TY - JOUR
T1 - Theoretical Performance Analysis of Distributed Queue for Massive Machine Type Communications
T2 - Throughput, Latency, Energy Consumption
AU - Li, Yaoyao
AU - Jian, Xin
AU - Yu, Keping
AU - Kumar, Neeraj
AU - Cai, Shaoxiong
N1 - Funding Information:
This work was supported in part by the National Natural Science Foundation of China under grant U20A20157, in part by the Natural Science Foundation of Chongqing under grant cstc2020jcyj-msxmX0031 and cstc2020jcyj-msxmX0718, in part by the Fundamental Research Funds for the Central Universities under grant 2020CDJGFWDZ014 and 2020CDJ-LHZZ-021, and in part by the Japan Society for the Promotion of Science (JSPS) Grants-in-Aid for Scientific Research (KAKENHI) under grant JP18K18044 and JP21K17736.
Publisher Copyright:
© 2004-2012 IEEE.
PY - 2022/6/1
Y1 - 2022/6/1
N2 - Massive machine type communications (mMTC) is one of main application cases in 5G, which is supposed to support communications of massive number of machine-type devices (MTDs). Distributed queue (DQ) is a variant of tree splitting protocol which combines an m-ary tree splitting algorithm with a set of simple smart rules, organizing every terminal in one out of two virtual queues. Theoretically, DQ allows access to infinite terminals and is stable under any traffic condition, which alleviates the unstable problem of slotted ALOHA, and is especially suitable for mMTC. However, its theoretical comprehensive performance analysis as well as related statistical characteristics is still missing, which severely restricts the full manifestation of its performance advantages. In view of this, the paper proposes a general performance analysis framework for DQ, with which full probability space of DQ evolution process is presented for the first time. To be more specific, probability distribution function (PDF), mean and variance of throughput, latency and energy consumption of DQ is analytically derived to comprehensively evaluate performance. Taking the IEEE 802.15.4 standard for mMTC as example, numerical results validate the accuracy of the proposed analysis framework and the stability of DQ, present effects of number of MTDs, number of contention slots (m), and maximum number of transmissions (L) on DQ in terms of aforementioned performance metrics. These results together provide good reference to find appropriate value of m and L to balance the performance metrics and enable more practical network optimization.
AB - Massive machine type communications (mMTC) is one of main application cases in 5G, which is supposed to support communications of massive number of machine-type devices (MTDs). Distributed queue (DQ) is a variant of tree splitting protocol which combines an m-ary tree splitting algorithm with a set of simple smart rules, organizing every terminal in one out of two virtual queues. Theoretically, DQ allows access to infinite terminals and is stable under any traffic condition, which alleviates the unstable problem of slotted ALOHA, and is especially suitable for mMTC. However, its theoretical comprehensive performance analysis as well as related statistical characteristics is still missing, which severely restricts the full manifestation of its performance advantages. In view of this, the paper proposes a general performance analysis framework for DQ, with which full probability space of DQ evolution process is presented for the first time. To be more specific, probability distribution function (PDF), mean and variance of throughput, latency and energy consumption of DQ is analytically derived to comprehensively evaluate performance. Taking the IEEE 802.15.4 standard for mMTC as example, numerical results validate the accuracy of the proposed analysis framework and the stability of DQ, present effects of number of MTDs, number of contention slots (m), and maximum number of transmissions (L) on DQ in terms of aforementioned performance metrics. These results together provide good reference to find appropriate value of m and L to balance the performance metrics and enable more practical network optimization.
KW - Distributed queue
KW - Massive machine type communication
KW - Random access
KW - Tree splitting algorithm
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U2 - 10.1109/TNSM.2022.3144510
DO - 10.1109/TNSM.2022.3144510
M3 - Article
AN - SCOPUS:85123347289
SN - 1932-4537
VL - 19
SP - 818
EP - 828
JO - IEEE Transactions on Network and Service Management
JF - IEEE Transactions on Network and Service Management
IS - 2
ER -