The passive video surveillance system is designed in this paper. At first, it captures images through the camera sensor and displays the image in the client program without battery and complicated wiring. This system consists of three modules: energy harvesting, data transmission, and data processing. Firstly, the system transmits UHF radio frequency signals to the environment through a signal transmitter, then the system converts the received radio frequency signal into an electrical signal and stores it in a on-board supercapacitor to supply power to each device in the system. The system dispatches the image capture task through a low-power microprocessor, and transmits the data to the host under the same local network through a Wi-Fi module.

Heterogeneous computing, as a kind of special parallel computing method, can exert the ability of different computing resources based on the characteristics of computing tasks and is much advantageous in improving server computing performance, energy efficiency ratio (EER) and real time performance. FPGA-GPU-CPU heterogeneous computing was born for the real-time processing of massive of data. However, the communication bottlenecks between different computing units have set restrictions on the computing capabilities of heterogeneous platform. In view of the above issues, this article connects GPU and FPGA devices through the PCI Express bus, so that data can be transmitted between these heterogeneous computing units without the assistance of the system CPU memory. And, we have realized that the PCIe communication by taking FPGA as the main controller through GPUDirect RDMA, which improves the weakness of slow reading in PCle communication where the GPU as the main controller. Experiments show that we have improved the efficiency by 1.4 times compared to the memory sharing-based communication and the data rate has been made closest to the maximum theoretical bandwidth.

As the Internet of Things technology is finding more wide applications; wearable smart systems such as smart phones have gradually come into our lives. The smart wearable systems with numerous states usually lead to various unanticipated problems. A connective and semantic similarity clustering algorithm (CSSCA) and a hierarchical combinatorial test model based on finite state machine (FSM) are proposed to solve the problem. The FSM model of user manipulations is usually used to model the system design specification of a smart phone for black-box testing, and then it is converted into a regular expression, and some testing cases are generated according to the regular expression. Many experiments show that a large in scale and complicated in structure smart phone software can be tested using our innovative algorithms to discover more deep hidden logical errors efficiently and effectively. (C) 2017 Elsevier Ltd. All rights reserved.

Smart TV in China as an important component of the smart home, does not only have the functions of the traditional TV, but also have the functions, such as distance education, remote monitoring, E-business, and media playing, which brings about its software to be more complex in structure and larger in scale, accordingly, the total testing efficiency becomes lower when using traditional testing methods, and the deep-hidden software defects cannot be detected efficiently and effectively. A novel automatic software testing method based on system design specifications is proposed to improve the smart TV software testing efficiency. First, the behavior of the smart TV is modeled, based on the system design specification with hierarchical state transition matrixes (HSTMs). The scale of the state model of the smart TV is lowered by setting the group state according to the choice of the key nodes based on the importance of the nodes in the network; then, the HSTM model is converted into an expanded regular expression (ERE) with the memory property. Second, every closure operator in the ERE is replaced recursively with a certain integral value, according to the cyclomatic complexity of an ERE in the closure to generate a simplified ERE. Then, a test case is generated from the simplified ERE. Finally, the test cases are converted into python script, and a test platform is designed to send the python script to the Android smart TV automatically through its android debug bridge interface. The practical application shows that the test period is shortened, and comparing with the traditional manual test methods, more errors can be tested.

Hybrid load in e-health services is composed of online e-health service applications and offline jobs. Previous methods overlooked the impact of system performance for the fine-grained service components. In this paper, a hybrid load scheduling scheme is proposed in which scheduling is performed not only at the level of the component, but also within components. To improve both execution efficiency and searching accuracy, the proposed algorithm searches the compressing method of the Lucene index and then filters that index. Simulations are conducted on a Storm platform to evaluate the performance of the proposed scheme. Simulation results demonstrate that the proposed scheme can increase the response speed by 67.79% with an accuracy of 95.94%, and the response speed decreases by 11.6–53.2%.

Due to the limited resources of wireless sensor network, low efficiency of real-time communication scheduling, poor safety defects, and so forth, a queuing performance evaluation approach based on regular expression match is proposed, which is a method that consists of matching preprocessing phase, validation phase, and queuing model of performance evaluation phase. Firstly, the subset of related sequence is generated in preprocessing phase, guiding the validation phase distributed matching. Secondly, in the validation phase, the subset of features clustering, the compressed matching table is more convenient for distributed parallel matching. Finally, based on the queuing model, the sensor networks of task scheduling dynamic performance are evaluated. Experiments show that our approach ensures accurate matching and computational efficiency of more than 70%; it not only effectively detects data packets and access control, but also uses queuing method to determine the parameters of task scheduling in wireless sensor networks. The method for medium scale or large scale distributed wireless node has a good applicability.

In this paper, a communication task scheduling evaluation model based on the queue model is proposed to analyze the wireless sensor performance parameters. The typical communication task scheduling which deals with all communication tasks scheduling requests and makes actions or responses. A task scheduling-preemptive-priority model is proposed to simulate and analyze typical wireless sensor network using matrix-geometric theory. And then, several merits of the communication task schedule are obtained, including the communication task loss rate, the average response time and the wireless sensor occupancy rate. At last, experiments are conducted to show the performance of our scheme. Simulation results manifest that when sensor usage rate up to 97%, our scheme is feasible for wireless sensor networks.

Due to the closeness of an embedded system, to test in the embedded software is extremely difficult, especially for real-time embedded software. It is no doubt that instruction set simulation(ISS) system based on embedded SoC will greatly reduce difficulties of embedded software testing. Therefore, to make sure the credibility of the instruction set simulation system it is especially important. The huge number of random test cases generated during testing makes it unable to determine the running results. A method of hardware and software collaborative verification based on FPGA Leon core and microcomputer software SPARC instruction set is proposed to solve both the efficiency in traditional software testing and the accuracy in determining running results problems effectively. Ten test cases from the Mibench standard test set are selected for hardware and software collaborative verification. The statistical results show the instruction coverage of all-digital SPARC V8 simulator reaches 97 percent.

Traditional multi-processor interconnection structure can not be suitable for highly integrated SoC multi-core processor because of high resource overhead, and NoC can solve the problem of multi-core processor interconnection on SoC with high-bandwidth, low power, scalability and parallel communication. Based on multi-core NoC simulation platform, task-oriented NoC scheduling policy is proposed, and median filter algorithm is optimized as typical application for parallel scheduling. SoClib simulation platform with SystemC language is used for validation and analysis variation of multi-core NoC speedup when cores number is changed.