Abstract This paper presents enCloud, a new aspect‐oriented trusted service migration with SGX‐enabled cloud VM. Addressing the challenge of reconciling end‐to‐end security with VM migration, enCloud incorporates two key aspects: (1) end‐to‐end security for enclave context migration, and (2) VM abstraction for conventional VM context migration. This paper provides a practical guideline with applicable APIs for trusted service migration. In a case study, enCloud demonstrates effective trusted DB service migration on a cloud VM, achieving end‐to‐end security with minimal trust boundaries. The framework supports pre‐copy live VM migration to minimize service downtime. This paper contributes a concise and practical solution in the form of the enCloud framework for secure service migration.

Kernel samepage merging (KSM) in Linux kernel archive is a memory deduplication scheme that finds duplicate pages and shares the page in order to alleviate memory bottleneck in cloud. However, because the KSM has to scan all pages in memory to find duplicate pages, KSM consumes high CPU cycles and so causes virtual machines (VMs) performance degradation [1]. This degradation of VMs performance is an obstacle in cloud to service real-time applications (i.e. Netflix) [3]. A previous work, CMD [1] proposed page grouping scheme to reduce page comparisons, but it requires special monitoring hardware, XLH [2] enhanced page sharing with the information of guest VM I/O operation. However, the CPU overhead of XLH is still very high - similar to the default KSM. to make KSM more useful, we need an optimization scheme that consume less CPU cycles. Therefore, we first profile the CPU cycle consumption of KSM and the results show that page comparison (28.77%) and page checksum (26.14%) take most of cycles. Based on the results, we propose advanced KSM for cloud computing (AKC) that consumes less CPU cycles than the default KSM. to reduce the number of page comparisons, we apply checksum based RB-tree structure. In addition, AKC decreases page checksum overhead with hardware-accelerated crc32 hash function.

Retention error has been recognized as the most dominant error in MLC (multi-level cell) flash. In this paper, we propose a new approach called PISO (Programming Initial Step Only) to reduce its number. Unlike a normal programming operation, a PISO operation only carries out the first programming-and-verifying step on a programmed cell. As a result, a number of electrons are injected into the cell to compensate its charge loss over time without disturbing its existing data. Further, we build a model to understand the relationship between the number of PISOs and the number of reduced errors. Experimental results from 1y-nm MLC chips show that PISO can efficiently reduce the number of retention errors with a minimal overhead. On average, applying 10 PISO operations each month on a one-year-old MLC chip that has experienced 4K P/E cycles can reduce its retention errors by 21.5% after 3 months.

Enterprise servers require customized solid-state drives (SSDs) to satisfy their specialized I/O performance and reliability requirements. For effective use of SSDs for enterprise purposes, SSDs must be designed considering requirements such as those related to performance, lifetime, and cost constraints. However, SSDs have numerous hardware and software design options, such as flash memory types and block allocation methods, which have not been well analyzed yet, but on which the SSD performance depends. Furthermore, there is no methodology for determining the optimal design for a particular I/O workload. This paper proposes SSD-Tailor, a customization tool for SSDs. SSD-Tailor determines a near-optimal set of design options for a given workload. SSD designers can use SSD-Tailor to customize SSDs in the early design stage to meet the customer requirements. We evaluate SSD-Tailor with nine I/O workload traces collected from real-world enterprise servers. We observe that SSD-Tailor finds near-optimal SSD designs for these workloads by exploring only about 1% of the entire set of design candidates. We also show that the near-optimal designs increase the average I/O operations per second by up to 17% and decrease the average response time by up to 163% as compared to an SSD with a general design.