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We present an intelligent interface system which includes a new gesture-based wearable input device, called iThrow, as a main user interface for mobile devices, and an infrastructure helping users be aware of and make a use of various public devices in user-friendly manners. In this kind of intelligent interface system, selecting an object among multiple ones is one of the fundamental functions because it is a pre-cursor to all other subsequent actions. We propose a new selection algorithm which improves selection speed by adaptively resizing the objects' angular widths. Results show that the proposed algorithm outperforms the ray-based selection technique in selection speed about 62.6%.

In this article, we propose two techniques that aim to minimize the scheduling latency of high-priority interrupt-driven tasks, named the Interrupt Handler Migration (IHM) and Direct Interrupt Scheduling (DIS). The IHM allows the interrupt handler to be migrated from the interrupt handler thread to the corresponding target process so that additional context switch can be avoided and the cache hit ratio with respect to the data generated by the interrupt handler can be improved. In addition, the DIS allows the shortest path reserved for urgent interrupt-process pairs to be laid between the interrupt arrival and target process by dividing a series of interrupt-driven operations into nondeferrable and deferrable operations. Both the IHM and DIS can be combined in a natural way and can operate concurrently. These techniques can be applied to all kinds of interrupt handlers with no modification to them. The proposed techniques not only reduce the scheduling latency, but also resolve the interrupt-driven priority inversion problem. We implemented a prototype in the Linux 2.6.19 kernel after adding real-time patches. Experimental results show that the scheduling latency is significantly reduced by up to 84.2% when both techniques are applied together. When the Linux OS runs on an ARM-based embedded CPU running at 200MHz, the scheduling latency can become as low as 30 μ s, which is much closer to the hardware-specific limitations. By lowering the scheduling latency, the limited CPU cycles can be consumed more for user-level processes and less for system-level tasks, such as interrupt handling and scheduling.

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