Age-Optimal Mobile Elements Scheduling for Recharging and Data Collection in Green IoT
Ensuring real-time reporting of fresh information and maintaining the sustainability of power supply is of great importance in time-critical green Internet of Things (IoT). In this paper, we investigate the mobile element scheduling problem in a network with multiple independent and rechargeable sen...
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doaj-dff825f133d34cb79ad612372c8203172021-03-30T01:43:08ZengIEEEIEEE Access2169-35362020-01-018817658177510.1109/ACCESS.2020.29909319079825Age-Optimal Mobile Elements Scheduling for Recharging and Data Collection in Green IoTJianxin Ma0https://orcid.org/0000-0002-2518-8367Shuo Shi1https://orcid.org/0000-0002-5671-266XShushi Gu2https://orcid.org/0000-0002-3897-5407Ning Zhang3https://orcid.org/0000-0002-8781-4925Xuemai Gu4https://orcid.org/0000-0002-6011-9885Department of Electrical and Information Engineering, Harbin Institute of Technology, Harbin, ChinaDepartment of Electrical and Information Engineering, Harbin Institute of Technology, Harbin, ChinaNetwork Communication Research Centre, Peng Cheng Laboratory, Shenzhen, ChinaDepartment of Computing Sciences, Texas A&M University-Corpus Christi, Corpus Christi, TX, USADepartment of Electrical and Information Engineering, Harbin Institute of Technology, Harbin, ChinaEnsuring real-time reporting of fresh information and maintaining the sustainability of power supply is of great importance in time-critical green Internet of Things (IoT). In this paper, we investigate the mobile element scheduling problem in a network with multiple independent and rechargeable sensors, in which mobile elements are dispatched to collect data packets from the sensor nodes and to recharge them. The age of information (AoI) is used to measure the time elapsed of the most recently delivered packet since the generation of the packet. We propose an age-optimal mobile elements scheduling (AMES), which decides the trajectories of mobile elements based on a cooperative enforcement game and completes the time-slot allocation in each meeting point, to minimize the average AoI and maximize the energy efficiency. The cooperative enforcement game enables the mobile elements to make optimal visiting decisions and avoid the visiting conflicts, and the outcome of the game is pareto-optimal. Compared to the existing approaches, i.e., greedy algorithm (GA), greedy-neighborhood algorithm (GA-neighborhood), simulation results demonstrate that AMES can achieve a lower average AoI and a higher energy efficiency with a higher successful visiting ratio of the sensor node.https://ieeexplore.ieee.org/document/9079825/Mobile element schedulingdata collectionage of informationenergy efficiencygreen IoT |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jianxin Ma Shuo Shi Shushi Gu Ning Zhang Xuemai Gu |
spellingShingle |
Jianxin Ma Shuo Shi Shushi Gu Ning Zhang Xuemai Gu Age-Optimal Mobile Elements Scheduling for Recharging and Data Collection in Green IoT IEEE Access Mobile element scheduling data collection age of information energy efficiency green IoT |
author_facet |
Jianxin Ma Shuo Shi Shushi Gu Ning Zhang Xuemai Gu |
author_sort |
Jianxin Ma |
title |
Age-Optimal Mobile Elements Scheduling for Recharging and Data Collection in Green IoT |
title_short |
Age-Optimal Mobile Elements Scheduling for Recharging and Data Collection in Green IoT |
title_full |
Age-Optimal Mobile Elements Scheduling for Recharging and Data Collection in Green IoT |
title_fullStr |
Age-Optimal Mobile Elements Scheduling for Recharging and Data Collection in Green IoT |
title_full_unstemmed |
Age-Optimal Mobile Elements Scheduling for Recharging and Data Collection in Green IoT |
title_sort |
age-optimal mobile elements scheduling for recharging and data collection in green iot |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
Ensuring real-time reporting of fresh information and maintaining the sustainability of power supply is of great importance in time-critical green Internet of Things (IoT). In this paper, we investigate the mobile element scheduling problem in a network with multiple independent and rechargeable sensors, in which mobile elements are dispatched to collect data packets from the sensor nodes and to recharge them. The age of information (AoI) is used to measure the time elapsed of the most recently delivered packet since the generation of the packet. We propose an age-optimal mobile elements scheduling (AMES), which decides the trajectories of mobile elements based on a cooperative enforcement game and completes the time-slot allocation in each meeting point, to minimize the average AoI and maximize the energy efficiency. The cooperative enforcement game enables the mobile elements to make optimal visiting decisions and avoid the visiting conflicts, and the outcome of the game is pareto-optimal. Compared to the existing approaches, i.e., greedy algorithm (GA), greedy-neighborhood algorithm (GA-neighborhood), simulation results demonstrate that AMES can achieve a lower average AoI and a higher energy efficiency with a higher successful visiting ratio of the sensor node. |
topic |
Mobile element scheduling data collection age of information energy efficiency green IoT |
url |
https://ieeexplore.ieee.org/document/9079825/ |
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