CN105516281A - Low energy consumption and load balance transfer calculating method and device based on mobile cloud environment - Google Patents
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Abstract
本发明公开了一种基于移动云环境低能耗和负载均衡的计算迁移方法和装置，从云端服务器和移动终端获取影响数据流应用程序划分的因素值，结合数据流应用程序划分策略，动态的对数据流应用程序进行划分，将移动终端数据流应用程序迁移到云端服务器执行或将云端服务器应用程序迁移到移动终端执行；因素值包括从云端服务器获取的云端服务器当前负载和从移动终端获取的当前电量、CPU负载、网络带宽和可用内存空间。通过本发明的方案不仅能减少移动终端的能耗、实现移动终端和云端的负载均衡，同时可以提高移动终端执行数据流应用程序的吞吐量，同时减少响应时间，提高运算效率。
The invention discloses a computing migration method and device based on low energy consumption and load balancing in a mobile cloud environment. The value of factors affecting the division of data flow applications is obtained from cloud servers and mobile terminals, and combined with the division strategy of data flow application programs, dynamically Data stream applications are divided, and mobile terminal data stream applications are migrated to the cloud server for execution or cloud server applications are migrated to the mobile terminal for execution; factor values include the current load of the cloud server obtained from the cloud server and the current load obtained from the mobile terminal. Battery power, CPU load, network bandwidth and available memory space. The solution of the present invention can not only reduce the energy consumption of the mobile terminal, realize the load balance between the mobile terminal and the cloud, but also improve the throughput of the mobile terminal to execute the data flow application program, reduce the response time, and improve the computing efficiency.
Description
技术领域technical field
本发明涉及移动云计算技术，尤其涉及移动云环境中一种基于移动云环境低能耗和负载均衡的计算迁移方法。The invention relates to mobile cloud computing technology, in particular to a computing migration method in the mobile cloud environment based on low energy consumption and load balancing in the mobile cloud environment.
背景技术Background technique
云计算正推动IT产业模式向服务交付方式转变，它提供了一个共享池可虚拟化的，动态可配置的和通过因特网或其它可用网络管理需求交付给客户的计算资源的计算规范。随着无线通信和便携式设备的技术快速发展，移动计算已经融入到我们的生活上，由于移动性的增加，用户在移动设备上需要独立运行或者访问远程的移动应用程序。在移动系统中的云服务应用带来了一个新兴的移动计算模式，称为移动云计算。Cloud computing is driving the transformation of the IT industry model to a service delivery method, which provides a shared pool of computing resources that can be virtualized, dynamically configured, and delivered to customers on demand through the Internet or other available networks. With the rapid development of wireless communication and portable device technology, mobile computing has been integrated into our lives. Due to the increase in mobility, users need to run independently or access remote mobile applications on mobile devices. The application of cloud services in mobile systems brings a new mobile computing model called mobile cloud computing.
移动数据流应用程序通常使用摄像头或者其它靠数据率的传感器来执行感知相关的服务，如脸部和物体识别，以增强在移动设备上的现实体现。面向数据路应用程序可以划分为许多独立的组件，各个组件分别完成各自不同的功能并且不同组件之间可能有着数据传输关系，这些组件可以看成是一个个子任务，每个子任务可以迁移到云端执行，也可以在移动终端本地执行。Mobile streaming applications typically use cameras or other data rate-dependent sensors to perform perception-related services, such as face and object recognition, to enhance the representation of reality on mobile devices. Data-oriented applications can be divided into many independent components. Each component performs different functions and may have a data transmission relationship between different components. These components can be regarded as subtasks, and each subtask can be migrated to the cloud for execution , and can also be executed locally on the mobile terminal.
由于移动终端使用方便、便于携带，越来越多数据流应用程序需要在移动终端执行，但很多应用程序由于移动设备CPU性能或能源限制而不能有效的运作。Due to the convenience and portability of mobile terminals, more and more data streaming applications need to be executed on mobile terminals, but many applications cannot operate effectively due to the CPU performance or energy constraints of mobile devices.
