Light trail architecture is attracting attention as a new optical wavelength-division multiplexing network architecture that can be built with currently available devices and can achieve bandwidth allocation with granularity finer than a wavelength. Because a light trail is a shared medium, we need a medium access control (MAC) protocol to prevent collisions. Although MAC protocols using token passing can prevent collisions, the bandwidths of links that are located upstream of the token holding node are kept idle. We first propose a dynamic light trail splitting method for increasing throughput of a light trail by using such idle bandwidths. Our method splits a trail into upstream and downstream trails at the token holding node, and independent data transmission on the two trails are permitted. As a result, we expect that the split trail architecture will achieve higher throughput than the original non-split trail architecture. The degree of performance improvement with the split trail architecture depends on how appropriately we determine the upstream and downstream token holding times of every transmission node. Thus, we formulate a problem in which we optimize the token holding times to accommodate requested traffic volume as a linear programming problem. We then derive the throughput of the split trail architecture by solving the problem using the NUOPT solver and investigate the degree of improvement over the original architecture. In addition, we evaluate the end-to-end delay of the split trail architecture by simulation. According to numerical examples, the split trail architecture achieves 1) almost the same throughput as the original one for the worst-case traffic pattern where every transmission node sends data to the terminating node of the trail only, 2) about 1.6 times higher throughput for a uniform traffic pattern where every node pair requests the same traffic volume and an extremely unbalanced traffic pattern where only a few node pairs request huge traffic volume, 3) about 1.9 time higher throughput for the split trail architecture's good-case traffic pattern where every transmission node sends data to its adjacent downstream node only, and 4) the end-to-end delay enough to satisfy any application's QoS requirement according to ITU-T Recommendation Y.1541.

A lot of vision systems have been embedded in devices around us, like mobile phones, vehicles and UAVs. Many of them still need interactive operations of human users. However, specifying accurate object information could be a challenging task due to video jitters caused by camera shakes and target motions. In this paper, we first collect practical hand drawn bounding boxes on real-life videos which are captured by hand-held cameras and UAV-based cameras. We give a deep look into human-computer interactive operations on unstable images. The collected data shows that human input suffers heavy deviations which are harmful to interaction accuracy. To achieve robust interactions on unstable platforms, we propose a target-focused video stabilization method which utilizes a proposal-based object detector and a tracking-based motion estimation component. This method starts with a single manual click and outputs stabilized video stream in which the specified target stays almost stationary. Our method removes not only camera jitters but also target motions simultaneously, therefore offering an comfortable environment for users to do further interactive operations. The experiments demonstrate that the proposed method effectively eliminates image vibrations and significantly increases human input accuracy.