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Peak Age of Information Optimization of Slotted Aloha: FCFS Versus LCFS
This paper aims at optimizing the Peak Age of Information (PAoI) performance of slotted Aloha networks with two representative data queue service disciplines, i.e., first-come first-served (FCFS) and last-come first-served (LCFS). Specifically, by assuming a unit-size buffer and Bernoulli packet arr...
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Published in: | IEEE transactions on network science and engineering 2023-11, Vol.10 (6), p.1-13 |
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description | This paper aims at optimizing the Peak Age of Information (PAoI) performance of slotted Aloha networks with two representative data queue service disciplines, i.e., first-come first-served (FCFS) and last-come first-served (LCFS). Specifically, by assuming a unit-size buffer and Bernoulli packet arrivals, the average PAoI are derived and minimized by properly tuning the packet arrival rate and the channel access probability of each sensor. Depending on whether the packet arrival rate can be tuned or not, the individual optimization and joint optimization are both considered. The optimal system parameters and corresponding minimum PAoI are explicitly characterized. The analysis shows that in the joint optimization case, the PAoI linearly increases with the network scale and the minimum PAoI with LCFS is 16.8% lower than that with FCFS in the massive access scenario. Yet, for achieving such performance gain over FCFS, each sensor with LCFS should generate a new sample in each time slot, indicating soaring energy consumption due to the sampling operation. The analysis shows that the energy efficiency with LCFS is always lower than that with FCFS, and the gap keeps increasing with the number of sensors, which reveals a clear age-energy tradeoff in terms of service disciplines. |
doi_str_mv | 10.1109/TNSE.2023.3272360 |
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Specifically, by assuming a unit-size buffer and Bernoulli packet arrivals, the average PAoI are derived and minimized by properly tuning the packet arrival rate and the channel access probability of each sensor. Depending on whether the packet arrival rate can be tuned or not, the individual optimization and joint optimization are both considered. The optimal system parameters and corresponding minimum PAoI are explicitly characterized. The analysis shows that in the joint optimization case, the PAoI linearly increases with the network scale and the minimum PAoI with LCFS is 16.8% lower than that with FCFS in the massive access scenario. Yet, for achieving such performance gain over FCFS, each sensor with LCFS should generate a new sample in each time slot, indicating soaring energy consumption due to the sampling operation. The analysis shows that the energy efficiency with LCFS is always lower than that with FCFS, and the gap keeps increasing with the number of sensors, which reveals a clear age-energy tradeoff in terms of service disciplines.</description><identifier>ISSN: 2327-4697</identifier><identifier>EISSN: 2334-329X</identifier><identifier>DOI: 10.1109/TNSE.2023.3272360</identifier><identifier>CODEN: ITNSD5</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Age of information ; Aloha networks ; Behavioral sciences ; channel access probability ; Energy consumption ; Internet of Things ; Optimization ; packet arrival rate ; Sensor phenomena and characterization ; Sensor systems ; Servers ; Steady-state</subject><ispartof>IEEE transactions on network science and engineering, 2023-11, Vol.10 (6), p.1-13</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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Specifically, by assuming a unit-size buffer and Bernoulli packet arrivals, the average PAoI are derived and minimized by properly tuning the packet arrival rate and the channel access probability of each sensor. Depending on whether the packet arrival rate can be tuned or not, the individual optimization and joint optimization are both considered. The optimal system parameters and corresponding minimum PAoI are explicitly characterized. The analysis shows that in the joint optimization case, the PAoI linearly increases with the network scale and the minimum PAoI with LCFS is 16.8% lower than that with FCFS in the massive access scenario. Yet, for achieving such performance gain over FCFS, each sensor with LCFS should generate a new sample in each time slot, indicating soaring energy consumption due to the sampling operation. The analysis shows that the energy efficiency with LCFS is always lower than that with FCFS, and the gap keeps increasing with the number of sensors, which reveals a clear age-energy tradeoff in terms of service disciplines.</description><subject>Age of information</subject><subject>Aloha networks</subject><subject>Behavioral sciences</subject><subject>channel access probability</subject><subject>Energy consumption</subject><subject>Internet of Things</subject><subject>Optimization</subject><subject>packet arrival rate</subject><subject>Sensor phenomena and characterization</subject><subject>Sensor systems</subject><subject>Servers</subject><subject>Steady-state</subject><issn>2327-4697</issn><issn>2334-329X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNpNkEFPAjEQhRujiQT5ASYemnhebGe62603QgBJiJiAxltTdru6CBTb5aC_3m6Wg6d5k3lvZvIRcsvZkHOmHtbPq8kQGOAQQQJm7IL0AFEkCOr9stUgE5EpeU0GIWwZYxzyDBF7ZPZizRcdfVjqKjo_VM7vTVO7A10em3pf_3ZNnK12rmlsSUc792ke6XQ8XdE368Mp0EXUN-SqMrtgB-faJ6_TyXr8lCyWs_l4tEgKEFmToLW2FGUpbFpxy1isLGdcWWmYwWgpVKGwSDcqV0JVViIrcZMa2AiZAwD2yX239-jd98mGRm_dyR_iSQ15zoVSEtLo4p2r8C4Ebyt99PXe-B_NmW6R6RaZbpHpM7KYuesydfzxn59zkSrEP489ZSg</recordid><startdate>20231101</startdate><enddate>20231101</enddate><creator>Zhan, Wen</creator><creator>Wu, Dewei</creator><creator>Sun, Xinghua</creator><creator>Guo, Ziyang</creator><creator>Liu, Peng</creator><creator>Liu, Jingjing</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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subjects | Age of information Aloha networks Behavioral sciences channel access probability Energy consumption Internet of Things Optimization packet arrival rate Sensor phenomena and characterization Sensor systems Servers Steady-state |
title | Peak Age of Information Optimization of Slotted Aloha: FCFS Versus LCFS |
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