Transient fault aware application partitioning computational offloading algorithm in microservices based mobile cloudlet networks
Transient fault aware application partitioning computational offloading algorithm in microservices based mobile cloudlet networks
复制标题
基于微服务的移动云网络中的瞬态故障感知应用分区计算卸载算法
DOI：
10.1007/s00607-019-00733-4
复制
发表时间：
2020-01-01
期刊：
影响因子：
3.7
通讯作者：
Li, Xiaoping
中科院分区：
文献类型：
--
作者：
Lakhan, Abdullah;Li, Xiaoping
移动的Cloudlet计算范式（MCC）通过利用资源受限的移动的设备的计算卸载方法，允许使用计算云资源执行资源密集型移动的应用。然而，计算卸载需要在MCC中执行期间对移动的应用进行分区，使得总执行成本最小化。在MCC中，在运行时网络上下文（即，网络带宽、信号强度、延迟等）是间歇性改变的，并且短暂的故障（由于临时网络连接故障、服务忙碌、数据库磁盘存储不足）经常在短时间内发生。因此，在运行时的移动的应用程序的瞬时故障感知分区是一项具有挑战性的任务。由于现有的MCC通过利用重量级虚拟机来提供计算单片服务，这导致长的VM启动时间和高开销，并且这些不能满足细粒度微服务应用的要求（例如，电子医疗、电子商务、3D游戏和增强现实）。科普上述问题，提出了基于微服务的移动的云平台，利用容器化技术取代重量级虚拟机，并提出了应用程序分区任务分配（APTA）算法，该算法在运行时确定应用程序分区，并采用故障感知（FA）策略在MCC中不中断地健壮执行微服务应用程序。仿真结果验证了所提出的微服务移动的云平台不仅缩短了运行时平台的建立时间，而且通过将APTA和FA应用于现有的基于VM的MCC和应用划分策略，降低了节点的能耗，提高了应用响应时间。
Mobile Cloudlet Computing paradigm (MCC) allows execution of resource-intensive mobile applications using computation cloud resources by exploiting computational offloading method for resource-constrained mobile devices. Whereas, computational offloading needs the mobile application to be partitioned during the execution in the MCC so that total execution cost is minimized. In the MCC, at the run-time network contexts (i.e., network bandwidth, signal strength, latency, etc.) are intermittently changed, and transient failures (due to temporary network connection failure, services busy, database disk out of storage) often occur for a short period of time. Therefore, transient failure aware partitioning of the mobile application at run-time is a challenging task. Since, existing MCC offers computational monolithic services by exploiting heavyweight virtual machines, which incurs with long VM startup time and high overhead, and these cannot meet the requirements of fine-grained microservices applications (e.g., E-healthcare, E-business, 3D-Game, and Augmented Reality). To cope up with prior issues, we propose microservices based mobile cloud platform by exploiting containerization which replaces heavyweight virtual machines, and we propose the application partitioning task assignment (APTA) algorithm which determines application partitioning at run-time and adopts the fault aware (FA) policy to execute microservices applications robustly without interruption in the MCC. Simulation results validate that the proposed microservices mobile cloud platform not only shrinks the setup time of run-time platform but also reduce the energy consumption of nodes and improve the application response time by exploiting APTA and FA to the existing VM based MCC and application partitioning strategies.