an
"effort cost", which captures the idea that servers exert more effort when
working at a faster rate, and a "value of idleness", which assumes that servers
value having idle time. Next, we characterize the symmetric Nash equilibrium
service rate under any routing policy that routes based on the server idle
time. We find that the system must operate in a quality-driven regime, in which
servers have idle time, in order for an equilibrium to exist, which implies
that the staffing must have a first-order term that strictly exceeds that of
the common square-root staffing policy. Then, within the class of policies that
admit an equilibrium, we (asymptotically) solve the problem of minimizing the
total cost, when there are linear staffing costs and linear waiting costs.
Finally, we end by exploring the question of whether routing policies that are
based on the service rate, instead of the server idle time, can improve system
performance.Comment: First submitted for journal publication in 2014; accepted for
publication in Operations Research in 2016. Presented in select conferences
throughout 201
Essays on Service Operations Management
This dissertation studies three different problems service firms can face. The first chapter looks at the optimal way to price reservations and services when customers make reservations in advance, while they are uncertain about the future value of service, to avoid waiting on the day of service. We show that charging customers the full price as non-refundable deposit when they make reservations and charging zero for service when they show up to claim their reservations is optimal for the firm. When the firm faces very large potential market, then it is better for the firm to not take reservations and accept only walk-ins. The second chapter looks at a problem of how to mitigate worker demotivations due to fairness concerns, when workers have intrinsic difference in quality, and higher quality server tends to be overcrowded by customers willing to receive higher quality service. We suggest distributing workload fairly between workers and compensating workers per workload as potential remedies and show which remedy works well under what operational conditions. We show that compensating workers per customer they serve results in high customer expected utility and expected quality. However, when customers also care about fairness and dislike receiving inferior service compared to other customers, then there does not exist a single remedy that results in both high customer expected utilization and high expected quality. In the third chapter, we study how a service firm should choose its advertising strategy when the service quality is not perfectly known to the customers. We model customers\u27 learning process using a Markov chain, and show that when customers do not perfectly learn the quality of service from advertisements, then the firm is better off by advertising actively when customers\u27 initial belief about service quality is low. Oppositely, when customers initially believe the service quality to be high, then it is better for the firm to stay silent and not use advertisement to signal its quality. In all three chapters, we use game theory to model the interactions among the participants of the problem and find the equilibrium outcomes
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