FPGA-based edge computing: Task modeling for cloud-edge collaboration

With the development of the Internet of Things and devices continuing to scale,using cloud computing resources to process data in real-time is challenging.Edge computing technologies can improve real-time performance in processing data.By introducing the FPGA into the computing node and using the dynamic reconfigurability of the FPGA,the FPGA-based edge node can increase the edge node capability.In this paper,a task-based collaborative method for an FPGA-based edge computing system is proposed in order to meet the collaboration among FPGA-based edge nodes,edge nodes,and the cloud.The modeling of the task includes two parts,task information and task-dependent file.Task information is used to describe the running information and dependency infor-mation required for the task execution.Task-dependent file contains the configuration bit-stream of FPGA in running of the task.By analyzing the task behavior,this paper builds four basic behaviors,analyzes the critical attributes of each behavior,and summa-rizes the task model suitable for FPGA-based edge nodes.Tasks with specific functions can be created by modifying different attributes of model nodes.Finally,the availability of the model and the task-based collaborative method are verified by simulation exper-iments.The experimental results that the task model proposed in this paper can meet cloud-edge collaboration in the FPGA-based edge computing environment.

Complex Problems Solution as a Service Based on Predictive Optimization and Tasks Orchestration in Smart Cities

Smart cities have different contradicting goals having no apparent solution.The selection of the appropriate solution,which is considered the best compromise among the candidates,is known as complex problem-solving.Smart city administrators face different problems of complex nature,such as optimal energy trading in microgrids and optimal comfort index in smart homes,to mention a few.This paper proposes a novel architecture to offer complex problem solutions as a service(CPSaaS)based on predictive model optimization and optimal task orchestration to offer solutions to different problems in a smart city.Predictive model optimization uses a machine learning module and optimization objective to compute the given problem’s solutions.The task orchestration module helps decompose the complex problem in small tasks and deploy them on real-world physical sensors and actuators.The proposed architecture is hierarchical and modular,making it robust against faults and easy to maintain.The proposed architecture’s evaluation results highlight its strengths in fault tolerance,accuracy,and processing speed.

A blockchain bee colony double inhibition labor division algorithm for spatio-temporal coupling task with application to UAV swarm task allocation

It is difficult for the double suppression division algorithm of bee colony to solve the spatio-temporal coupling or have higher dimensional attributes and undertake sudden tasks.Using the idea of clustering,after clustering tasks according to spatio-temporal attributes,the clustered groups are linked into task sub-chains according to similarity.Then,based on the correlation between clusters,the child chains are connected to form a task chain.Therefore,the limitation is solved that the task chain in the bee colony algorithm can only be connected according to one dimension.When a sudden task occurs,a method of inserting a small number of tasks into the original task chain and a task chain reconstruction method are designed according to the relative relationship between the number of sudden tasks and the number of remaining tasks.Through the above improvements,the algorithm can be used to process tasks with spatio-temporal coupling and burst tasks.In order to reflect the efficiency and applicability of the algorithm,a task allocation model for the unmanned aerial vehicle(UAV)group is constructed,and a one-to-one correspondence between the improved bee colony double suppression division algorithm and each attribute in the UAV group is proposed.Task assignment has been constructed.The study uses the self-adjusting characteristics of the bee colony to achieve task allocation.Simulation verification and algorithm comparison show that the algorithm has stronger planning advantages and algorithm performance.

Mathematical, Mathematics Educational, and Educational Values in Mathematical Modeling Tasks

Purpose:The purpose of this study is to explore the mathematical values,mathematics educational values,and educational values invoIved in mathematical modeling tasks based on different mathematical modeling perspectives.Design/Approach/Methods:In this con text,the prese nt study is a qualitative research based on document analysis.The data were analyzed usingsemantic content analysis,and the selected modeling tasks based on different mathematical modeling perspectives were examined at the sentence level.Findings:Control,mystery,and openness mathematical values appeared in all mathematical modeling tasks,and rationalism and objectivism mathematical values appeared in realistic/applied and socio-critical modeli ng perspectives.Product,exploration,creating,releva nee,pleasure,and application mathematics educational values also emerged in all modeling tasks.Educational values of social justice,equity,social welfare,humanity,and altruism were more important in the socio critical modeling,while the value of individualism was more emphasized in the model-eliciting approach.Originality/Value:By determining mathematical,mathematics educational,and educational values involved in mathematical modeling tasks based on different mathematical modeling perspectives,an effective and more value-balaneed mathematical modeling instruction can be provided.

