在移动自组网络中,节点的移动或是无线连接的中断会引起频繁的网络分割.因此,访问节点并获取相应的数据是相当困难的.通过理论和统计分析得到特定运动模型对应的网络分割模式,建立了网络分割模式与数据复制有效性之间的联系,推导出了理想复制方法在特定网络环境下能够获得的数据可用性的上限,也指出纯随机复制方法可提高数据可用性.基于上述分析,提出了一种新的数据复制方法RICMAN(replication in intermittently connected mobile ad hoc networks)来提高断续性连接移动自组网络的数据可用性.该方法将所需数据以副本的形式复制到一系列拓扑结构相对稳定和资源充足的特定节点上,为处于同一分区的节点提供数据服务.副本的分布和更新基于半概率性数据分发协议实现.此协议能够识别可能的跨越多个网络分区的运动节点,由这些节点传播数据及其更新,从而在断续性连接网络中最大化数据传榆.为了保持副本的一致性,该方法使用一种弱一致性模型——最终一致性模型,以确保所有的更新最终在有限的延迟内传送到所有的副本处.仿真结果显示,RICMAN方法能够以较小的开销获取较高的数据可用性羟过优化后,数据可用性仅比理想上限低10%~15%.
Accessing data in a intermittently connected mobile ad hoc networks is a challenging problem that is caused by frequent network partitions due to node mobility and to impairments of wireless communications. This partitioning pattern is studied by examining the statistics of network partitions for a number of mobility models. This paper then establishes the relationship between the network partitioning pattern and the effectiveness of the data replication scheme, and then gives an upper bound of data availability, achieved by an ideal replication scheme under standard operational conditions. The data availability of a totally random scheme can achieve is also given. Based on these results, a novel replication scheme, RICMAN (replication in intermittently connected mobile ad hoc networks), which takes into account the fact that the network is often partitioned into smaller and uses only intermittent connectivity, thanks to mobile nodes traveling across partition, is proposed. In RICMAN, data items are replicated with the nodes using rather stable neighboring topology and with enough resources. A semi-probabilistic data disseminating protocol is employed to distribute the replicas and propagate the updates and can identify the potential mobile nodes traveling across partitions to maximize data delivery. To maintain replica consistency, a weak, eventual consistency model is utilized to ensure all updates eventually propagate to all replicas in a finite delay. Simulation results demonstrate that RICMAN scheme can achieve high data availability with low overhead. With optimized parameters, the data availability is just 10%-15% lower than the upper bound under certain network conditions.