A Framework for Speculative Scheduling and Device Selection for Task Execution on a Mobile Cloud

被引：3
|
作者：
Banerjee, Ansuman [1 ]
Paul, Himadri Sekhar [2 ]
Mukherjee, Arijit [2 ]
Dey, Swarnava [2 ]
Datta, Pubali [2 ]
机构：
[1] Indian Stat Inst, ACMU, Kolkata, India
[2] Tata Consultancy Serv Ltd, Innovat Labs, Kolkata, India
来源：
ADAPTIVE RESOURCE MANAGEMENT AND SCHEDULING FOR CLOUD COMPUTING (ARMS-CC 2014) | 2014年 / 8907卷
关键词：
19;
D O I：
10.1007/978-3-319-13464-2_4
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, we study the problem of opportunistic task scheduling and workload management in a mobile cloud setting considering computation power variation. We gathered mobile usage data for a number of persons and applied supervised clustering to show that a pattern of usage exists and that follows a state-based model. Based on this model, we present a strategy to choose and offload work on a mobile device. We present a framework and experimental results showing the efficacy of our proposed approach.
引用
收藏
页码：36 / 51
页数：16
相关论文
共 50 条
  • [1] A Holistic Optimization Framework for Mobile Cloud Task Scheduling
    Liu, Huazhong
    Pu, Jie
    Yang, Laurence T.
    Lin, Man
    Yin, Dexiang
    Guo, Yimu
    Chen, Xingyu
    [J]. IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING, 2019, 4 (02): : 217 - 230
  • [2] ASME-SKYR framework: a comprehensive task scheduling framework for mobile cloud computing
    Yadav, Santosh Kumar
    Kumar, Rakesh
    [J]. WIRELESS NETWORKS, 2024, 30 (03) : 1221 - 1244
  • [3] ASME-SKYR framework: a comprehensive task scheduling framework for mobile cloud computing
    Santosh Kumar Yadav
    Rakesh Kumar
    [J]. Wireless Networks, 2024, 30 : 1221 - 1244
  • [4] Optimization of Maritime Communication Workflow Execution with a Task-Oriented Scheduling Framework in Cloud Computing
    Ahmad, Zulfiqar
    Acarer, Tayfun
    Kim, Wooseong
    [J]. JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2023, 11 (11)
  • [5] CloneCloud: Elastic Execution between Mobile Device and Cloud
    Chun, Byung-Gon
    Ihm, Sunghwan
    Maniatis, Petros
    Naik, Mayur
    Patti, Ashwin
    [J]. EUROSYS 11: PROCEEDINGS OF THE EUROSYS 2011 CONFERENCE, 2011, : 301 - 314
  • [6] DeePar: A Hybrid Device-Edge-Cloud Execution Framework for Mobile Deep Learning Applications
    Huang, Yutao
    Wang, Feng
    Wang, Fangxin
    Liu, Jiangchuan
    [J]. IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (IEEE INFOCOM 2019 WKSHPS), 2019, : 892 - 897
  • [7] Speculative Execution Attacks and Cloud Security
    Zhang, Yinqian
    Sion, Radu
    [J]. CCSW'19: PROCEEDINGS OF THE 2019 ACM SIGSAC CONFERENCE ON CLOUD COMPUTING SECURITY WORKSHOP, 2019, : 201 - 201
  • [8] Albatross: An Efficient Cloud-Enabled Task Scheduling and Execution Framework Using Distributed Message Queues
    Sadooghi, Iman
    Kumar, Geet
    Wang, Ke
    Zhao, Dongfang
    Li, Tonglin
    Raicu, Ioan
    [J]. PROCEEDINGS OF THE 2016 IEEE 12TH INTERNATIONAL CONFERENCE ON E-SCIENCE (E-SCIENCE), 2016, : 11 - 20
  • [9] Content Aware Task Scheduling Framework for Mobile Workflow Applications in Heterogeneous Mobile-Edge-Cloud Paradigms: CATSA Framework
    Lakhan, Abdullah
    Li, Xiaoping
    [J]. 2019 IEEE INTL CONF ON PARALLEL & DISTRIBUTED PROCESSING WITH APPLICATIONS, BIG DATA & CLOUD COMPUTING, SUSTAINABLE COMPUTING & COMMUNICATIONS, SOCIAL COMPUTING & NETWORKING (ISPA/BDCLOUD/SOCIALCOM/SUSTAINCOM 2019), 2019, : 242 - 249
  • [10] Mobile Sensing Framework for Task Partitioning Between Cloud and Edge Device for Improved Performance
    Alam, Shahnawaz
    Dewangan, Keshaw
    Sinharay, Arijit
    Ghose, Avik
    [J]. 2016 IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATION (ISCC), 2016, : 379 - 384
12345