MoM-PO/SBR Algorithm Based on Collaborative Platform and Mixed Model

For electromagnetic scattering of 3?D complex electrically large conducting targets,a new hybrid algorithm,MoM?PO/SBR algorithm,is presented to realize the interaction of information between method of moment(MoM)and physical optics(PO)/shooting and bouncing ray(SBR).In the algorithm,the COC file that based on the Huygens equivalent principle is introduced,and the conversion interface between the equivalent surface and the target is established.And then,the multi?task flow model presented in this paper is adopted to conduct CPU/graphics processing unit(GPU)tests of the algorithm under three modes,i.e.,MPI/OpenMP,MPI/compute unified device architecture(CUDA)and multi?task programming model(MTPM).Numerical results are presented and compared with reference solutions in order to illustrate the accuracy and the efficiency of the proposed algorithm.

Autonomy Evaluation of Unmanned Systems Based on Task Models

In this study,relevant work on autonomy evaluation(AE)in recent years was comprehensively reviewed and classified from the perspective of task models,and a closed-loop task models based theoretical framework for AE was developed.The main contributions of this study are as follows.1)A taxonomy for AE based on task models was introduced to classify current theories,methods and standards.2)The limitations of the current autonomous evaluation methods were addressed to provide a theoretical framework for quantitative evaluation based on task models,and evaluation metrics for each stage were proposed based on the AE theoretical framework.3)Qualitative analyses of the superiority of the proposed AE framework based on the closed-loop task models were conducted.This study attempts to provide a reference for researchers and engineers in the autonomous unmanned systems field and inspire future development of AE.

Gravity observation at continental borderlands (Russia, Primorie, Cape Shults)

The paper is focused on different kinds of gravity results obtained in Shults Cape Observatory for 2010 -2015. Gravity observation is interpreted together with GPS observation data which was obtained from 2012 to 2015 at the same station, The station is situated on Gamov peninsular （42.58° N, 131.15° E, Russia） at the coast of Japan Sea, This region constitutes the eastern boundary of Eurasia. This major continental tectonic feature is associated with a seismic activity, high heat flow and anomalous thickness of earth＇s crust. The goal of the observation was the investigation of gravity variation with time and seismicity situation monitoring. Gravity observation was developed at special basement by absolute gravimeter （GABL type） and by spring gravimeter （SCINREX CG-5and gPhone type）. Tidal models were tested by results of observation with spring gravimeters. Reduction task was solved, as the experimental data received from different points of Shults Cape Observatory was used. Applied reduction coefficient is 203.3 12Gal m l, and agrees with theoretical calculation. Next goal was studying structure of earth＇s crust by means of gravity models. Gravity anomaly varied from 30 mGal to 46 mGal, which also depend on difference reference system, Experimental results were used for testing of the structure of continental boundary, which also depends on the sea bottom flexion. Thickness of elastic layer was estimated from 12 km to 18 km by using different models.

Empirical Research on User Acceptance of Mobile Searches

The mobile search, a combination of a web search engine and a mobile communication system, is viewed as the most influential application in the 3G era. Therefore, mobile search service providers are eager to know which factors most influence user acceptance of mobile searches. Based on the characteristics of mobile searches and a review of previous information technology acceptance research, this study integrates the task technology fit model and the unified theory of acceptance and use of technology model to develop a mobile search acceptance model and empirically tests this model. This study finds that, for mobile searches, the performance expectancy, social influence, and perceived cost all significantly influence use intention and the performance expectancy increases with the increasing user＇s experience and higher tasktechnology fit degree. The effort expectancy is found to not affect the use intention of mobile searches and the users＇ gender does not have a significant moderating effect on the use intention. The results are then used to develop suggestions for mobile search providers to promote their application and development.