Reliable Redundant Services Placement in Federated MicroClouds In a battlefield or disaster relief environment, network connectivity ability is unstable and task requirements may change frequently. Federated microclouds are promising for solving problem of service delivery in this dynamic scenario. However, due to the harsh environment and the dynamic feature of federated microclouds, there is a serious risk of service failure. Redundant configuration is an effective method to enhance service reliability. But when determining the placement strategy for an application request containing multiple services, few previous approaches can effectively handle such a highly complex task of redundant services placement under multiple constraints, including resource constraints, communication delay limits and location constraints. In this paper, we study how to reliably place redundant services requested by user on federated microclouds. We first design a twolevel reliability evaluation model to quantitatively measure the reliability of each services placement from the two aspects of node reliability and Shared Risk Domain (SRD) reliability. Second, we propose a Reliable Redundant Services Placement (RRSP) approach to iteratively place each service by using Dynamic Graph Growth (DGG) algorithm. RRSP can determine the current optimal location according to the reliability of nodes and the number of service combinations to find a highly reliable placement strategy in a short time. The evaluation results show that our algorithm can provide more reliable services placement than three other representative algorithms.

Redundant Virtual Machine Placement in Mobile Edge Computing Mobile edge computing (MEC), as an extension of the cloud computing paradigm to edge networks, overcomes some obstacles of traditional mobile cloud computing by offering ultrashort latency and less core network traffic. The edge resources are virtualized to be shared among multiple mobile users. Consolidated server systems using server virtualization involves serious risks of hosting server failures. Redundant virtual machine placement can be an effective countermeasure. This problem has been well solved in cloud computing. However, it is a more nontrivial task to efficiently deploy virtual machines redundantly in MEC networks. To address this issue, a redundant virtual machine placement method in MEC is proposed. Firstly, this method estimates the minimum number of virtual machines required based on the performance requirements of the applications. Then, the redundant virtual machine placement problem is formulated as a combinatorial optimization formulation. Finally, a optimal placement strategy searching algorithm is proposed to determine the optimal location of the virtual machines. The strategy can preserve the minimum configuration in the event of failure of any k edge servers. The experiment results illustrates the effectiveness of our algorithm.