Recent developments in Big Data frameworks are moving towards reservation based approaches as a mean to manage the increasingly complex mix of computations, whereas preemption techniques are employed to meet strict jobs deadlines. Within this work we propose and evaluate a new planning algorithm in the context of reservation based scheduling. Our approach is able to achieve high cluster utilization while minimizing the need for preemption that causes system overheads and planning mispredictions.

Mobile devices, due to their wide distribution and to their increasing smartness and availability of computational power, can become the interaction point between users and their surrounding environments. However, current mobile devices OSes lack of the ability to anticipate and overcome internal and external changes. Integrating mechanisms of self-awareness and self-adaptability in nowadays smartphones is an attractive perspective to match with these requirements. Moreover, adaptive behaviors can enhance the management by the mobile device itself, of the available resources at its best, e.g., the battery life. This paper envisions various situations in which a self-aware mobile device can interact with the surrounding environment and support the user in performing everyday actions. A prototype of such an adaptive device, called morphone.os and based on the Android OS, has been designed and implemented to verify the reaction of the device in different situations providing convincing and promising preliminary results.