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  • 1.
    Casalicchio, Emiliano
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Iannucci, Stefano
    Mississippi State University, .
    The state-of-the-art in container technologies: Application, orchestration and security2020Ingår i: Concurrency and Computation, ISSN 1532-0626, E-ISSN 1532-0634, artikel-id e5668Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Containerization is a lightweight virtualization technology enabling the deployment and execution of distributed applications on cloud, edge/fog, and Internet-of-Things platforms. Container technologies are evolving at the speed of light, and there are many open research challenges. In this paper, an extensive literature review is presented that identifies the challenges related to the adoption of container technologies in High Performance Computing, Big Data analytics, and geo-distributed (Edge, Fog, Internet-of-Things) applications. From our study, it emerges that performance, orchestration, and cyber-security are the main issues. For each challenge, the state-of-the-art solutions are then analyzed. Performance is related to the assessment of the performance footprint of containers and comparison with the footprint of virtual machines and bare metal deployments, the monitoring, the performance prediction, the I/O throughput improvement. Orchestration is related to the selection, the deployment, and the dynamic control of the configuration of multi-container packaged applications on distributed platforms. The focus of this work is on run-time adaptation. Cyber-security is about container isolation, confidentiality of containerized data, and network security. From the analysis of 97 papers, it came out that the state-of-the-art is more mature in the area of performance evaluation and run-time adaptation rather than in security solutions. However, the main unsolved challenges are I/O throughput optimization, performance prediction, multilayer monitoring, isolation, and data confidentiality (at rest and in transit). © 2020 John Wiley & Sons, Ltd.

  • 2.
    Martinsen, Jan Kasper
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datalogi och datorsystemteknik.
    Grahn, Håkan
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datalogi och datorsystemteknik.
    Isberg, Anders
    Sony Mobile Communications AB Lund, SWE.
    Combining thread-level speculation and just-in-time compilation in Google’s V8 JavaScript engine2017Ingår i: Concurrency and Computation, ISSN 1532-0626, E-ISSN 1532-0634, Vol. 29, nr 1, artikel-id e3826Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Summary: Thread-level speculation can be used to take advantage of multicore architectures for JavaScript in web applications. We extend previous studies with these main contributions; we implement thread-level speculation in the state-of-the art just-in-time-enabled JavaScript engine V8 and make the measurements in the Chromium web browser both from Google instead of using an interpreted JavaScript engine. We evaluate the thread-level speculation and just-in-time compilation combination on 15 very popular web applications, 20 HTML5 demos from the JS1K competition, and 4 Google Maps use cases. The performance is evaluated on two, four, and eight cores. The results clearly show that it is possible to successfully combine thread-level speculation and just-in-time compilation. This makes it possible to take advantage of multicore architectures for web applications while hiding the details of parallel programming from the programmer. Further, our results show an average speedup for the thread-level speculation and just-in-time compilation combination by a factor of almost 3 on four cores and over 4 on eight cores, without changing any of the JavaScript source code.

  • 3.
    Shirinbab, Sogand
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Lundberg, Lars
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Casalicchio, Emiliano
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Performance evaluation of containers and virtual machines when running Cassandra workload concurrently2020Ingår i: Concurrency and Computation, ISSN 1532-0626, E-ISSN 1532-0634, artikel-id e5693Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    NoSQL distributed databases are often used as Big Data platforms. To provide efficient resource sharing and cost effectiveness, such distributed databases typically run concurrently on a virtualized infrastructure that could be implemented using hypervisor-based virtualization or container-based virtualization. Hypervisor-based virtualization is a mature technology but imposes overhead on CPU, networking, and disk. Recently, by sharing the operating system resources and simplifying the deployment of applications, container-based virtualization is getting more popular. This article presents a performance comparison between multiple instances of VMware VMs and Docker containers running concurrently. Our workload models a real-world Big Data Apache Cassandra application from Ericsson. As a baseline, we evaluated the performance of Cassandra when running on the nonvirtualized physical infrastructure. Our study shows that Docker has lower overhead compared with VMware; the performance on the container-based infrastructure was as good as on the nonvirtualized. Our performance evaluations also show that running multiple instances of a Cassandra database concurrently affected the performance of read and write operations differently; for both VMware and Docker, the maximum number of read operations was reduced when we ran several instances concurrently, whereas the maximum number of write operations increased when we ran instances concurrently.

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