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Security-aware service migration for tactical mobile micro-clouds

机译:用于战术移动微云的安全感知服务迁移

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Mobile micro-clouds (MMCs), which are small cloud-like infrastructures that can host services for mobile users, provide a promising approach to deliver data and computation to users in low bandwidth/high latency networks. In this work, we take a step towards security-aware service migration for multiple servers for MMC in tactical environments. As a fundamental model, we consider two users sharing a cluster of MMCs and moving between coverage areas of different MMCs according to random walk. We formulate the problem using a finite horizon Markov Decision Process (MDP). Due to the coupling between users due to security (and possibly interference) costs, we observe that the problem is significantly more complex compared with the non-security-aware single user service migration problem studied in the literature, even in the simplest case of two users. Accordingly, we consider efficient control algorithms which aim to minimize time average costs. Particularly, we propose a modified myopic policy which aims to reduce time average costs by steering operation towards settings which would reduce the likelihood of future security cost increases, by proactively keeping the services distant. Our numerical results demonstrate that our modified myopic policy outperforms other policies in terms of average cost for various settings.
机译:移动微云(MMC),它是可以托管移动用户服务的小型云的基础设施,提供了一种有希望的方法来向低带宽/高延迟网络提供数据和计算。在这项工作中,我们在战术环境中为MMC的多个服务器迈进了安全感知服务迁移。作为一个基本模型,我们考虑两个用户共享一个MMC集群并根据随机步行的不同MMC的覆盖区域之间移动。我们使用有限地平线马尔可夫决策过程(MDP)制定问题。由于用户之间的耦合由于安全性(和可能的干扰)成本,我们观察到与文献中研究的非安全感知单用户服务迁移问题相比,问题显着更复杂,即使在最简单的两种情况下也是如此用户。因此,我们考虑了有效的控制算法,其目的是最小化时间平均成本。特别是,我们提出了一种修改的近视政策,旨在通过主动保持遥远的服务来减少将降低未来安全成本的可能性的设置来降低时间平均成本。我们的数值结果表明,我们修改的近视政策在各种环境的平均成本方面优于其他政策。

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