College of Information Sciences and Technology, Donghua University, Shanghai, China.
PLoS One. 2011;6(6):e20949. doi: 10.1371/journal.pone.0020949. Epub 2011 Jun 20.
Some of the approaches have been developed to retrieve data automatically from one or multiple remote biological data sources. However, most of them require researchers to remain online and wait for returned results. The latter not only requires highly available network connection, but also may cause the network overload. Moreover, so far none of the existing approaches has been designed to address the following problems when retrieving the remote data in a mobile network environment: (1) the resources of mobile devices are limited; (2) network connection is relatively of low quality; and (3) mobile users are not always online. To address the aforementioned problems, we integrate an agent migration approach with a multi-agent system to overcome the high latency or limited bandwidth problem by moving their computations to the required resources or services. More importantly, the approach is fit for the mobile computing environments. Presented in this paper are also the system architecture, the migration strategy, as well as the security authentication of agent migration. As a demonstration, the remote data retrieval from GenBank was used to illustrate the feasibility of the proposed approach.
有些方法已经被开发出来，可以从一个或多个远程生物数据源自动检索数据。然而，它们大多数都要求研究人员保持在线状态并等待返回的结果。后者不仅需要高可用性的网络连接，还可能导致网络过载。此外，到目前为止，还没有任何现有的方法旨在解决在移动网络环境中检索远程数据时的以下问题：（1）移动设备的资源有限；（2）网络连接的质量相对较低；（3）移动用户并非总是在线。为了解决上述问题，我们将代理迁移方法与多代理系统集成在一起，通过将计算迁移到所需的资源或服务来克服高延迟或带宽有限的问题。更重要的是，该方法适用于移动计算环境。本文还介绍了系统架构、迁移策略以及代理迁移的安全认证。作为一个演示，使用从 GenBank 检索远程数据来说明所提出方法的可行性。