发明内容：Invention content:
为了克服上述背景技术的缺陷，本发明提供一种基于移动云环境低能耗和负载均衡的计算迁移方法和装置，能实现低能耗和负载均衡。In order to overcome the above-mentioned defects in the background technology, the present invention provides a computing migration method and device based on low energy consumption and load balancing in a mobile cloud environment, which can realize low energy consumption and load balancing.
为了解决上述技术问题,本发明的所采用的技术方案为：In order to solve the problems of the technologies described above, the adopted technical solution of the present invention is:
一种基于移动云环境低能耗和负载均衡的计算迁移方法，从云端服务器和移动终端获取影响数据流应用程序划分的因素值，结合数据流应用程序划分策略，动态的对数据流应用程序进行划分，将移动终端数据流应用程序迁移到云端服务器执行或将云端服务器应用程序迁移到移动终端执行；因素值包括从云端服务器获取的云端服务器当前负载和从移动终端获取的当前电量、CPU负载、网络带宽和可用内存空间。A calculation migration method based on low energy consumption and load balancing in the mobile cloud environment, which obtains the factor values affecting the division of data stream applications from cloud servers and mobile terminals, and dynamically divides data stream applications in combination with the division strategy of data stream applications , migrate the mobile terminal data stream application program to the cloud server for execution or migrate the cloud server application program to the mobile terminal for execution; factor values include the current load of the cloud server obtained from the cloud server and the current power, CPU load, and network obtained from the mobile terminal bandwidth and available memory space.
较佳地，数据流应用程序划分策略包括：判断移动终端剩余电量是否低于预先设定的阈值a，若是，则将计算时间在t0以上的数据流应用程序组件迁移到云端去执行，将计算时间要求小于t0的数据流应用程序组件放在移动终端执行；若否，则继续当前的划分策略运行数据流应用程序；Preferably, the data flow application division strategy includes: judging whether the remaining power of the mobile terminal is lower than a preset threshold a, if so, migrating the data flow application components whose calculation time is above t0 to the cloud for execution, and computing The data flow application component whose time requirement is less than t0 is executed on the mobile terminal; if not, continue the current division strategy to run the data flow application;
较佳地，数据流应用程序划分策略包括：判断移动终端CPU负载的变化是否高于预先设定的阈值p，若是，则将计算时间在t1以上的数据流应用程序组件迁移到云端执行，并将计算时间要求小于t1的数据流应用程序组件放在移动终端执行；若否，则继续当前的划分策略运行数据流应用程序；。Preferably, the data flow application division strategy includes: judging whether the change of the CPU load of the mobile terminal is higher than a preset threshold p, if so, migrating the data flow application components whose calculation time is above t1 to the cloud for execution, and Execute the data stream application program components whose calculation time is less than t1 on the mobile terminal; if not, continue the current division strategy to run the data stream application program;
较佳地，判断移动终端与云端之间带宽变化是否高于预先设定的阈值b时，若是，则将通讯时间大于t2的数据流应用程序组件放在移动端执行，将通讯时间小于t2的数据流应用程序组件放在云端执行；若否，则继续当前的划分策略运行数据流应用程序。Preferably, when judging whether the change in bandwidth between the mobile terminal and the cloud is higher than the preset threshold b, if so, execute the data stream application program components whose communication time is greater than t2 on the mobile terminal, and execute the data flow application program components whose communication time is less than t2 The data flow application component is executed on the cloud; if not, the current division strategy continues to run the data flow application.
较佳地，判断移动端的可用内存是否小于预先设定的阈值s，若是，则将所需内存大小在m以上的数据流应用程序组件迁移到云端执行，将所需内存大小在m以下的数据流应用程序组件放在移动端执行；若否，则继续当前的划分策略运行数据流应用程序。Preferably, it is judged whether the available memory of the mobile terminal is less than the preset threshold s, and if so, the data flow application components with the required memory size above m are migrated to the cloud for execution, and the data flow application components with the required memory size below m are migrated to the cloud for execution. The stream application component is executed on the mobile terminal; if not, the current division strategy continues to run the data stream application.
较佳地，判断服务器端的负载是否大于预先设定的阈值l，若是，则将计算时间在t3以上的数据流应用程序组件迁移到移动端执行，将计算时间要求小于t3的数据流应用程序组件放在云端执行；若否，则继续当前的划分策略运行数据流应用程序。Preferably, it is judged whether the load on the server side is greater than a preset threshold 1, and if so, the data flow application components whose calculation time is longer than t3 are migrated to the mobile terminal for execution, and the data flow application components whose calculation time is required to be less than t3 Execute on the cloud; if not, continue to run the data flow application with the current division strategy.
