Flash memory has been widely utilized in embedded systems and consumer electronics, because of its low-power consumption, high-performance access, non-volatility, and shock resistance. A flash-memory device is different from a typical hard-disk device and requires a sophisticated management method to improve the reliable endurance and provide the efficient storage management. To improve the reliable endurance and provide the efficient storage management, the previous works have demonstrated that the identification of the frequently used data and the least recently used data is a key point. In this paper, we will propose a hotness filter of files to calculate how the files are accessed (i.e., reads and writes) intensively. The proposed filter is designed specifically to distinguish between hot and cold files by considering the characteristics of non-volatile memory systems and Android systems. In the experiments, we have implemented the hotness filter in a real Android system (e.g., Asus Nexus 7) and demonstrated that the proposed filter can correctly identify hot and cold files without significant overhead.

Function evaluation is an important arithmetic computation in many signal processing applications, such as the special function unit in modern graphics processing units (GPUs). Lookup table (LUT) usually takes a significant portion of total area in function evaluation using piecewise polynomial approximation. Many papers have proposed various approaches to reduce table size without sacrificing precision requirement. This paper presents new LUT compression methods that do not introduce extra errors but can effectively further reduce the table size in the piecewise polynomial approximation with uniform or non-uniform segmentations.

This paper proposes an adaptive mode and modulation coding switching (AMMCS) scheme for multiple-input multiple-output (MIMO) multicasting system. More specifically, in addition to the adaptively chosen modulation and error coding, two types of MIMO modes are adaptively switched, i.e., between spatial multiplexing (SM) mode, which can achieve higher data rate, and spatial diversity (SD) mode, which can provide higher received signal-to-noise ratio (SNR). Analytical equations for scheduling rate and average spectral efficiency are derived for both SD and SM modes in a 2×2 MIMO system. Simulation results well justify our analytical equations and also demonstrate that our proposed scheme can achieve higher scheduling rate when SNR is low and higher spectral efficiency when SNR is high.

In this paper, a joint uplink (UL) and downlink (DL) framework for wireless mobile camera networks over an OFDMA-based infrastructure is proposed. On the UL, this system collects unicast real-time video streams from mobile wireless camera stations (CSs) and forwards them to a control center. On the DL, the aggregated video streams are multicast to multiple mobile stations (MSs) to facilitate monitoring of the same video scenes. A target bit rate is set for each UL video stream, based on an objective function that includes both the quality of experience (QoE) and popularity of video contents as key criteria. A QoE-driven scheduling and resource allocation policy at the MAC/PHY layers, and a real-time scalable video layer adaptation algorithm in the APP layer are proposed. On the DL, a previously published opportunistic layered multicasting scheduling algorithm is applied. Simulation results demonstrate that this proposed novel architecture can significantly enhance both the spectral efficiency and the QoE of users in both UL and DL directions.

We propose Opportunistic Layered Multicasting (OLM), a joint user scheduling and resource allocation algorithm that provides enhanced quality and efficiency for layered video multicast over Mobile WiMAX. This work is a lead off and complete synergy of layered video multicasting with opportunistic concept. The target application is characterized by groups of users acquiring popular video programs over a fading channel. To accommodate various bandwidth requirements and device capability, video streams are coded into base and enhancement layers using scalable video coding technology. Correspondingly, the optimization problems, which select the best subset of users to receive a specific video layer and assign the most appropriate modulation and coding scheme for this video layer, are specifically formulated for both video layer types. We also design fast and effective algorithms to bridge the gap between theoretical throughput capacity and implementation concerns. Thus, the basic video quality can be efficiently guaranteed to all subscribers while creating most utility out of limited resources on enhancement information. To overcome the inevitable packet loss in a multicast session, an FEC rate adaptation scheme to approach theoretical performance is also presented. Favorable performance of the proposed algorithms is demonstrated by simulations utilizing realistic Mobile WiMAX parameters.

We propose a systematic cross-layer joint scheduling and resource allocation algorithm to provide enhanced quality of service (QoS) for real-time video uplink of camera networks over WiMAX. Under the constraint of limited available OFDMA resource, how to fairly schedule all mobile camera stations (CSs) with varying channel quality and maintain system performance simultaneously is always a critical issue for practical QoS design of a WiMAX base station (BS). The proposed system uses video encoding rate adaptation in application (APP) layer of CSs and effectively incorporates with the medium access control (MAC) QoS mechanisms of the BSs to greatly improve the spectrum efficiency of WiMAX.

A WiMAX radio resource allocation (WRA) problem is investigated in the context of IPTV broadcasting over mobile WiMAX multicast, broadcast services (MBS) channels. The goal is to maximize quality of services, in terms of number of subscribers served, number of IPTV channels carried, and perceived video qualities of individual viewers, subject to constraints on multicast channel capacities and space-time channel quality variations. We present an efficient heuristic algorithm based on the Pareto principle that achieves near-optimal results in polynomial time complexity. Extensive simulations are conducted to compare this new approach against state-of-the-art heuristic algorithms and consistent superior performance has been observed.

We present a Linear Feedback Shift Register (LFSR) like architecture, because the LFSR can bring a lot of data by using a few bits. We calculate the ATE data by Gauss-Elimination and put the ATE data to our decompression architecture to generate a lot of patterns. And one ATE data will run several times in the architecture. If some faults cannot be detected, we will generate the patterns which are brought by fault simulation. If still a few faults cannot be detected, the faults will be caught by directly modify the bits of ATE data. The less ATE data we use, the less cycles we need. Because the reason, we can get high speed testing. And the less data, the low-cost environment we need. The cycle we can save is up to 61.60x. And the average rate of compression can get 19.33x.

