The diffusion of useful information in generalized networks, such as those consisting of wireless physical substrates and social network overlays is very important for theoretical and practical applications. Contrary to previous works, we focus on the impact of user interest and its features (e.g., interest periodicity) on the dynamics and control of diffusion of useful information within such complex wireless-social systems. By considering the impact of temporal and topical variations of users interests, e.g., seasonal periodicity of interest in summer vacation advertisements which spread more effectively during Spring-Summer months, we develop an epidemic-based mathematical framework for modeling and analyzing such information dissemination processes and use three indicative operational scenarios to demonstrate the solutions and results that can be obtained by the corresponding differential equation-based formalism. We then develop an optimal control framework subject to the above information diffusion modeling that allows controlling the trade-off between information propagation efficiency and the associated cost, by considering and leveraging on the impact that user interests have on the diffusion processes. By analysis and extensive simulations, significant outcomes are obtained on the impact of each network layer and the associated interest parameters on the dynamics of useful information diffusion. Furthermore, several behavioral properties of the optimal control of the useful information diffusion with respect to the number of infected/informed nodes and the evolving user interest are shown through analysis and verified via simulations. Specifically, a key finding is that low interest-related diffusion can be aided by utilizing proper optimal controls. Our work in this paper paves the way towards this user-centered information diffusion framework.

中文翻译：

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在通用网络中，由用户兴趣决定的信息扩散的分析和控制。

有用信息在广义网络中的传播，例如由无线物理基础结构和社交网络覆盖层组成的网络，对于理论和实际应用非常重要。与以前的工作相反，我们关注用户兴趣及其特征（例如，兴趣周期性）对这种复杂的无线社交系统内有用信息的传播动态和控制的影响。通过考虑用户兴趣的时间和主题变化的影响（例如，暑假广告中兴趣的季节性变化，这种变化在春夏季月份更有效地传播），我们开发了一种基于流行病的数学框架，用于对此类信息传播过程进行建模和分析，并使用三个指示性操作方案来演示可通过相应的基于微分方程的形式主义获得的解决方案和结果。然后，我们根据上述信息扩散模型开发一个最佳控制框架，该框架允许通过考虑和利用用户兴趣对扩散过程的影响来控制信息传播效率和相关成本之间的折衷。通过分析和广泛的模拟，可以获得有关每个网络层的影响以及相关的兴趣参数对有用信息传播的动态的显着结果。此外，通过分析显示了有用信息传播的最佳控制相对于受感染/已通知节点的数量以及不断发展的用户兴趣的几种行为特性，并通过仿真进行了验证。具体而言，一个关键发现是，通过利用适当的最佳控制手段，可以降低与利益相关的低扩散。我们在本文中的工作为建立以用户为中心的信息传播框架铺平了道路。