较佳地，阈值a、p、b、s和l是在装置内预先设定或人工输入的。Preferably, the thresholds a, p, b, s and l are preset in the device or input manually.
本发明还提供一种基于移动云环境低能耗和负载均衡的计算迁移装置，包括因素值获取模块、数据流应用程序划分决策模块和数据流应用程序划分执行模块；因素值获取模块用于从云端和移动端获取因素值，并将因素值输入数据流应用程序划分决策模块；数据流应用程序划分决策模块将因素值结合内部存储的数据流应用程序划分策略向数据流应用程序划分执行模块输出划分决策；数据流应用程序划分执行模块执行从数据流应用程序划分划分决策模块接收到的数据流应用程序划分决策。The present invention also provides a computing migration device based on low energy consumption and load balance in a mobile cloud environment, including a factor value acquisition module, a data stream application division decision-making module, and a data stream application division execution module; the factor value acquisition module is used to obtain data from the cloud and the mobile terminal to obtain the factor value, and input the factor value into the data flow application division decision-making module; the data flow application division decision-making module combines the factor value with the internally stored data flow application division strategy to the data flow application division execution module to output the division Decision-making; the dataflow application partition execution module executes the dataflow application partition decision received from the dataflow application partition partition decision module.
较佳地，因素值获取模块从云端服务器获取云端服务器的当前负载，从移动终端获取移动终端的当前电量、CPU负载、网络带宽和可用内存空间。Preferably, the factor value obtaining module obtains the current load of the cloud server from the cloud server, and obtains the current power, CPU load, network bandwidth and available memory space of the mobile terminal from the mobile terminal.
较佳地，数据流应用程序划分决策模块内存储的数据流应用程序划分策略包括：依据移动终端剩余电量进行决策，判断移动终端剩余电量是否高于预先设定的阈值a，若是，则将计算时间在t0以上的数据流应用程序组件迁移到云端去执行，将计算时间要求小于t0的数据流应用程序组件放在移动终端执行；若否，则继续当前的划分策略运行数据流应用程序；或依据移动终端CPU负载的变化进行决策，判断移动终端CPU负载的变化是否高于预先设定的阈值p，若是，则将计算时间在t1以上的数据流应用程序组件迁移到云端执行，并将计算时间要求小于t1的数据流应用程序组件放在移动终端执行；若否，则继续当前的划分策略运行数据流应用程序；或依据移动终端与云端之间带宽变化进行决策，判断移动终端与云端之间带宽变化是否高于预先设定的阈值b时，若是，则将通讯时间大于t2的数据流应用程序组件放在移动端执行，将通讯时间小于t2的数据流应用程序组件放在云端执行；若否，则继续当前的划分策略运行数据流应用程序；或依据移动终端的可用内存进行决策，判断移动端的可用内存是否小于预先设定的阈值s，若是，则将所需内存大小在m以上的数据流应用程序组件迁移到云端执行，将所需内存大小在m以下的数据流应用程序组件放在移动端执行；若否，则继续当前的划分策略运行数据流应用程序；或依据服务器端的负载进行决策，判断服务器端的负载是否大于预先设定的阈值l，若是，则将计算时间在t3以上的数据流应用程序组件迁移到移动端执行，将计算时间要求小于t3的数据流应用程序组件放在云端执行；若否，则继续当前的划分策略运行数据流应用程序；阈值a、p、b、s和l是在装置内预先设定或人工输入的。Preferably, the data flow application division strategy stored in the data flow application division decision module includes: making decisions based on the remaining power of the mobile terminal, judging whether the remaining power of the mobile terminal is higher than a preset threshold a, and if so, calculate Migrate the data flow application components whose time is above t0 to the cloud for execution, and execute the data flow application components whose calculation time is less than t0 on the mobile terminal; if not, continue the current division strategy to run the data flow application; or Make a decision based on the change of the CPU load of the mobile terminal, and judge whether the change of the CPU load of the mobile terminal is higher than the preset threshold p. The data flow application components whose time requirement is less than t1 are executed on the mobile terminal; if not, continue the current division strategy to run the data flow application; or make decisions based on the bandwidth change between the mobile terminal and the cloud, and judge If the inter-bandwidth change is higher than the preset threshold b, if yes, execute the data stream application components with a communication time greater than t2 on the mobile terminal, and execute the data stream application components with a communication time less than t2 on the cloud; If not, continue the current partitioning strategy to run the data flow application; or make a decision based on the available memory of the mobile terminal to determine whether the available memory of the mobile terminal is less than the preset threshold s, and if so, set the required memory size above m Migrate the data flow application components to the cloud for execution, and execute the data flow application components with the required memory size below m on the mobile terminal; if not, continue to run the data flow application with the current division strategy; Make a decision on the load to determine whether the load on the server side is greater than the preset threshold l, if so, migrate the data flow application components whose calculation time is above t3 to the mobile terminal for execution, and transfer the data flow application components whose calculation time is less than t3 Execute on the cloud; if not, continue the current division strategy to run the data flow application program; the thresholds a, p, b, s and l are preset in the device or input manually.
