Construction of a Temporal Coherency Preserving Dynamic Data Dissemination Network

In this paper, we discuss various techniques for the efficient organization of a temporal coherency preserving dynamic data dissemination network. The network consists of sources of dynamically changing data, repositories to replicate this data, and clients. Given the temporal coherency properties of the data available at various repositories, we suggest methods to intelligently choose a repository to serve a new client request. The goal is to support as many clients as possible, from the given network. Secondly, we propose strategies to decide what data should reside on the repositories, given the data coherency needs of the clients. We model the problem of selection of repositories for serving each of the clients as a linear optimization problem, and derive its objective function and constraints. In view of the complexity and infeasibility of using this solution in practical scenarios, we also suggest a heuristic solution. Experimental evaluation, using real world data, demonstrates that the fidelity achieved by clients using the heuristic algorithm is close to that achieved using linear optimization. To improve the fidelity further through better load sharing between repositories, we propose an adaptive algorithm to adjust the resource provisions of repositories according to their recent response times. It is often advantageous to reorganize the data at the repositories according to the needs of clients. To this end, we propose two strategies based on reducing the communication and computational overheads. We evaluate and compare the two strategies, analytically, using the expected response time for an update at repositories, and by simulation, using the loss of fidelity at clients, as our performance measure. The results suggest that a considerable improvement in fidelity can be achieved by judicious reorganization.