Generally speaking, the dependency data compression is very useful for Intellectual Property (IP) cores and SoC. We consider the shift-in power and compression ratio in low-cost ATE environment. We propose new compression architecture with fixed length for running ones. We suppose that the ATE has not repeated function and synchronization signal. In the results, when the complexity of VLSI circuit is growing up, the number of input pins for testing is very low. The average compression ratio of our method is 63% for MinTest on ISCAS'89 benchmarks. The average of peak/WTC shift-in turns to 3×/6.6×, after comparing Selective Scan Slice (SSS) and our method. The average of hardware overhead is 6%.

ATPG-based technique for reducing shift and capture power during scan testing is presented without any influence on fault coverage. This paper presents Adjacent Backtracing filling (AB-fillingl) which both adjacent and backtracing filling algorithms are used, is integrated in the ATPG algorithm to reduce capture power while feeding the first test pattern into CUT. After our approach for at-speed scan testing, all of test patterns have assigned as partially-specified values with a small number of don't care value (x) bits as in test compression, and it is a low capture power and considering the shift power test pattern. Experimental results for ISCAS'89 benchmark circuits show that the proposed scheme outperforms previous method in capture power.

Internet Protocol Television (IPTV) is an emerging and killer application for WiMAX networks, which takes advantage of multicasting mechanisms to efficiently deliver the video data to groups of subscribers. In this paper, we propose a Reception-rate-tracking Opportunistic Multicast Scheduling (ROMS) to enhance the performance of scalable IPTV layered multicasting over WiMAX networks. The proposed ROMS jointly considers the subscriber scheduling and resource allocation to achieve resource efficient multicasting. We validate our solution through theoretical analyses and empirical simulations. Our study indicates that the proposed solution outperforms the Slot-throughput-tracking Opportunistic Multicast Scheduling (SOMS) in terms of resource efficiency for 19.6%-33% in different subscriber group sizes.

A wireless resource scheduling problem is formulated in the context of IPTV multicasting streaming services over WiMAX channels. The goal is to maximize quality of services, in terms of number of subscribers served, number of IPTV channels carried, and video qualities of individual channels; subject to constraints of finite amount of multicast channel capacities as well as time and spatially varying wireless channel qualities. While a globally optimal solution is NP-hard, we present an efficient heuristic algorithm that exploits the structure of the problem formulation to yield solutions that are very close to the optimal solution.

A scheme that ATPG-based technique for reducing shift and capture power during scan testing is presented without any influence on fault coverage. This paper presents an X-filling approach called Adjacent Backtracing fill (AB-fill). After AB-fill approach for at-speed scan testing, all of test patterns have assigned as partially-specified values with a small number of don’t care bits (x) as in test compression, and it is integrated in the ATPG algorithm to reduce capture power while feeding the first test pattern into CUT.

This paper presents a test slice difference (TSD) technique to improve test data compression. It is an efficient method and only needs one scan cell. Consequently, hardware overhead is much lower than cyclical scan chains (CSR). As the complexity of VLSI continues to grow, excessive power supply noise has become seriously. We propose a new compression scheme which smooth down the switching activity and reduce the test data volume simultaneously.

In this paper, new compression architecture is proposed for multiple scan-chains. We use buffers to hold back data, and use read enable signals to filter useless data. We use only four extra channels and less hardware for largest ISCAS'89 circuits to reduce test data volume and shift-in power. The average of peak/WTC shift-in turns to 3x/6.6x, after comparing (Wang and Chakrabarty, 2008) and our method. The average of improvement/ hardware is 16%/6%.

We propose a resource allocation algorithm that provides enhanced QoS and efficiency for layered video multicast over mobile WiMAX. The application is characterized by groups of users acquiring popular video programs over a fading channel. To accommodate various bandwidth requirements and adaptive perceptual quality to different users, video streams are coded into base and enhancement layers using scalable video coding technology. Correspondingly, the optimization problems, which assign the most appropriate modulation schemes to provide best video quality to as many users, can be formulated using opportunistic multicasting concept. We maximize the minimum effective throughput across all users for mandatory (base) layer delivery through adapting modulation and coding schemes. At the same time, optional (enhancement) layers are allocated to maximize total utility. Thus the basic video quality can be efficiently guaranteed to all subscribers while making most out of limited resources on enhancement information. We further present an FEC rate adaptation scheme to approach theoretical performance. Favorable performance of the proposed algorithms is demonstrated by simulations utilizing realistic Mobile WiMAX parameters.

The subject materials of most enterprise e-training programs were mainly developed by employees of the enterprises; therefore, it becomes a challenging issue to efficiently and effectively translate the knowledge and experiences of the employees to computerized subject materials, especially for those who are not an experienced teacher. In addition, to develop an e- training course, personal ignorance or incorrect concepts might significantly affect the quality of the course if only a single employee is asked to develop the subject materials. To cope with this problem, a multi- expert e-training course design model is proposed in this paper. Accordingly, an e-training course development system has been implemented. Moreover, a practical application has showed that of the novel approach not only can improve the quality of the e- training course, but also help the experts to organize their domain knowledge.