本发明通过分析影响数据流应用程序划分的因素，对移动终端数据流应用程序做出划分处理，包括对云端服务器当前负载和从移动终端获取的当前电量、CPU负载、网络带宽和可用内存空间检测，并依据所获取的结果，对数据流应用程序进行动态的实时调整。通过本发明的方案不仅能减少移动终端的能耗、实现移动终端和云端的负载均衡，同时可以提高移动终端执行数据流应用程序的吞吐量，同时减少响应时间，提高运算效率。The present invention divides the data flow application program of the mobile terminal by analyzing the factors that affect the division of the data flow application program, including detecting the current load of the cloud server and the current power, CPU load, network bandwidth and available memory space obtained from the mobile terminal , and make dynamic real-time adjustments to data streaming applications based on the obtained results. The solution of the present invention can not only reduce the energy consumption of the mobile terminal, realize the load balance between the mobile terminal and the cloud, but also improve the throughput of the mobile terminal to execute the data flow application program, reduce the response time, and improve the computing efficiency.
附图说明Description of drawings
图1为本发明实施例的结构示意图；Fig. 1 is the structural representation of the embodiment of the present invention;
图2为本发明实施例的流程图。Fig. 2 is a flowchart of an embodiment of the present invention.
具体实施方式detailed description
下面结合附图和实施例对本发明做进一步的说明。The present invention will be further described below in conjunction with the accompanying drawings and embodiments.
本实施例提供一种基于移动云环境低能耗和负载均衡的计算迁移装置，包括因素值获取模块、数据流应用程序划分决策模块和数据流应用程序划分执行模块(图1)。This embodiment provides a computing migration device based on low energy consumption and load balancing in a mobile cloud environment, including a factor value acquisition module, a data flow application division decision module, and a data flow application division execution module (Figure 1).
一、因素值获取模块用于从云端和移动端获取因素值，并将因素值输入数据流应用程序划分决策模块；因素值获取模块从云端服务器获取云端服务器的当前负载，从移动终端获取移动终端的当前电量、CPU负载、网络带宽和可用内存空间。本实施例的因素值获取模块具体包括云端服务器的当前负载获取部、移动终端的当前电量获取部、移动终端的CPU负载获取部、网络带宽获取部和移动终端的可用内存空间获取部。1. The factor value obtaining module is used to obtain the factor value from the cloud and the mobile terminal, and input the factor value into the data flow application division decision module; the factor value obtaining module obtains the current load of the cloud server from the cloud server, and obtains the mobile terminal load from the mobile terminal. The current power consumption, CPU load, network bandwidth and available memory space. The factor value acquisition module in this embodiment specifically includes the current load acquisition unit of the cloud server, the current power acquisition unit of the mobile terminal, the CPU load acquisition unit of the mobile terminal, the network bandwidth acquisition unit and the available memory space acquisition unit of the mobile terminal.
