基于中间件的实时内存调度

在数据密集型实时监测系统中，任务需要通过分配内存来存储和处理动态变化的信息。该文提出了一种基于中间件的新型内存调度器，通过反馈驱动来调节实时任务的内存分配，与受控任务保持平滑的连接，开放结构允许系统设计人员增加或修改内存管理策略。测试结果表明，内存调度器引起的开销较小，能有效地协调资源共享冲突。

Real-time Memory Scheduling Based on Middleware

The high data intensity of real-time monitoring systems makes it difficult to ensure that subtasks can maintain sufficient memory to store and analyze the data gathered form the sensors. This paper describes the design and implementation of a memory scheduler for these types of monitoring systemsi The memory scheduler mediates between multiple real-time tasks and the facilities of a real-time operating system using feedback and other inputs, it adjusts memory allocations over time to ensure that high application-level QoS is maintained. The scheduling connects to its monitored tasks in a non-invasive manner based on and integrated with standard middleware, and implements an open architecture for new memory management policies. The test results show that the overloads of scheduler are reasonable and allow the monitoring system to function in the face of run-time memory resource contention.