Recent years have seen the rapid popularity of serverless computing, benefiting from its seamless scalability and pay-as-you-go charging model. Despite recent efforts to enhance function cold-start performance by utilizing snapshot and working set mechanisms, the existing methods still suffered considerable overheads in end-to-end response time as functions' inputs varied. In this paper, we propose Faast, a novel solution designed to improve function response time by enhancing virtual machine snapshot-based startup while guaranteeing function execution performance. Our system introduces a preparation phase to generate a lightweight working set, which excludes stale pages that do not require loading from snapshot files for each function to expedite startup. Additionally, Faast facilitates network connectivity for the snapshot by implementing NAT within the virtio-net device model bypassing the time-consuming network namespace setup. To guarantee execution performance, a divergent page fault handling mechanism is designed to address page faults related to stale and non-stale pages separately, effectively mitigating sluggish disk I/O accesses. Faast also incrementally adapts the working set file across various function invocations to bolster functions' resilience to diverse inputs. Extensive experiments demonstrate that Faast reduces function end-to-end time by up to 63% compared to the state-of-the-art.

In this paper, we investigate the problem of achieving efficient memory resource management for unikernel-based virtual machines (uVMs), where unikernels are running as the operating systems of the VMs. Through extensive experiments, we first demonstrate that existing VM memory management mechanisms are unsuitable for uVMs. Then, we propose MEUNIK, a system that aims to achieve high memory management efficiency or uVMs. The four key mechanisms of MEUNIK are designed to address the problems we find in existing solutions. We have implemented a prototype MEUNIK system based on the Xen hypervisor and performed extensive evaluation experiments on three groups of uVMs, which are constructed based on a variety of programs and applications, including fifteen small benchmark programs, four complex server applications, and two network-operation-heavy programs. The evaluation results show that our system achieves the design goals with minimal overhead.

We show that many popular mobile services suffer from excessive network bandwidth consumption. The root cause is that the existing mobile/cloud communication interfaces are designed and optimized for service providers rather than end user devices. Solving the problem is challenging, because of the conflicted interests of service providers and mobile devices. We propose Edge-hosted Personal Service (EPS), with which device-oriented solutions can be easily deployed without affecting service providers. EPS also enjoys other notable advantages, including enabling new mobile services, reducing loads on the cloud, and benefiting delay-sensitive applications. We demonstrate the usefulness of EPS by designing ETA (Edge-based web Traffic Adaptation), an effective solution for the excessive bandwidth consumption problem, and deploy ETA with a prototype EPS system. By exploring lightweight virtualization techniques, our EPS prototype system is highly scalable in terms of concurrent EPS instances, and secure in terms of resource isolation. The real-world evaluation shows that our ETA EPS can effectively reduce bandwidth for mobile devices with small overheads.

Cloud storage usages are becoming increasingly popular on mobile devices. Through an extensive motivation study, we find that cloud storage accesses from mobile apps suffer from several notable problems that undermine usage experiences. The root cause is that the way of cloud storage providers deploying their services onto mobile devices relies on app developers for the correct and appropriate implementations and lacks the ability of monitoring and servicing client-side cloud storage accesses. We propose StoArranger, a practical system framework that solves the problems by coordinating, rearranging, and transforming cloud storage communications on mobile devices. We have prototyped the proposed system using two different implementation approaches. We discuss our experiences of the implementations in the paper. The real-app evaluation experiments show that StoArranger can significantly improve mobile cloud storage access efficiency with little overheads.

Being powered by battery and the reliance on expensive cellular data while users are on the move are holding smart mobile devices from being widely used in those long-lasted, computation-intensive, or highly network-reliant usage scenarios. In the meantime, more and more mobile workloads and optimizations now rely on the cloud, such as mobile cloud offloading, cloud-based mobile web optimization, and cloud-based network traffic redundancy reduction. However, it is hard to perform large-scale and personalized support or optimization for mobile workloads without significant computation resource increase on the cloud, as well as higher bandwidth requirement on the networks. We target solving the above two problems by enabling edge-hosed personalized services (EPS for short). The idea of EPS is twofold. One is enabling developer-customizable and power-and-traffic-efficient network communication on the "last-hop" communication between mobile devices and the network edge. The other is distributing cloud services for mobile workloads to network edge, so that they can be done on a personalized basis, while enjoying much lower communication latency to/from mobile devices.

Smartphone device inputs, such as inputs from touchscreen, sensors, and GPS, carry sensitive user information, but are vulnerable to passive and active attacks. We present our ongoing design and implementation of SDIF, a Secure Device Input Framework for smartphones. The core components of SDIF are a small and dedicated bare-metal hypervisor built using ARM hardware virtualization support and a user-space sandbox framework. They collectively ensures SDIF's support for unmodified OSes and apps. SDIF guarantees the secure device inputs from hardware to target applications with two key designs. The first is a design of a secure path for input data to be delivered from input device drivers to target applications. The second is a design of trusted device data reading, which ensures input data generated by hardware is faithfully put to device driver memory.