This paper presents svc-hook, a system call hook mechanism for the ARM64 CPU architecture. To apply system call hooks to a program, svc-hook performs binary rewriting, and specifically, it replaces svc that is a CPU instruction invoking a system call.

This paper explores a practical means to employ Data Plane Development Kit (DPDK), a kernel-bypassing framework for packet processing, in resource-limited multi-tenant edge data centers. The problem is that the traditional virtual CPU (vCPU) schedulers are not well compatible with the event detection model of DPDK, which needs to monopolize a physical CPU (pCPU) for NIC register polling. Consequently, DPDK-applied systems running on consolidated Virtual Machines (VMs), a common setup at edges, fail to achieve low serving latencies regardless of the use of DPDK. Toward edge data center providers, this work presents a new vCPU scheduling policy named Polling vCPU Consolidation (PvCC) which runs DPDK-applied systems on dedicated pCPUs adopting microsecond-scale time slices. Along with this, we introduce a mechanism to determine an appropriate number of dedicated pCPUs according to customers' demands represented through a newly introduced vCPU scaling API enabling customers to scale up/down the vCPUs of their VMs at runtime. Our experiments show that PvCC allows DPDK-applied systems running on consolidated VMs to achieve low serving latencies, and our vCPU scaling API enables customers to adjust CPU resource assignment according to the incoming request rate and providers to effectively assign spare pCPUs to VMs executing non-latency-sensitive best-effort tasks.

This paper explores Exit-Less, Isolated, and Shared Access (ELISA), a novel in-memory object sharing scheme for Virtual Machines (VMs). ELISA has the isolation advantage over the shared memory directly exposed to guest VMs while its overhead is smaller than that of host-interposition relying on the costly exit from the VM context. In a nutshell, ELISA isolates shared in-memory objects by Extended Page Table (EPT) separation, and a guest VM accesses them by switching the EPT context using VMFUNC, a low-overhead CPU instruction of Intel CPUs. Our experiment shows that the overhead of ELISA is 3.5 times smaller than that of VMCALL-oriented host-interposition. We demonstrate the benefits of ELISA through two use cases; by replacing VMCALL with ELISA, a VM networking system and an in-memory key-value store exhibit 163% and 64% higher performance respectively.

Network Function Virtualization has been touted as the silver bullet for tackling a number of operator problems, including vendor lock-in, fast deployment of new functionality, converged management, and lower expenditure since packet processing runs on inexpensive commodity servers. The reality, however, is that, in practice, it has proved hard to achieve the stable, predictable performance provided by hardware middleboxes, and so operators have essentially resorted to throwing money at the problem, deploying highly underutilized servers (e.g., one NF per CPU core) in order to guarantee high performance during peak periods and meet SLAs.

Containers are in great demand because they are lightweight when compared to virtual machines. On the downside, containers offer weaker isolation than VMs, to the point where people run containers in virtual machines to achieve proper isolation. In this paper, we examine whether there is indeed a strict tradeoff between isolation (VMs) and efficiency (containers). We find that VMs can be as nimble as containers, as long as they are small and the toolstack is fast enough.

Video streaming dominates the Internet's overall traffic mix, with reports stating that it will constitute 90% of all consumer traffic by 2019. Most of this video is delivered by Content Delivery Networks (CDNs), and, while they optimize QoE metrics such as buffering ratio and start-up time, no single CDN provides optimal performance. In this paper we make the case for elastic CDNs, the ability to build virtual CDNs on-the-fly on top of shared, third-party infrastructure at a scale. To bring this idea closer to reality we begin by large-scale simulations to quantify the effects that elastic CDNs would have if deployed, and build and evaluate MiniCache, a specialized, minimalistic virtualized content cache that runs on the Xen hypervisor. MiniCache is able to serve content at rates of up to 32 Gb/s and handle up to 600K reqs/sec on a single CPU core, as well as boot in about 90 milliseconds on x86 and around 370 milliseconds on ARM32.

In sensing systems, data compression is a promised way to save energy because it reduces the rate of data transmission, but less attention has been paid to the underlying task scheduling algorithms. We present a Double Rate Bundle Scheduling algorithm (DRBS) that maximizes the sleep state period of the CPU to reduce energy consumption. Our prototype implementation in a Mote device improves energy efficiency up to 8% compared to existing algorithms.