Memory Management Approach for Swapless Embedded Systems
The Linux kernel Out of Memory (OOM) killer is not usually invoked on desktop and server computers, because those environments contain sufficient resident memory and swap space, making the OOM condition a rare event. However, swapless embedded systems typically have little main memory and no swap space. In such systems, there is usually no need to allocate a big memory space; nevertheless, even relatively small allocations may eventually trigger the OOM killer.
Experiments with end-user desktop applications show that when a system has low memory—that is, it is about to reach the OOM condition—applications could become nonresponsive due to system slowness. System performance is affected when physical memory is about to reach the OOM condition or is fully occupied. System slowness should be prevented as such behaviour brings discomfort to end users.
Furthermore, the process selection algorithm used by the kernel-based OOM killer was designed for desktop and server computer needs. Thus, it may not work properly on swapless embedded systems, because at any moment it can kill applications that a user may be interacting with.
In this article, we present an approach that employs two memory management mechanisms for swapless embedded systems. The first is applied to prevent system slowness and OOM killer activation, by refusing memory allocations based on a predefined memory consumption threshold. Such a threshold should be determined and calibrated carefully in order to optimize memory usage while avoiding large memory consumption that may lead to system delay and invocation of the OOM killer. We call it the Memory Allocation Threshold (MAT).
The second mechanism employs an additional threshold value known as the Signal Threshold (ST). When this threshold is reached, the kernel sends a low memory signal (LMS), which should be caught by user space, triggering memory release before crossing the MAT. Both thresholds are implemented by a kernel module, the Low Memory Watermark (LMW) module. We offer some experimental results that point out situations when our approach can prove useful in optimizing memory consumption for a class of embedded systems.
System performance is degraded when the memory requirements of active applications exceed the physical memory available on a system. Under such conditions, the perceived system response can be significantly slow. On swapless devices, application memory needs can drive the system to such conditions often, because system internal main memory is low and the chance of applications occupying the whole physical memory is high.
Memory resources should be managed differently on such devices to avoid slow system responsiveness. The memory allocation failure mechanism can be applied to prevent slowness. Preventing system slowness makes OOM killer invocation rare. Thus, such a mechanism also can reduce the chances of triggering the OOM killer, whose process selection algorithm may choose an unexpected application to be killed on devices with low memory and no swap space.
Memory allocation failure means refusing memory allocations requested by applications. It is carried out according to a MAT value that is set based on experimentation with various use cases of end-user applications. MAT should be set sufficiently high to allow applications to allocate necessary memory without affecting overall system performance, but its value should be well defined to guarantee memory allocation failure when necessary to prevent extreme memory consumption.
Before memory allocation failure occurs, however, process termination can be performed to release allocated memory. It can be triggered by transmitting the LMS from kernel space to user space to notify applications to free up memory. LMS is dispatched according to ST value. ST should be smaller than MAT, as shown in Figure 1, because the LMS should occur well before memory allocation failure.
If the LMS dispatch is successful and memory is released by receiving the signal, a possible memory allocation failure will be prevented. A useful scenario could involve running some window-based applications, A, B and C, consuming chunks of memory, while their window frames can superimpose one another (assuming the use of a simple window manager environment such as Matchbox). Assuming that application A is the one the user is interacting with at the moment MAT is reached, instead of denying memory allocation to A, it would be preferable to attempt to free up memory allocated by applications B and C, which are not visible to the user. Doing this would allow the user to continue working with application A.
However, memory allocation failure could be unavoidable for some application use cases. For instance, such a case could involve a single window-based application, consuming memory at a constant rate, that the user is interacting with. Releasing memory from other applications would not be as desirable in this situation, because there may be no other window-based applications from which memory could be released. Therefore, a more desirable solution would be to fail memory allocation requested by the guilty application, selecting it as a candidate for termination.
In our proposal, the kernel should provide two mechanisms to deal with management of memory in extreme cases of low memory levels:
Failure of brk(), mmap() and fork() system calls: deny memory allocation requests to prevent system slowness and kernel OOM killer invocation according to a previously calibrated MAT level.
Low memory signal: Kernel Event Layer signal sent by the kernel to a user-space process terminator, which should employ a process selection algorithm that works based on a specified ST.
Using these mechanisms, it would be possible to identify when memory can be released or when to deny further allocations. Denying memory allocations should happen only when memory release attempts cannot be successful.
- Nmap—Not Just for Evil!
- Resurrecting the Armadillo
- High-Availability Storage with HA-LVM
- March 2015 Issue of Linux Journal: System Administration
- Real-Time Rogue Wireless Access Point Detection with the Raspberry Pi
- DNSMasq, the Pint-Sized Super Dæmon!
- Localhost DNS Cache
- Days Between Dates: the Counting
- The Usability of GNOME
- Linux for Astronomers