In recent years, edge computing has emerged as a prospective distributed computing paradigm that overcomes several limitations of cloud computing. In the edge computing environment, a service provider can deploy its application instances on edge servers at the edge of the network to serve its own users with low latency. Given a limited budget $\mathcal {K}$K for deploying applications on the edge servers in a particular geographical area, a number of approaches have been proposed very recently to determine the optimal deployment strategy that achieves various optimization objectives, e.g., to maximize the servers’ coverage, to minimize the average network latency, etc. However, the robustness of the services collectively delivered by the service provider’s applications deployed on the edge servers has not been considered at all. This is a critical issue, especially in the highly distributed, dynamic and volatile edge computing environment. In this article, we make the first attempt to tackle this challenge. Specifically, we formulate this Robustness-oriented Edge Application Deployment (READ) problem as a constrained optimization problem and prove its $\mathcal {NP}$NP-hardness. Then, we provide an integer programming based approach named READ-$\mathcal {O}$O for solving this problem precisely. We also provide an approximation algorithm, namely READ-$\mathcal {A}$A, for finding near-optimal solutions to large-scale READ problems efficiently. We prove its approximation ratio is not worse than $\mathcal {K}/2$K/2, which is a constant regardless of the total number of edge servers. We evaluate our approaches experimentally on a widely-used real-world dataset against five representative approaches. The experiment results demonstrate that our approaches can solve the READ problem effectively and efficiently.

中文翻译：

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阅读：边缘计算环境中面向鲁棒性的边缘应用程序部署

近年来，边缘计算已经成为一种前瞻性的分布式计算范式，它克服了云计算的几个限制。在边缘计算环境中，服务提供商可以将其应用程序实例部署在网络边缘的边缘服务器上，以低延迟为自己的用户提供服务。鉴于预算有限$\数学{K}$ķ为了在特定地理区域的边缘服务器上部署应用程序，最近提出了许多方法来确定实现各种优化目标的最佳部署策略，例如，最大化服务器的覆盖范围，最小化平均网络延迟，但是，根本没有考虑部署在边缘服务器上的服务提供商的应用程序共同提供的服务的健壮性。这是一个关键问题，尤其是在高度分布式、动态和易变的边缘计算环境中。在本文中，我们首次尝试应对这一挑战。具体来说，我们将这个面向鲁棒性的边缘应用程序部署（READ）问题表述为一个有约束的优化问题，并证明其$\数学{NP}$NP-硬度。然后，我们提供了一种基于整数规划的方法，名为 READ-$\数学{O}$○为了准确解决这个问题。我们还提供了一种近似算法，即 READ-$\数学{A}$一个，用于有效地找到大规模 READ 问题的近乎最优解决方案。我们证明它的近似比不差于$\数学{K}/2$ķ/2，这是一个常数，与边缘服务器的总数无关。我们在广泛使用的真实世界数据集上针对五种代表性方法对我们的方法进行了实验评估。实验结果表明，我们的方法可以有效且高效地解决 READ 问题。