二、数据流应用程序划分决策模块将因素值结合内部存储的数据流应用程序划分策略向数据流应用程序划分执行模块输出划分决策；2. The data stream application division decision-making module outputs the division decision to the data stream application division execution module by combining the factor value with the internally stored data stream application division strategy;
数据流应用程序划分决策模块内存储的数据流应用程序划分策略包括以下几种：The data flow application division strategy stored in the data flow application division decision module includes the following types:
依据移动终端剩余电量进行决策，判断移动终端剩余电量是否低于预先设定的阈值a，若是，则将计算时间在t0以上的数据流应用程序组件迁移到云端去执行，将计算时间要求小于t0的数据流应用程序组件放在移动终端执行；若否，则继续当前的划分策略运行数据流应用程序；Make decisions based on the remaining power of the mobile terminal, and judge whether the remaining power of the mobile terminal is lower than the preset threshold a, if so, migrate the data stream application components with a calculation time above t0 to the cloud for execution, and reduce the calculation time to less than t0 The data flow application component of the mobile terminal is executed; if not, the current division strategy is continued to run the data flow application;
或依据移动终端CPU负载的变化进行决策，判断移动终端CPU负载的变化是否高于预先设定的阈值p，若是，则将计算时间在t1以上的数据流应用程序组件迁移到云端执行，并将计算时间要求小于t1的数据流应用程序组件放在移动终端执行；若否，则继续当前的划分策略运行数据流应用程序；Or make a decision based on the change of the CPU load of the mobile terminal, and judge whether the change of the CPU load of the mobile terminal is higher than the preset threshold p, if so, migrate the data flow application components whose calculation time is above t1 to the cloud for execution, and The data flow application components whose calculation time is required to be less than t1 are executed on the mobile terminal; if not, continue the current division strategy to run the data flow application;
或依据移动终端与云端之间带宽变化进行决策，判断移动终端与云端之间带宽变化是否高于预先设定的阈值b时，若是，则将通讯时间大于t2的数据流应用程序组件放在移动端执行，将通讯时间小于t2的数据流应用程序组件放在云端执行；若否，则继续当前的划分策略运行数据流应用程序；当依据次方案进行决策时，移动终端和云端处于同一种网络类型之下；Or make a decision based on the bandwidth change between the mobile terminal and the cloud, and determine whether the bandwidth change between the mobile terminal and the cloud is higher than the preset threshold b, if so, put the data flow application component with a communication time greater than t2 on the mobile Execute on the terminal, put the data flow application components whose communication time is less than t2 on the cloud; if not, continue the current division strategy to run the data flow application; when making decisions according to the sub-plan, the mobile terminal and the cloud are in the same network under type;
或依据移动终端的可用内存进行决策，判断移动端的可用内存是否小于预先设定的阈值s，若是，则将所需内存大小在m以上的数据流应用程序组件迁移到云端执行，将所需内存大小在m以下的数据流应用程序组件放在移动端执行；若否，则继续当前的划分策略运行数据流应用程序；Or make a decision based on the available memory of the mobile terminal to determine whether the available memory of the mobile terminal is less than the preset threshold s, if so, migrate the data flow application components with the required memory size above m to the cloud for execution, and transfer the required memory Data flow application components whose size is below m are executed on the mobile terminal; if not, continue to run the data flow application with the current division strategy;
或依据服务器端的负载进行决策，判断服务器端的负载是否大于预先设定的阈值l，若是，则将计算时间在t3以上的数据流应用程序组件迁移到移动端执行，将计算时间要求小于t3的数据流应用程序组件放在云端执行；若否，则继续当前的划分策略运行数据流应用程序。Or make a decision based on the load on the server side, and judge whether the load on the server side is greater than the preset threshold l, if so, migrate the data stream application components whose calculation time is above t3 to the mobile terminal for execution, and reduce the data whose calculation time is less than t3 The streaming application components are executed on the cloud; if not, continue to run the data streaming application with the current division strategy.
以上决策方案中的阈值a、p、b、s和l是在装置内预先设定的，或者是后期人工输入的。The thresholds a, p, b, s, and l in the above decision-making scheme are preset in the device, or are manually input later.
