Implementation of Multiprocessing and Multithreading for End Node Middleware Control on Internet of Things Devices

Iwan Kurnianto Wibowo, A. Besari, Muh. Rifqi Rizqullah
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Abstract

Previously, an educational robot system was built by incorporating Internet of Things (IoT) elements. Over time, this educational robot has been implanted with a middleware. Middleware has a role in receiving command data from the real-time database, access sensors, actuators, and sending feedback. Middleware contains protocols that translate commands between high-level programming and Raspberry Pi hardware. The focus of this research is to improve the performance of the middleware to pursue processing time efficiency. For this reason, it is necessary to implement multiprocessing and multithreading in handling several tasks. The CPU division has been adjusted automatically to not work on just one core or block of memory. Several program functions can run in parallel and reduce program execution time efficiently. The tasks handled are sensor reading and actuator control in the form of a motor. Testing has been carried out to perform multiprocessing and multithreading tasks to process six sensors and five actuators. Multiprocessing requires an average of 1.00% to 15.00% CPU usage and 2.70% memory usage. Meanwhile, multithreading involves an average of 1.00% to 71.00% CPU usage and 3.30% memory usage.
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物联网设备端节点中间件控制的多处理多线程实现
此前,教育机器人系统是通过结合物联网(IoT)元素构建的。随着时间的推移,这个教育机器人已经植入了一个中间件。中间件的作用是接收来自实时数据库的命令数据、访问传感器、执行器和发送反馈。中间件包含在高级编程和树莓派硬件之间转换命令的协议。本文的研究重点是提高中间件的性能,追求处理时间效率。因此,有必要在处理多个任务时实现多处理和多线程。CPU划分已经自动调整为不能只在一个核心或内存块上工作。多个程序函数可以并行运行,有效地减少了程序的执行时间。处理的任务是传感器读取和电机形式的致动器控制。对6个传感器和5个执行器进行了多处理和多线程任务测试。多处理平均需要1.00%到15.00%的CPU使用率和2.70%的内存使用率。同时,多线程涉及平均1.00%到71.00%的CPU使用率和3.30%的内存使用率。
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审稿时长
10 weeks
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