Towards programmable IoT with ActiveNDN

被引:1
作者
Mekbungwan, Preechai [1 ]
Lertsinsrubtavee, Adisorn [1 ]
Kitisin, Sukumal [2 ]
Pau, Giovanni [3 ]
Kanchanasut, Kanchana [4 ]
机构
[1] Asian Inst Technol, Internet Educ & Res Lab, Pathum Thani, Thailand
[2] Kasetsart Univ, Fac Sci, Dept Comp Sci, Bangkok, Thailand
[3] UNIBO, Dipartimento Informat Sci & Ingn, Bologna, Italy
[4] Technol Innovat Inst, Autonomous Robot Res Ctr, Abu Dhabi, U Arab Emirates
关键词
Named data networking; Internet of Things; Wireless sensor networks; Real-time IoT; In-network computation; Programmable IoT; Air-quality monitoring;
D O I
10.1007/s12243-023-00954-x
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
We propose to perform robust distributed computation, such as analysing and filtering raw data in real time, as close as possible to sensors in an environment with intermittent Internet connectivity and resource-constrained computable IoT nodes. To enable this computation, we deploy a named data network (NDN) for IoT applications, which allows data to be referenced by names. The novelty of our work lies in the inclusion of computation functions in each NDN router and allowing functions to be treated as executable Data objects. Function call is expressed as part of the NDN Interest names with proper name prefixes for NDN routing. With the results of the function computation returned as NDN Data packets, a normal NDN is converted to an ActiveNDN node. Distributed function executions can be orchestrated by an ActiveNDN program to perform required computations in the network. In this paper, we describe the design of ActiveNDN with a small prototype network as a proof of concept. We conduct extensive simulation experiments to investigate the performance and effectiveness of ActiveNDN in large-scale wireless IoT networks. Two programmable IoT air quality monitoring applications on our real-world ActiveNDN testbed are described, demonstrating that programmable IoT devices with on-site execution are capable of handling increasingly complex and time-sensitive IoT scenarios.
引用
收藏
页码:667 / 684
页数:18
相关论文
共 23 条
  • [1] Abane A., 2020, Journal of Cyber Security and Mobility, V9, P1, DOI [10.13052/jcsm2245-1439.911, DOI 10.13052/JCSM2245-1439.911]
  • [2] Amadeo M, 2013, IFIP WIREL DAY
  • [3] [Anonymous], 2014, ACM ICN 14, DOI [DOI 10.1145/2660129.2660148, 10.1145/2660129.2660148]
  • [4] [Anonymous], FIRE INFORM RESOURCE
  • [5] Forest fire detection system using wireless sensor networks and machine learning
    Dampage, Udaya
    Bandaranayake, Lumini
    Wanasinghe, Ridma
    Kottahachchi, Kishanga
    Jayasanka, Bathiya
    [J]. SCIENTIFIC REPORTS, 2022, 12 (01)
  • [6] Heidemann J., 2001, Operating Systems Review, V35, P146, DOI 10.1145/502059.502049
  • [7] Jacquet P, 2001, IEEE INMIC 2001: IEEE INTERNATIONAL MULTI TOPIC CONFERENCE 2001, PROCEEDINGS, P62, DOI 10.1109/INMIC.2001.995315
  • [8] Detection of PM2.5 plume movement from IoT ground level monitoring data
    Kanabkaew, Thongchai
    Mekbungwan, Preechai
    Raksakietisak, Sunee
    Kanchanasut, Kanchana
    [J]. ENVIRONMENTAL POLLUTION, 2019, 252 : 543 - 552
  • [9] Compute First Networking: Distributed Computing meets ICN
    Krol, Michal
    Mastorakis, Spyridon
    Oran, David
    Kutscher, Dirk
    [J]. PROCEEDINGS OF THE 2019 CONFERENCE ON INFORMATION-CENTRIC NETWORKING (ICN '19), 2019, : 67 - 77
  • [10] RICE: Remote Method Invocation in ICN
    Krol, Michal
    Habak, Karim
    Oran, David
    Kutscher, Dirk
    Psaras, Ioannis
    [J]. PROCEEDINGS OF THE 5TH ACM CONFERENCE ON INFORMATION-CENTRIC NETWORKING (ICN'18), 2018, : 1 - 11