本模块的功能包括主要是按照数据流应用程序迁移策略模块所确定的划分结果将部分组件放到云端执行；对数据流应用程序迁移策略模块所确定的划分结果进行评估并调整划分结果向目标靠近，对移动终端因素获取模块进行实时监控，若因素有改变则需调整划分策略。对云端服务器因素获取模块进行实时监控从而动态调整划分策略，The functions of this module include mainly placing some components on the cloud for execution according to the division results determined by the data flow application migration strategy module; evaluating the division results determined by the data flow application migration strategy module and adjusting the division results to approach the target , to monitor the mobile terminal factor acquisition module in real time, if the factor changes, the division strategy needs to be adjusted. Real-time monitoring of the cloud server factor acquisition module to dynamically adjust the division strategy,
三、数据流应用程序划分执行模块执行从数据流应用程序划分决策模块接收到的数据流应用程序划分决策。3. The data stream application division execution module executes the data stream application division decision received from the data stream application division decision module.
四、以移动终端剩余电量为例说明上述装置的工作方法如下(图2)：4. Take the remaining power of the mobile terminal as an example to illustrate the working method of the above-mentioned device as follows (Fig. 2):
步骤1，因素获取模块从云端服务器和移动终端获取影响数据流应用程序划分的因素值，即移动终端的剩余电量，输送给数据流应用程序划分决策模块；实践中，因素值包括从云端服务器获取的云端服务器当前负载和从移动终端获取的当前电量、CPU负载、网络带宽和可用内存空间。Step 1, the factor acquisition module obtains the factor value affecting the division of data flow applications from the cloud server and mobile terminal, that is, the remaining power of the mobile terminal, and sends it to the data flow application division decision module; in practice, the factor value includes obtaining from the cloud server The current load of the cloud server and the current power, CPU load, network bandwidth and available memory space obtained from the mobile terminal.
步骤2，数据流应用程序划分决策模块将所获取移动终端剩余电量结合数据流应用程序划分策略，动态的对数据流应用程序进行划分，判断剩余电量是否低于预先设定的阈值a，本实施例取该阈值为总电量的30％；若是，则进入步骤3，若否，则进入步骤4；Step 2, the data flow application division decision-making module dynamically divides the data flow application program by combining the obtained remaining power of the mobile terminal with the data flow application division strategy, and judges whether the remaining power is lower than the preset threshold a. For example, take the threshold value as 30% of the total electricity; if yes, go to step 3, if not, go to step 4;
步骤3，将计算时间在t0以上的数据流应用程序组件迁移到云端去执行，将计算时间要求小于t0的数据流应用程序组件放在移动终端执行，并进入步骤5；Step 3. Migrate the data flow application components whose calculation time is longer than t0 to the cloud for execution, and execute the data flow application components whose calculation time is less than t0 on the mobile terminal, and proceed to step 5;
步骤4，则继续当前的划分策略运行数据流应用程序，并进入步骤5；In step 4, continue to run the data flow application with the current division strategy, and proceed to step 5;
步骤5，将得出的划分策略输送至数据流应用程序划分执行模块执行；Step 5, delivering the obtained division strategy to the data flow application division execution module for execution;
回到步骤1，进一步获取各项因素值，进行实时检测以调整划分结果同时将结果朝目标靠近。Go back to step 1, further obtain the values of various factors, and perform real-time detection to adjust the division results and move the results closer to the target.
另外本实施例还可以参照云端服务器当前负载和移动终端的CPU负载、网络带宽和可用内存空间对数据流应用程序进行划分。In addition, in this embodiment, the data stream application program may be divided according to the current load of the cloud server and the CPU load, network bandwidth, and available memory space of the mobile terminal.
如，步骤3为判断当移动终端当前网络带宽变化是否超过20％时，若是，说明此时网络带宽不太稳定，转到步骤4并以新的划分策略继续执行数据流应用程序。For example, step 3 is to judge whether the current network bandwidth of the mobile terminal changes by more than 20%, if so, it indicates that the network bandwidth is not stable at this time, go to step 4 and continue to execute the data flow application program with the new division strategy.
应当理解的是，对本领域普通技术人员来说，可以根据上述说明加以改进或变换，而所有这些改进和变换都应属于本发明所附权利要求的保护范围。It should be understood that those skilled in the art can make improvements or changes based on the above description, and all these improvements and changes should belong to the protection scope of the appended claims of the present invention.
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