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Services providers, such as public healthcare systems and government agencies, are under tremendous pressure to reduce costs and improve service quality. Scheduling is an important managerial component which has considerable impact on both the costs and quality of services. Service providers need customers' availability information to improve resource utilization. On the other hand, customers may be of "two minds" about communicating their private information. While communicating certain amount of availability might be necessary in order to obtain preferred schedules, too much communication place a potential cost due to privacy loss. In this paper, we present a bidding-based mechanism which aims at generating high quality schedules and, at the same time, protecting customers' privacy. We show that, under the proposed bidding procedure, myopic bidding is the dominant strategy for customers. We also evaluate the privacy and efficiency performance of the proposed mechanism through a computational study.

Compared with traditional manufacturing scheduling, service process scheduling poses additional challenges attributable to the significant customer involvement in service processes. In services, there are typically no inventoried products, which make the service provider's capacity more sensitive to dynamic changes. Service process scheduling objectives are also more complicated due to the consideration of customer preferences, customer waiting costs and human resource costs. After describing the Unified Services Theory and analysing its scheduling implications, this paper reviews the research literature on service process scheduling system design with a particular emphasis on agent-based approaches. Major issues in agent-based service process scheduling systems design are discussed and research opportunities are identified. The survey of the literature reveals that despite of many domainspecific designs in agent-based service process scheduling, there is a lack of general problem formulations, classifications, solution frameworks, and test beds. Constructing these general models for service process scheduling system design will facilitate the collaboration of researchers in this area and guide the effective development of integrated service process scheduling systems.

Minimizing energy consumption in datacenters requires virtual machine (VM) scheduling methods that effectively deal with system heterogeneities. Existing heterogeneity-aware VM scheduling mechanisms focus on capacity-level heterogeneities while capability-level heterogeneities are largely ignored. In this paper, we propose an integer programming formulation of the VM scheduling model that considers capabilitylevel heterogeneities. Given the NP-hardness of the model, we present a heuristic-based capability-aware VM scheduling algorithm to obtain energy-efficient VM scheduling solutions. Simulation results show that the proposed heuristic algorithm generates near optimal scheduling solutions while significantly reducing computation times.