Energy efficiency on location based applications in mobile cloud computing: a survey

被引:15
|
作者
Wang, Lian [1 ]
Cui, Yong [1 ]
Stojmenovic, Ivan [2 ,3 ]
Ma, Xiao [1 ]
Song, Jian [1 ]
机构
[1] Tsinghua Univ, Dept Comp Sci, Beijing 100084, Peoples R China
[2] Univ Ottawa, Sch Informat Technol & Engn, Ottawa, ON, Canada
[3] Tsinghua Univ, Sch Software, Beijing 100084, Peoples R China
基金
加拿大自然科学与工程研究理事会;
关键词
Mobile; Cloud computing; Location based service; Energy-efficiency;
D O I
10.1007/s00607-013-0334-0
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The constrained battery power of mobile devices poses a serious impact on user experience. As an increasingly prevalent type of applications in mobile cloud environments, location-based applications (LBAs) present some inherent limitations concerning energy. For example, the Global Positioning System based positioning mechanism is well-known for its extremely power-hungry attribute. Due to the severity of the issue, considerable researches have focused on energy-efficient locating sensing mechanism in the last a few years. In this paper, we provide a comprehensive survey of recent work on low-power design of LBAs. An overview of LBAs and different locating sensing technologies used today are introduced. Methods for energy saving with existing locating technologies are investigated. Reductions of location updating queries and simplifications of trajectory data are also mentioned. Moreover, we discuss cloud-based schemes in detail which try to develop new energy-efficient locating technologies by leveraging the cloud capabilities of storage, computation and sharing. Finally, we conclude the survey and discuss the future research directions.
引用
收藏
页码:569 / 585
页数:17
相关论文
共 50 条
  • [31] Energy efficiency in cloud computing data centers: a survey on software technologies
    Avita Katal
    Susheela Dahiya
    Tanupriya Choudhury
    Cluster Computing, 2023, 26 : 1845 - 1875
  • [32] Key aspects for the development of applications for Mobile Cloud Computing
    Rodriguez, Nelson R.
    Murazzo, Maria A.
    Chavez, Susana B.
    Valenzuela, Francisca A.
    Martin, Adriana E.
    Villafane, Daniela A.
    JOURNAL OF COMPUTER SCIENCE & TECHNOLOGY, 2013, 13 (03): : 143 - 148
  • [33] Energy efficiency in cloud computing data center: a survey on hardware technologies
    Avita Katal
    Susheela Dahiya
    Tanupriya Choudhury
    Cluster Computing, 2022, 25 : 675 - 705
  • [34] Cloudlet-based Mobile Cloud Computing for Healthcare Applications
    Tawalbeh, Lo'ai A.
    Bakheder, Waseem
    Mehmood, Rashid
    Song, Houbing
    2016 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2016,
  • [35] A mobile Internet Applications System Based on Cloud Computing and Identification
    Li, Yang
    Li, Jie
    PROCEEDINGS OF THE 2015 INTERNATIONAL SYMPOSIUM ON COMPUTERS & INFORMATICS, 2015, 13 : 1206 - 1212
  • [36] Computing Energy-Efficiency in the Mobile GPU
    Kim, Sangduk
    Kim, Hyo-Eun
    Kim, Hyunsuk
    Lee, Jin-Aeon
    2013 INTERNATIONAL SOC DESIGN CONFERENCE (ISOCC), 2013, : 222 - 224
  • [37] Energy Saving in Mobile Cloud Computing
    Rahman, Mazedur
    Gao, Jerry
    Tsai, Wei-Tek
    PROCEEDINGS OF THE 2013 IEEE INTERNATIONAL CONFERENCE ON CLOUD ENGINEERING (IC2E 2013), 2013, : 285 - 291
  • [38] A Survey on the Applications of Cloud Computing in the Industrial Internet of Things
    Dritsas, Elias
    Trigka, Maria
    BIG DATA AND COGNITIVE COMPUTING, 2025, 9 (02)
  • [39] Cyber Physical Systems based on Cloud Computing and Internet of Things for Energy Efficiency
    Suciu, George
    Butca, Cristina
    Suciu, Victor
    Cretu, Alexandru
    Fratu, Octavian
    ADVANCED TOPICS IN OPTOELECTRONICS, MICROELECTRONICS, AND NANOTECHNOLOGIES VIII, 2016, 10010
  • [40] Energy efficiency in cloud computing based on mixture power spectral density prediction
    Dinh-Mao Bui
    Nguyen Anh Tu
    Eui-Nam Huh
    The Journal of Supercomputing, 2021, 77 : 2998 - 3023