Key Technology of Embedded System Implementation for Software-based CNC System

The software-based computer numerical control（CNC） system includes three types of tasks： periodic real-time tasks, aperiodic real-time tasks, and non-real-time tasks. The tasks are characterized by concurrency, hybridization, and correlation, which make system implementation difficult. The conventional scheduling algorithm can not meet the demands of system implementation in the software-based CNC system completely. The uncertainty factors when running real-time tasks affect control performance by degrading manufacturing accuracy as a result of system resource and processor use restrictions. To address the technical difficulty of embedded system implementation, a novel fuzzy feedback scheduling algorithm based on output jitter of key real-time tasks for a software-based CNC system is proposed. Time characteristics, such as sampling jitter, input-output jitter, and non-schedulability are discussed, followed by quantification through simulations of the impact of time characteristics on manufacturing accuracy. On the basis of this research, the scheduler architecture is designed, and then the algorithm table is calculated. When the system resource changes, the key periodic real-time tasks meet their deadlines by means of dynamically adjusting the task period. The simulated results show that the machining precision rises by an order of magnitude for the proposed scheduler in resource-constrained software-based CNC systems. Moreover, unlike conventional feedback scheduling methods, the algorithm in this paper does not rely on the availability of task execution times and is easy to implement while incurring only a small overhead.

Parallel Software-Based Self-Testing with Bounded Model Checking for Kilo-Core Networks-on-Chip

Online testing is critical to ensuring reliable operations of the next generation of supercomputers based on a kilo-core network-on-chip(NoC)interconnection fabric.We present a parallel software-based self-testing(SBST)solution that makes use of the bounded model checking(BMC)technique to generate test sequences and parallel packets.In this method,the parallel SBST with BMC derives the leading sequence for each router’s internal function and detects all functionally-testable faults related to the function.A Monte-Carlo simulation algorithm is then used to search for the approximately optimum configuration of the parallel packets,which guarantees the test quality and minimizes the test cost.Finally,a multi-threading technology is used to ensure that the Monte-Carlo simulation can reach the approximately optimum configuration in a large random space and reduce the generating time of the parallel test.Experimental results show that the proposed method achieves a high fault coverage with a reduced test overhead.Moreover,by performing online testing in the functional mode with SBST,it effectively avoids the over-testing problem caused by functionally untestable turns in kilo-core NoCs.

Precision Livestock Farming: Precision feeding technologies and sustainable livestock production

In order to be able to produce safe,uniform,cheap,environmentally-and welfare-friendly food products and market these products in an increasingly complex international agricultural market,livestock producers must have access to timely production related information.Especially the information related to feeding/nutritional issues is important,as feeding related costs are always significant part of variables costs for all types of livestock production.Therefore,automating the collection,analysis and use of production related information on livestock farms will be essential for improving livestock productivity in the future.Electronically-controlled livestock production systems with an information and communication technology(ICT)focus are required to ensure that information is collected in a cost effective and timely manner and readily acted upon on farms.New electronic and ICT related technologies introduced on farms as part of Precision Livestock Farming(PLF)systems will facilitate livestock management methods that are more responsive to market signals.The PLF technologies encompass methods for electronically measuring the critical components of the production system that indicate the efficiency of resource use,interpreting the information captured and controlling processes to ensure optimum efficiency of both resource use and livestock productivity.These envisaged real-time monitoring and control systems could dramatically improve production efficiency of livestock enterprises.However,further research and development is required,as some of the components of PLF systems are in different stages of development.In addition,an overall strategy for the adoption and commercial exploitation of PLF systems needs to be developed in collaboration with private companies.This article outlines the potential role PLF can play in ensuring that the best possible management processes are implemented on farms to improve farm profitability,quality of products,welfare of livestock and sustainability of the farm environment,especially as it related to intensive livestock species.