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The importance of data replication in mobile computing systems for ensuring data availability and integrity, despite mobility challenges such as bandwidth limitations and interference. The document also introduces adaptive clustering as an efficient network architecture for mobile wireless networks, providing spatial reuse of bandwidth and robustness against topological changes. Additionally, the document touches upon the role of file systems in managing data storage and retrieval in computing.
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With the tremendous growth of the portable computing devices and wireless communication, the mobile computing has become extremely popular. The wireless enabled portable computing devices with massive storage capacity and high-end processing capabilities have started to make the extensive use of mobile databases already. The rising popularity in these computing paradigms demands that the mobile computing be reliable enough to ensure the continuous data availability and integrity. However mobility comes at the cost of bandwidth, limited power, security and interference. In modern mobile computing systems data replication has been adopted as an efficient means to ensure the data availability and integrity as well as an effective means to achieve the fault tolerance. Data replication not only ensure the availability of the data but also reduce the communication cost, increase data sharing and increase the safety of the critical data. Furthermore, it also determine when and where (location) to place the replica of data, controlling the number of data replicas over a network for efficient utilisation of the network resources.
In the proposed network architecture, nodes are organised into non overlapping clusters. The clusters are independently controlled, and are dynamically reconfigured as the nodes move. This network architecture has three main advantages.
In computing, a file system(or filesystem) is used to control how data is stored and retrieved. Without a file system, information placed in a storage area would be one large body of data with no way to tell where one piece of information stops and the next begins. By separating the data into individual pieces, and giving each piece a name, the information is easily separated and identified.