Holistic Runtime Performance and Security-aware Monitoring in Public Cloud Environment

被引:5
|
作者
Jha, Devki Nandan [1 ,2 ]
Lenton, Graham [2 ]
Asker, James [2 ]
Blundell, David [2 ]
Wallom, David [1 ]
机构
[1] Univ Oxford, Oxford eRes Ctr, Oxford, England
[2] 100 Percent IT Ltd CyberH, Wessex House, Newbury, Berks, England
来源
2022 22ND IEEE/ACM INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND INTERNET COMPUTING (CCGRID 2022) | 2022年
关键词
Public cloud; Run-time monitoring; eBPF; Performance; Security;
D O I
10.1109/CCGrid54584.2022.00128
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The emergence of cloud computing allows users to execute their applications in a ubiquitous manner. Public cloud offers various ready-to-use services e.g. AWS EC2, Amazon RDS on a pay-per-use basis. Alongside these advantages, the cloud also brings a number of issues, for example offloading data for storage and computation may lead to privacy and security concerns. Also, it is not easy to guarantee the performance of the underlying system. With the increasing performance and security concerns, it is necessary to continuously monitor and evaluate the system and its performance. This can help us to quickly detect anomalies that can hinder system performance and/or make the system untrusted. In this paper, we present PERSECMON: performance and security-aware monitoring framework for continuous run-time monitoring in the public cloud environment. PERSECMON provides not only the system performance metrics but also the security measurements which can be used to analyse the system state at run-time. It uses the BCC/eBPF (BPF Compiler Collection/ Extended Berkeley Packet Filters) framework to instrument the system. PERSECMON is integrated with the open-source user interface framework, Kibana which provides a clear visualisation of the obtained metrics. To show the efficacy of our proposed work, we have developed a benchmarking case study using Bonnie++, Fibonacci Sequence and Netperf executed on Ubuntu Server 21.04. The results show that PERSECMON successfully captures relevant metrics that can be utilised in real-time to analyse the system performance. These metrics can further be accessed to detect the system state including memory leaks, queuing delay and remote access time which may lead to security or reliability events.
引用
收藏
页码:1052 / 1059
页数:8
相关论文
共 32 条
  • [21] An improved Caledonian crow learning algorithm based on ring topology for security-aware workflow scheduling in cloud computing
    Zade, B. Mohammad Hasani
    Javidi, M. M.
    Mansouri, N.
    PEER-TO-PEER NETWORKING AND APPLICATIONS, 2023, 16 (06) : 2929 - 2984
  • [22] An improved Caledonian crow learning algorithm based on ring topology for security-aware workflow scheduling in cloud computing
    B. Mohammad Hasani Zade
    M. M. Javidi
    N. Mansouri
    Peer-to-Peer Networking and Applications, 2023, 16 : 2929 - 2984
  • [23] A Security and Privacy Aware Computing Approach on Data Sharing in Cloud Environment
    Al Mayyahi, Mustafa Azeez
    Seno, Seyed Amin Hosseini
    BAGHDAD SCIENCE JOURNAL, 2022, 19 (06) : 1572 - 1580
  • [25] Autonomic Resource Management for Power, Performance, and Security in Cloud Environment
    Fargo, Farah
    Franza, Olivier
    Tunc, Cihan
    Hariri, Salim
    2019 IEEE/ACS 16TH INTERNATIONAL CONFERENCE ON COMPUTER SYSTEMS AND APPLICATIONS (AICCSA 2019), 2019,
  • [26] Enhanced Performance and Data Security using Elliptic Curve Cryptography in Cloud Environment
    Acharya, Shreenath
    Manoj, K.
    Gayana, M. N.
    2021 INTERNATIONAL CONFERENCE ON COMPUTATIONAL PERFORMANCE EVALUATION (COMPE-2021), 2021, : 869 - 873
  • [27] An improved efficient: Artificial Bee Colony algorithm for security and QoS aware scheduling in cloud computing environment
    Thanka, M. Roshni
    Maheswari, P. Uma
    Edwin, E. Bijolin
    CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2019, 22 (Suppl 5): : 10905 - 10913
  • [28] An improved efficient: Artificial Bee Colony algorithm for security and QoS aware scheduling in cloud computing environment
    M. Roshni Thanka
    P. Uma Maheswari
    E. Bijolin Edwin
    Cluster Computing, 2019, 22 : 10905 - 10913
  • [29] Credit-based scheme for security-aware and fairness-aware resource allocation in cloud computing云计算中面向安全和公平资源分配的信誉模型
    Di Lu
    Jianfeng Ma
    Cong Sun
    Xindi Ma
    Ning Xi
    Science China Information Sciences, 2017, 60
  • [30] Alioth: A Machine Learning Based Interference -Aware Performance Monitor for Multi -Tenancy Applications in Public Cloud
    Shi, Tianyao
    Yang, Yingxuan
    Cheng, Yunlong
    Gao, Xiaofeng
    Fang, Zhen
    Yang, Yongqiang
    2023 IEEE INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM, IPDPS, 2023, : 908 - 917