JS']JS Capsules: A Framework for Capturing Fine-grained Java']JavaScript Memory Measurements for the MobileWeb

被引:0
|
作者
Naseer, Usama [1 ]
Benson, Theophilus A. [1 ,2 ]
机构
[1] Brown Univ, Providence, RI 02912 USA
[2] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA
关键词
Mobile web; Memory performance; Web optimizations;
D O I
10.1145/3579327
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Understanding the resource consumption of the mobile web is an important topic that has garnered much attention in recent years. However, existing works mostly focus on the networking or computational aspects of the mobile web and largely ignore memory, which is an important aspect given the mobile web's reliance on resource-heavy JavaScript. In this paper, we propose a framework, called JS Capsules, for characterizing the memory of JavaScript functions and, using this framework, we investigate the key browser mechanics that contribute to the memory overhead. Leveraging our framework on a testbed of Android mobile phones, we conduct measurements of the Alexa top 1K websites. While most existing frameworks focus on V8 - the JavaScript engine used in most popular browsers - in the context of memory, our measurements show that the memory implications of JavaScript extends far beyond V8 due to the cascading effects that certain JavaScript calls have on the browser's rendering mechanics. We quantify and highlight the direct impact that website DOM have on JavaScript memory overhead and present, to our knowledge, the first root-cause analysis to dissect and characterize their impact on JavaScript memory overheads.
引用
收藏
页数:27
相关论文
共 26 条
  • [21] JS']JSAC: A Novel Framework to Detect Malicious Java']JavaScript via CNNs over AST and CFG
    Jiang, Hongliang
    Yang, Yuxing
    Sun, Lu
    Jiang, Lin
    2019 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2019,
  • [22] Js']JsSandbox: A Framework for Analyzing the Behavior of Malicious Java']JavaScript Code using Internal Function Hooking
    Kim, Hyoung Chun
    Choi, Young Han
    Lee, Dong Hoon
    KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, 2012, 6 (02): : 766 - 783
  • [23] FGRec: A Fine-Grained Point-of-Interest Recommendation Framework by Capturing Intrinsic Influences
    Su, Yijun
    Zhang, Jia-Dong
    Li, Xiang
    Zha, Daren
    Xiang, Ji
    Tang, Wei
    Gao, Neng
    2020 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2020,
  • [24] Memory Based Computing: Reshaping the Fine-grained Logic in a Reconfigurable Framework
    Paul, S.
    Bhunia, S.
    FPGA 11: PROCEEDINGS OF THE 2011 ACM/SIGDA INTERNATIONAL SYMPOSIUM ON FIELD PROGRAMMABLE GATE ARRAYS, 2011, : 283 - 283
  • [25] IoTm: A Lightweight Framework for Fine-grained Measurements of IoT Performance Metrics
    Shahzad, Muhammad
    Ganji, Anirudh
    2018 IEEE 26TH INTERNATIONAL CONFERENCE ON NETWORK PROTOCOLS (ICNP), 2018, : 12 - 22
  • [26] Page Overlays: An Enhanced Virtual Memory Framework to Enable Fine-grained Memory Management
    Seshadri, Vivek
    Pekhimenko, Gennady
    Ruwase, Olatunji
    Mutlu, Onur
    Gibbons, Phillip B.
    Kozuch, Michael A.
    Mowry, Todd C.
    Chilimbi, Trishul
    2015 ACM/IEEE 42ND ANNUAL INTERNATIONAL SYMPOSIUM ON COMPUTER ARCHITECTURE (ISCA), 2015, : 79 - 91