Abstract
As an emerging measure of data freshness, the age of information (AoI) is receiving extensive attention. Many methods using AoI have been proposed for communication scheduling in the Internet of Things (IoT). However, most of them are aimed at constant channel conditions in the ideal state, and the utilization of link resources is not sufficient. In addition, only the optimization of AoI is considered, without considering whether the sample is extruded. Sample extrusion refers to the scenario in which the transmission of the remaining untransmitted sample of the source node cannot be completed within the transmission time interval (TTI) before the arrival of the new sampling period of the source node. Thus, sample extrusion is a phenomenon that occurs when the new sample arrives while the old sample has not yet been completely transmitted. This scenario has a serious impact on delay-sensitive IoT applications. Therefore, under dynamic channel conditions and limited link resources, this paper establishes two mathematical models for AoI and sample extrusion. The influence of the scheduling algorithm on these two target values is analyzed and proven. Based on a greedy strategy, we propose a preemptive online algorithm for link resource allocation that considers two objectives: to give full play to the value of link resources and to minimize sample extrusion. The simulation results show that the proposed strategy can achieve better comprehensive performance in both scenarios where the sample variance between source nodes is small or large.
Highlights
INTRODUCTIONLi et al [22] constructed a realistic system model and proposed the JUVENTAS algorithm to schedule and transmit source node information that achieved a near-optimal solution
CONTRIBUTIONS AND OUTLINE In this paper, we consider that each source node periodically collects time-sensitive samples, and we use advanced transmission technology to transmit the samples to a base station (BS) with limited link capacity over a dynamically changing channel
We take into account the effective use of resources and avoidance of sample extrusion, and according to the analysis results and the introduction of variables that can reflect the channel changes and size of the remaining sample to be transmitted, a preemptive online scheduling algorithm based on a greedy strategy is proposed to solve the model
Summary
Li et al [22] constructed a realistic system model and proposed the JUVENTAS algorithm to schedule and transmit source node information that achieved a near-optimal solution This algorithm is based on ideal channel conditions and only optimizes AoI. C. CONTRIBUTIONS AND OUTLINE In this paper, we consider that each source node periodically collects time-sensitive samples, and we use advanced transmission technology to transmit the samples to a base station (BS) with limited link capacity over a dynamically changing channel. We take into account the effective use of resources and avoidance of sample extrusion, and according to the analysis results and the introduction of variables that can reflect the channel changes and size of the remaining sample to be transmitted, a preemptive online scheduling algorithm based on a greedy strategy is proposed to solve the model.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
