Maximum Throughput Under Admission Control With Unknown Queue-Length in Wireless Sensor Networks

被引:6
作者
Zhang, Xiaolu [1 ]
Li, Demin [1 ]
Zhang, Yihong [1 ]
机构
[1] Donghua Univ, Coll Informat Sci & Technol, Engn Res Ctr Digitized Text & Fash Technol, Minist Educ, Shanghai 201620, Peoples R China
关键词
Sensors; Throughput; Admission control; Wireless sensor networks; Switches; Energy consumption; Data models; Maximum throughput; probabilistic admission control; queue-length; discounted reward; energy performance; CONTROL POLICY; ENERGY;
D O I
10.1109/JSEN.2020.2997984
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
InaWireless Sensor Network (WSN) node, as the input traffic increases, the throughput can be assumed to first increase and then start to decrease, indicating congestion in the buffer. This suggests the need for an admission control mechanism to maintain high throughput as the arrival traffic increases. Considering the stochastic nature of WSNs, the information of the queue-length of arrival or newly sensed data packets can be unknown to a sensor node. This paper proposes a probabilistic admission control model with the maximum throughput for the node. In the proposed model, a reward when a data packet arriving to a sensor is accepted (not rejected) for transmission is considered, but a holding cost per unit time for the delay of accepted data packets in the sensor is also incurred. For the sensor node, by constructing a suitable Markov decision process (MDP), a probabilistic admission control algorithm on how to accept data packets on sleep and active phases to achieve amaximumthroughput is proposed. Furthermore, for the identified ( p; q) model, the energy consumption of the node in active and sleep phases, aswell as the energy consumption switching from active to sleep per unit time and vice versa is investigated. An extensive simulation is implemented. The numerical results show that the problem is effectively solved by an optimal scheme with high energy efficiency. The results of this paper can be applied in designing optimal sensor nodes in WSNs.
引用
收藏
页码:11387 / 11399
页数:13
相关论文
共 27 条
[1]   MAC Essentials for Wireless Sensor Networks [J].
Bachir, Abdelmalik ;
Dohler, Mischa ;
Watteyne, Thomas ;
Leung, Kin K. .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2010, 12 (02) :222-248
[2]  
Bertsekas D.P., 2014, Constrained Optimization and Lagrange Multiplier Methods
[3]   Node-level energy management for sensor networks in the presence of multiple applications [J].
Boulis, A ;
Srivastava, M .
WIRELESS NETWORKS, 2004, 10 (06) :737-746
[4]   Throughput analysis and admission control for IEEE 802.11a [J].
Ergen, M ;
Varaiya, P .
MOBILE NETWORKS & APPLICATIONS, 2005, 10 (05) :705-716
[5]  
Forst W., 2010, OPTIMIZATIONLTHEORY
[6]   A dynamic N threshold prolong lifetime method for wireless sensor nodes [J].
Huang, Der-Chen ;
Lee, Jong-Hyouk .
MATHEMATICAL AND COMPUTER MODELLING, 2013, 57 (11-12) :2731-2741
[7]   Service Admission Control in Multi-Service Sensor Networks [J].
Iraqi, Youssef ;
Jabeur, Nafaa .
ISCC: 2009 IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS, VOLS 1 AND 2, 2009, :926-931
[8]   Energy Efficient Strategy for Throughput Improvement in Wireless Sensor Networks [J].
Jabbar, Sohail ;
Minhas, Abid Ali ;
Imran, Muhammad ;
Khalid, Shehzad ;
Saleem, Kashif .
SENSORS, 2015, 15 (02) :2473-2495
[9]   Snapshot and Continuous Data Collection in Probabilistic Wireless Sensor Networks [J].
Ji, Shouling ;
Beyah, Raheem ;
Cai, Zhipeng .
IEEE TRANSACTIONS ON MOBILE COMPUTING, 2014, 13 (03) :626-637
[10]   QoE-Based Flow Admission Control in Small Cell Networks [J].
Ksentini, Adlen ;
Taleb, Tarik ;
Letaif, Khaled B. .
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2016, 15 (04) :2474-2483