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Two recent trends are major motivators for service component migration: the upcoming use of cloud-based services and the increasing number of mobile users accessing Internet-based services via wireless networks. While cloud-based services target the vision of Software as a Service, where services are ubiquitously available, mobile use leads to varying connectivity properties. In spite of temporary weak connections and even disconnections, services should remain operational. This paper investigates service component migration between the mobile client and the infrastructure-based cloud as a means to avoid service failures and improve service performance. Hereby, migration decisions are controlled by policies. To investigate component migration performance, an analytical Markov model is introduced. The proposed model uses a two-phased approach to compute the probability to finish within a deadline for a given reconfiguration policy. The model itself can be used to determine the optimal policy and to quantify the gain that is obtained via reconfiguration. Numerical results from the analytic model show the benefit of reconfigurations and the impact of different reconfigurations applied to three service types, as immediate reconfigurations are in many cases not optimal, a threshold on time before reconfiguration can take place is introduced to control reconfiguration.