Spatiotemporal super-resolution (SR) aims to upscale both the spatial and temporal dimensions of input videos, and produces videos with higher frame resolutions and rates. It involves two essential sub-tasks: spatial SR and temporal SR. We design a two-stream network for spatiotemporal SR in this work. One stream contains a temporal SR module followed by a spatial SR module, while the other stream has the same two modules in the reverse order. Based on the interchangeability of performing the two sub-tasks, the two network streams are supposed to produce consistent spatiotemporal SR results. Thus, we present a cross-stream consistency to enforce the similarity between the outputs of the two streams. In this way, the training of the two streams is correlated, which allows the two SR modules to share their supervisory signals and improve each other. In addition, the proposed cross-stream consistency does not consume labeled training data and can guide network training in an unsupervised manner. We leverage this property to carry out semi-supervised spatiotemporal SR. It turns out that our method makes the most of training data, and can derive an effective model with few high-resolution and high-frame-rate videos, achieving the state-of-the-art performance. The source code of this work is available at https://hankweb.github.io/STSRwithCrossTask/.

In recent years, flash memory has been widely used in embedded systems, portable devices, and high-performance storage products due to its nonvolatility, shock resistance, low power consumption, and high performance natures. To reduce the product cost, multi-level-cell (MLC) flash memory has been proposed; compared with the traditional single-level-cell (SLC) flash memory that only stores one bit of data per cell, each MLC cell can store two or more bits of data. Thus MLC can achieve a larger capacity and reduce the cost per unit. However, MLC also suffers from the degradation in both performance and reliability. In this paper, we try to enhance the reliability and reduce the product cost of flash-memory-based solid-state drive (SSD) from a totally different perspective. We propose the half-level-cell (HLC) scheme to manage and reuse the worn-out space in SSD; through our management scheme, the system can treat two bad pages as a normal page without sacrificing performance and reliability. The proposed scheme is purely on software/firmware-level, thus there is no need to change the hardware. The experiment results show that the lifetime of SSD with our proposed HLC scheme can be extended to 50.56% under the Windows workload and up to 65.45% under the multimedia workload. When we apply the HLC scheme to flash-memory cache of hybrid storage systems, the response time can be improved up to 20.57%.

The increasingly high display resolution of mobile devices imposes a further burden on energy consumption. Existing schemes manage either OLED or GPU power to save energy. This paper presents the design, algorithm, and implementation of a co-managing scheme called Duet, which automatically trades off perceptual quality for energy efficiency in accordance with static and dynamic visual acuity when users interact with mobile applications. The results of experiments conducted on a commercial smartphone with popular interactive apps show that Duet saves more energy while retaining better visual quality, compared with a joint scheme that simultaneously uses dynamic pixel disabling and dynamic resolution scaling to save OLED and GPU energy in isolation.

OLED power management on mobile devices is very challenging due to the dynamic nature of human-screen interaction. This paper presents the design, algorithms, and implementation of a lightweight mobile app called ShiftMask, which allows the user to dynamically shift OLED power to the portion of interest, while dimming the remainder of the screen based on visual acuity. To adapt to the user's focus of attention, we propose efficient algorithms that consider visual fixation in static scenes, as well as changes in focus and screen scrolling. The results of experiments conducted on a commercial smartphone with popular interactive apps demonstrate that ShiftMask can achieve substantial energy savings, while preserving acceptable readability.

In recent years, multi-level cell flash memory (MLC) has been widely adopted in solid state drives (SSD's) as the major storage medium due to its lower cost and higher density, compared with single-level cell flash memory (SLC). However, MLC has reliability concerns since it has lower endurance and higher disturb failure rate. Researchers thus proposed SLC/MLC hybrid SSD to exploit the advantages of SLC and MLC by separating frequently updated data in SLC and seldom modified data in MLC. In this paper, we propose an adaptive error correction code (ECC) scheme with four ECC levels to enhance the reliability of SSD's. Different from past researches, SLC is dedicated for the management of ECC, not for the user data. Since ECC is maintained in the data area of SLC (2 KB), rather than the spare area of MLC (128 Bytes), ECC capability is no longer confined by the limited size of the spare area. With adaptive management, ECC capability for a page would be upgraded whenever the current ECC cannot guarantee its reliability. A quantitative analysis is conducted to explore the impacts of different settings. The experiment results show that the lifetime of SSD can be extended by 318 percent for the trace of OLTP applications with our adaptive ECC scheme.

Several excellent researches have been proposed to improve the performance of solid-state drives (SSDs) by exploiting I/O parallelism of multi-channel architecture. However, these researches do not fully explore the internal parallelism and do not take wear leveling into consideration. In this paper, I/O performance is further improved by interleaving requests in channel level and striping sub-requests in plane level. A wear-leveling-aware distributed garbage collector is proposed to improve SSD lifetime and reclamation efficiency. To balance the utilization of user space among all channels, data migration is performed implicitly during channel selection and explicitly during garbage collection. To the best of our knowledge, this is the first paper on the design of distributed garbage collector for multi-channel flash-memory storage system. The experimental results showed that the proposed scheme can achieve good wear leveling and improve the overall performance by 34% for the Windows workload, 56.5% for the Linux workload, 88.4% for the multimedia workload, and 9.3% for the on-line transaction processing (OLTP) workload under the two-die-two-plane architecture, compared with the related work.

Abstract In this paper, a modified time‐of‐arrival (TOA) estimation error test and a hybrid time‐of‐arrival/angle‐of‐arrival (TOA/AOA) estimation error test for identification of line of sight (LOS) base stations (BSs) are proposed. The proposed schemes aim to improve the location accuracy of wireless location systems suffering from the non‐line of sight (NLOS) propagation errors. The modified TOA‐based estimation error test is considered a straightforward approach in identifying the LOS‐BS set when the number of LOS BSs is greater than or equal to three. When both TOA and AOA metrics are available, hybrid TOA/AOA squares of normalized estimation errors are formulated by adopting the approximate maximum likelihood (AML) estimation. The proposed hybrid estimation error test scheme is capable of identifying the LOS/NLOS status of each BS, and performing location estimation in the situation where only two LOS BSs exist. Simulation results show that the proposed schemes are capable of correctly identifying the LOS BSs and improving the overall location accuracy. Copyright © 2009 John Wiley & Sons, Ltd.