Container-Based Internet of Vehicles Edge Application Migration Mechanism

Internet of Vehicles (IoV) applications integrating with edge computing will significantly drive the growth of IoV. However, the contradiction between the high-speed mobility of vehicles, the delay sensitivity of corresponding IoV applications and the limited coverage and resource capacity of distributed edge servers will pose challenges to the service continuity and stability of IoV applications. IoV application migration is a promising solution that can be supported by application containerization, a technology forseamless cross-edge-server application migration without user perception. Therefore, this paper proposes the container-based IoV edge application migration mechanism, consisting of three parts. The first is the migration trigger determination algorithm for cross-border migration and service degradation migration, respectively, based on trajectory prediction and traffic awareness to improve the determination accuracy. The second is the migration target decision calculation model for minimizing the average migration time and maximizing the average service time to reduce migration times and improve the stability and adaptability of migration decisions. The third is the migration decision algorithm based on the improved artificial bee colony algorithm to avoid local optimal migration decisions. Simulation results show that the proposed migration mechanism can reduce migration times, reduce average migration time, improve average service time and enhance the stability and adaptability of IoV application services.     

引导学生自主学习,在实践中培养创新型人才

<正>1研究背景近年来,计算机硬件,特别是多核技术及嵌入式技术的发展,给计算机相关研究带来了新的契机,同时也对计算机相关课程的教学产生了深远影响。多核技术的发展使未来大多数的软件     

无线传感器网络中能量均衡可靠路由度量方法

针对无线传感器网络的资源限制以及对传输可靠性的特殊要求,提出一种能量均衡路由度量方法EBETX。以ETX值作为路由度量的同时,兼顾网络中节点能量消耗情况,保证网络各节点能量均衡消耗,延长网络的生存时间,实现高效路由与能量均衡的有效权衡。通过NS2仿真实验验证了该方法的可行性。     

Development of a web-based insulin decision aid for the elderly: usability barriers and guidelines

Universal Access in the Information Society - In recent years, researchers have attempted to shift patient decision aids (PDAs) from paper-based to web-based to increase its accessibility. Insulin...     

PCI总线在双谱段探测系统中的应用*

PCI是DSP应用系统与通用计算机高速通信的理想接口。介绍了一种双谱段探测系统的PCI接口方案,该方案采用TI公司的TMS320F2812 DSP作为控制单元主控芯片,采用Cypress公司PCIDP系列的CY7C09449PV作为PCI接口芯片,具有接口简单方便易于实现的优点。详细讨论了CY7C09449PV与TMS320F2812的硬件连接、参数配置与时序分析。     

用多媒体软件模拟匀加速直线运动

用多媒体软件Ｄｉｒｅｃｔｏｒ６．０来模拟物理教学中的匀加速直线运动。     

Hybrid Well-balanced WENO Schemes with Different Indicators for Shallow Water Equations

In (J. Comput. Phys. 229: 8105–8129, 2010), Li and Qiu investigated the hybrid weighted essentially non-oscillatory (WENO) schemes with different indicators for Euler equations of gas dynamics. In this continuation paper, we extend the method to solve the one- and two-dimensional shallow water equations with source term due to the non-flat bottom topography, with a goal of obtaining the same advantages of the schemes for the Euler equations, such as the saving computational cost, essentially non-oscillatory property for general solution with discontinuities, and the sharp shock transition. Extensive simulations in one- and two-dimensions are provided to illustrate the behavior of this procedure.     

Facial expression recognition using radial encoding of local Gabor features and classifier synthesis

Primarily motivated by some characteristics of the human visual cortex (HVC), we propose a new facial expression recognition scheme, involving a statistical synthesis of hierarchical classifiers. In this scheme, the input images of the database are first subjected to local, multi-scale Gabor-filter operations, and then the resulting Gabor decompositions are encoded using radial grids, imitating the topographical map-structure of the HVC. The codes are fed to local classifiers to produce global features, representing facial expressions. Experimental results show that such a hybrid combination of the HVC structure with a hierarchical classifier significantly improves expression recognition accuracy when applied to wide-ranging databases in comparison with the results in the literature. Furthermore, the proposed system is not only robust to corrupted data and missing information, but can also be generalized to cross-database expression recognition.     

Blockwise conjugate gradient methods for image reconstruction in volumetric CT

Cone beam computed tomography (CBCT) enables volumetric image reconstruction from 2D projection data and plays an important role in image guided radiation therapy (IGRT). Filtered back projection is still the most frequently used algorithm in applications. The algorithm discretizes the scanning process (forward projection) into a system of linear equations, which must then be solved to recover images from measured projection data. The conjugate gradients (CG) algorithm and its variants can be used to solve (possibly regularized) linear systems of equations Ax=b and linear least squares problems minx∥b-Ax∥(2), especially when the matrix A is very large and sparse. Their applications can be found in a general CT context, but in tomography problems (e.g. CBCT reconstruction) they have not widely been used. Hence, CBCT reconstruction using the CG-type algorithm LSQR was implemented and studied in this paper. In CBCT reconstruction, the main computational challenge is that the matrix A usually is very large, and storing it in full requires an amount of memory well beyond the reach of commodity computers. Because of these memory capacity constraints, only a small fraction of the weighting matrix A is typically used, leading to a poor reconstruction. In this paper, to overcome this difficulty, the matrix A is partitioned and stored blockwise, and blockwise matrix-vector multiplications are implemented within LSQR. This implementation allows us to use the full weighting matrix A for CBCT reconstruction without further enhancing computer standards. Tikhonov regularization can also be implemented in this fashion, and can produce significant improvement in the reconstructed images.