skip to main content


Title: Fast Function Instantiation with Alternate Virtualization Approaches
This paper focuses on the need for emerging domains such as serverless and in-network computing, where applications are often hosted on virtualized compute instances (e.g., containers and unikernels), to have applications startup as quickly as possible. We provide a qualitative and quantitative analysis of containers and unikernels with regard to the startup time. We analyze these in-depth and identify the key components and their impact under scale on the startup latency. We study how startup time scales as we launch multiple instances concurrently. We study the contribution of popular Container Networking Interfaces (CNIs), to the startup time.  more » « less
Award ID(s):
1763929
NSF-PAR ID:
10299324
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
2021 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN)
Page Range / eLocation ID:
1 to 6
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Burst-parallel serverless applications invoke thousands of short-lived distributed functions to complete complex jobs such as data analytics, video encoding, or compilation. While these tasks execute in seconds, starting and configuring the virtual network they rely on is a major bottleneck that can consume up to 84% of total startup time. In this paper we characterize the magnitude of this network cold start problem in three popular overlay networks, Docker Swarm, Weave, and Linux Overlay. We focus on end-to-end startup time that encompasses both the time to boot a group of containers as well as interconnecting them. Our primary observation is that existing overlay approaches for serverless networking scale poorly in short-lived serverless environments. Based on our findings we develop Particle, a network stack tailored for multi-node serverless overlay networks that optimizes network creation without sacrificing multi-tenancy, generality, or throughput. When integrated into a serverless burst-parallel video processing pipeline, Particle improves application runtime by 2.4--3X over existing overlays. 
    more » « less
  2. 5G edge clouds promise a pervasive computational infrastructure a short network hop away, enabling a new breed of smart devices that respond in real-time to their physical surroundings. Unfortunately, today’s operating system designs fail to meet the goals of scalable isolation, dense multi-tenancy, and high performance needed for such applications. In this paper we introduce EdgeOS that emphasizes system-wide isolation as fine-grained as per-client. We propose a novel memory movement accelerator architecture that employs data copying to enforce strong isolation without performance penalties. To support scalable isolation, we introduce a new protection domain implementation that offers lightweight isolation, fast startup and low latency even under high churn. We implement EdgeOS in a microkernel based OS and demonstrate running high scale network middleboxes using the Click software router and endpoint applications such as memcached, a TLS proxy, and neural network inference. We reduce startup latency by 170X compared to Linux processes, and improve latency by three orders of magnitude when running 300 to 1000 edge-cloud memcached instances on one server. 
    more » « less
  3. With close to native performance, Linux containers are becoming the de facto platform for cloud computing. While various solutions have been proposed to secure applications and containers in the cloud environment by leveraging Intel SGX, most cloud operators do not yet offer SGX as a service. This is likely due to a number of security, scalability, and usability concerns coming from both cloud providers and users. Cloud operators worry about the security guarantees of unofficial SDKs, limited support for remote attestation within containers, limited physical memory for the Enclave Page Cache (EPC) making it difficult to support hundreds of enclaves, and potential DoS attacks against EPC by malicious users. Meanwhile, end users need to worry about careful program partitioning to reduce the TCB and adapting legacy applications to use SGX. We note that most of these concerns are the result of an incomplete infrastructure, from the OS to the application layer. We address these concerns with lxcsgx, which allows SGX applications to run inside containers while also: enabling SGX remote attestation for containerized applications, enforcing EPC memory usage control on a per-container basis, providing a general software TPM using SGX to augment legacy applications, and supporting partitioning with a GCC plugin. We then retrofit Nginx/OpenSSL and Memcached using the software TPM and SGX partitioning to defend against known and potential attacks. Thanks to the small EPC footprint of each enclave, we are able to run up to 100 containerized Memcached instances without EPC swapping. Our evaluation shows the overhead introduced by lxcsgx is less than 6.9% for simple SGX applications, 9.5% for Nginx/OpenSSL, and 20.9% for containerized Memcached. 
    more » « less
  4. This paper describes EdgeNet, a lightweight cloud infrastructure for the edge. We aim to bring as much of the flexibility of open cloud computing as possible to a very lightweight, easily-deployed, software-only edge infrastructure. EdgeNet has been informed by the advances of cloud computing and the successes of such distributed systems as PlanetLab, GENI, G-Lab, SAVI, and V-Node: a large number of small points-of-presence, designed for the deployment of highly distributed experiments and applications. EdgeNet differs from its predecessors in two significant areas: first, it is a software-only infrastructure, where each worker node is designed to run part- or full-time on existing hardware at the local site; and, second, it uses modern, industry-standard software both as the node agent and the control framework. The first innovation permits rapid and unlimited scaling: whereas GENI and PlanetLab required the installation and maintenance of dedicated hardware at each site, EdgeNet requires only a software download, and a node can be added to the EdgeNet infrastructure in 15 minutes. The second offers performance, maintenance, and training benefits; rather than maintaining bespoke kernels and control frameworks, and developing training materials on using the latter, we are able to ride the wave of open-source and industry development, and the plethora of industry and community tutorial materials developed for industry standard control frameworks. The result is a global Kubernetes cluster, where pods of Docker containers form the service instances at each point of presence. 
    more » « less
  5. Purpose Marine transportation has been faced with an increasing demand for containerized cargo during the past decade. Marine container terminals (MCTs), as the facilities for connecting seaborne and inland transportation, are expected to handle the increasing amount of containers, delivered by vessels. Berth scheduling plays an important role for the total throughput of MCTs as well as the overall effectiveness of the MCT operations. This study aims to propose a novel island-based metaheuristic algorithm to solve the berth scheduling problem and minimize the total cost of serving the arriving vessels at the MCT. Design/methodology/approach A universal island-based metaheuristic algorithm (UIMA) was proposed in this study, aiming to solve the spatially constrained berth scheduling problem. The UIMA population was divided into four sub-populations (i.e. islands). Unlike the canonical island-based algorithms that execute the same metaheuristic on each island, four different population-based metaheuristics are adopted within the developed algorithm to search the islands, including the following: evolutionary algorithm (EA), particle swarm optimization (PSO), estimation of distribution algorithm (EDA) and differential evolution (DE). The adopted population-based metaheuristic algorithms rely on different operators, which facilitate the search process for superior solutions on the UIMA islands. Findings The conducted numerical experiments demonstrated that the developed UIMA algorithm returned near-optimal solutions for the small-size problem instances. As for the large-size problem instances, UIMA was found to be superior to the EA, PSO, EDA and DE algorithms, which were executed in isolation, in terms of the obtained objective function values at termination. Furthermore, the developed UIMA algorithm outperformed various single-solution-based metaheuristic algorithms (including variable neighborhood search, tabu search and simulated annealing) in terms of the solution quality. The maximum UIMA computational time did not exceed 306 s. Research limitations/implications Some of the previous berth scheduling studies modeled uncertain vessel arrival times and/or handling times, while this study assumed the vessel arrival and handling times to be deterministic. Practical implications The developed UIMA algorithm can be used by the MCT operators as an efficient decision support tool and assist with a cost-effective design of berth schedules within an acceptable computational time. Originality/value A novel island-based metaheuristic algorithm is designed to solve the spatially constrained berth scheduling problem. The proposed island-based algorithm adopts several types of metaheuristic algorithms to cover different areas of the search space. The considered metaheuristic algorithms rely on different operators. Such feature is expected to facilitate the search process for superior solutions. 
    more » « less