Formative Impact of Gauss Markov Mobility Model on Data Availability in MANET

摘要

Recent advancements in wireless communication and the miniaturization of computers support communications among mobile nodes connected to each other by one-hop or multihop links. In Mobile Ad hoc Network (MANET), mobile nodes need to share and access data held by other mobile nodes in applications such as collaborative rescue operations at a disaster site, military operations and sensor networks. Since, disconnections often occur, data in two separated networks become inaccessible to each other. Preventing the deterioration of data availability at the point of network partitioning is a very significant issue. Data replication and data diffusion (dissemination) address the issue of data unavailability. The results of these conventional researches have revealed that mobility heavily affects data availability. The influence of mobility on data availability is determined from various perspectives without using specific applications or specific data replication/diffusion protocols. But several general metrics like the average size of the partitions, distribution of partition sizes, the size of partitions to which the node belongs, the change in size of partition to which the node belongs, the total number of connected nodes to a node, the no of nodes to which a node can disseminate its data and the distribution of the connected nodes are analyzed to determine the impact of mobility on the data availability. The values of proposed metrics are computed and compared for both Gauss Markov and RPGM mobility models. From the simulation results, it is known that the Gauss Markov Mobility Model works well in terms of the data storage capacity and partition stability. For designing the data replication protocol it is effective to share the data among the nodes in the same partition and for designing the data dissemination protocol, aggressive data dissemination is effective in terms of distribution rapidness.