Integrated architectures consolidate multiple functions on a shared electronic control unit and are in combination with multicore processors well suited to implement complex functionality with reduced size, weight, and power consumption. The major challenges are robust encapsulation (to prevent that the integrated systems corrupt each other) and resource management (to ensure that each system receives sufficient resources). Hypervisor-based virtualization is a promising integration architecture for complex embedded real-time systems. It refers to the division of the hardware resources into multiple isolated execution environments (virtual machines), each hosting an operating system and application tasks. This thesis addresses the hypervisors management of the resource computation time. State of the art approaches assign exclusive processor cores or fixed processor shares to each virtual machine. For applications with a computation time demand that varies at run-time, such static solutions result in a low utilization, since the pessimistic worst-case demand has to be reserved at all times, but is often not needed. Therefore, adaptability is desired in order to utilize the shared processor efficiently, but without losing the real-time capability as a prerequisite for the integration. The first contribution is an algorithm for the partitioning of virtual machines to homogeneous cores. The second contribution is a virtual machine scheduling architecture that combines real-time guarantees with an adaptive management of the computing power in case of mode changes and execution time variations. The third contribution is a technique for real-time virtual machine migration. Together, these contributions enable the integration of independently developed systems on top of a hypervisor. Adaptive measures are taken to follow the varying demand effectively and to protect critical systems. A prototype demonstrates the feasibility.