Recently Intelligent Transport Systems (ITS) have acted as an efficient solution for improving the operational performance of traffic systems, reducing traffic congestion, and increasing safety for the travelers. But due to the inclusion of different distributed transport departments, heterogeneous devices, and diverse data sources, the architecture of ITS has become complex and costly. For an efficient and cost-effective architecture, ITS need to have easy and effective mechanisms for interacting among different transport subsystems. Recent technologies such as -service-oriented architectures (SOA), cloud or grid computing, provide a way of building a reliable and loosely-coupled distributed system. This paper surveys the promising solutions for distributed architectures of ITS and discusses opportunities and challenges in the context of ITS for public transport.

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Energy efficient virtual machine (VM) consolidation in modern data centers is typically optimized using methods such as Mixed Integer Programming, which typically require precise input to the model. Unfortunately, many parameters are uncertain or very difficult to predict precisely in the real world. As a consequence, a once calculated solution may be highly infeasible in practice. In this paper, we use methods from robust optimization theory in order to quantify the impact of uncertainty in modern data centers. We study the impact of different parameter uncertainties on the energy efficiency and overbooking ratios such as e.g. VM resource demands, migration related overhead or the power consumption model of the servers used. We also show that setting aside additional resource to cope with uncertainty of workload influences the overbooking ration of the servers and the energy consumption. We show that, by using our model, Cloud operators can calculate a more robust migration schedule leading to higher total energy consumption. A more risky operator may well choose a more opportunistic schedule leading to lower energy consumption but also higher risk of SLA violation.

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