Smart scene management for IoT-based constrained devices using checkpointing
Smart scene management for IoT-based constrained devices using checkpointing
复制标题
使用检查点对基于物联网的受限设备进行智能场景管理
DOI：
10.1109/nca.2016.7778613
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
S. Tazi
中科院分区：
文献类型：
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作者：
Francois Aissaoui;G. Cooperman;T. Monteil;S. Tazi
物联网的典型设备通常性能较低，且内存有限。这是出于能源和成本方面的考虑。然而，物联网应用需要越来越复杂的程序以及越来越大量的数据。原则上，应用程序可以通过根据需要从文件系统保存和加载数据来在有限的内存中管理不断增加的数据。但是对于代码开发者来说，以这种方式管理内存的使用既耗时又容易出错。我们提出一种新颖的架构，其中不同的语义场景被实现为独立的操作系统进程。当需要从一个场景切换到另一个场景时，代表当前场景的正在运行的进程被设置检查点，并且一个代表新场景的进程从检查点镜像重新启动。这种解决方案利用检查点为终端程序员提供了一个更简单的框架，同时还能带来更高的性能。例如，实验表明从检查点镜像重新启动一个旧进程比启动一个新进程快约25倍。当使用基于mmap的优化（将虚拟内存页面的换入推迟到运行时）时，重新启动一个旧进程大约快500倍。总体而言，在树莓派B上，检查点设置和重新启动每个操作都在不到0.2秒内完成。
Typical devices of the Internet of Things are usually under-powered, and have limited RAM. This is due to energy and cost concerns. Yet, IoT applications require increasingly complex programs with increasingly large amounts of data. In principle, an application could manage the increasing data within the limited RAM by saving and loading data from the file system as needed. But managing the use of RAM in this way is both time-consuming and error-prone for the code developer. We propose instead a novel architecture in which different semantic scenes are implemented as independent operating system processes. As the need arises to switch from one scene to another, the currently running process, which represents the current scene, is checkpointed and a process representing the new scene is restarted from a checkpoint image. This solution employs checkpointing to provide a simpler framework for the end programmer, while at the same time resulting in higher performance. For example, experiments show that restarting an old process from a checkpoint image is about 25 times faster than starting a new process. When using an mmap-based optimization (deferring the paging in of virtual memory pages until runtime), restarting an old process is about 500 times faster. Overall, checkpoint and restart each execute in less than 0.2 seconds on a Raspberry Pi B.