Multiple Mobile Sinks for Quality of Service Improvement in Large-Scale Wireless Sensor Networks

被引:2
作者
Yagouta, Abdelbari Ben [1 ]
Gouissem, Bechir Ben [1 ]
Mnasri, Sami [2 ,3 ]
Alghamdi, Mansoor [2 ]
Alrashidi, Malek [2 ]
Alrowaily, Majed Abdullah [4 ]
Alkhazi, Ibrahim [2 ]
Gantassi, Rahma [5 ]
Hasnaoui, Salem [1 ]
机构
[1] Univ Tunis El Manar UTM, Natl Engn Sch Tunis ENIT, Commun Syst Lab SysCom, Tunis 1002, Tunisia
[2] Univ Tabuk, Appl Coll, Comp Sci Dept, Tabuk 71491, Saudi Arabia
[3] Univ Toulouse II, IRIT RMESS, F-31058 Toulouse, France
[4] Jouf Univ, Coll Comp & Informat Sci, Dept Comp Sci, Sakaka 72341, Saudi Arabia
[5] Chonnam Natl Univ, Dept Elect Engn, Gwangju 61186, South Korea
关键词
cluster-based routing protocol; energy consumption; quality of service; multiple mobile sinks; large scale wireless sensor network; ENERGY-EFFICIENT; LIFETIME; TIME;
D O I
10.3390/s23208534
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
The involvement of wireless sensor networks in large-scale real-time applications is exponentially growing. These applications can range from hazardous area supervision to military applications. In such critical contexts, the simultaneous improvement of the quality of service and the network lifetime represents a big challenge. To meet these requirements, using multiple mobile sinks can be a key solution to accommodate the variations that may affect the network. Recent studies were based on predefined mobility models for sinks and relied on multi-hop routing techniques. Besides, most of these studies focused only on improving energy consumption without considering QoS metrics. In this paper, multiple mobile sinks with random mobile models are used to establish a tradeoff between power consumption and the quality of service. The simulation results show that using hierarchical data routing with random mobile sinks represents an efficient method to balance the distribution of the energy levels of nodes and to reduce the overall power consumption. Moreover, it is proven that the proposed routing methods allow for minimizing the latency of the transmitted data, increasing the reliability, and improving the throughput of the received data compared to recent works, which are based on predefined trajectories of mobile sinks and multi-hop architectures.
引用
收藏
页数:23
相关论文
共 62 条
[31]   MCH-EOR: Multi-objective Cluster Head Based Energy-aware Optimized Routing algorithm in Wireless Sensor Networks [J].
Mehta, Deepak ;
Saxena, Sharad .
SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS, 2020, 28
[32]   Energy-efficient IoT routing based on a new optimizer [J].
Mnasri, Sami ;
Alrashidi, Malek .
SIMULATION MODELLING PRACTICE AND THEORY, 2022, 119
[33]   The 3D Redeployment of Nodes in Wireless Sensor Networks with Real Testbed Prototyping [J].
Mnasri, Sami ;
Van den Bossche, Adrien ;
Nasri, Nejah ;
Val, Thierry .
AD-HOC, MOBILE, AND WIRELESS NETWORKS, ADHOC-NOW 2017, 2017, 10517 :18-24
[34]   Recent Advances and Future Prospects of Using AI Solutions for Security, Fault Tolerance, and QoS Challenges in WSNs [J].
Osamy, Walid ;
Khedr, Ahmed M. M. ;
Salim, Ahmed ;
El-Sawy, Ahmed A. A. ;
Alreshoodi, Mohammed ;
Alsukayti, Ibrahim .
ELECTRONICS, 2022, 11 (24)
[35]   Enhancing Real-Time Delivery of Gradient Routing for Industrial Wireless Sensor Networks [J].
Pham Tran Anh Quang ;
Kim, Dong-Sung .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2012, 8 (01) :61-68
[36]   Two Approaches to the Traffic Quality Intuitionistic Fuzzy Estimation of Service Compositions [J].
Poryazov, Stoyan ;
Andonov, Velin ;
Saranova, Emiliya ;
Atanassov, Krassimir .
MATHEMATICS, 2022, 10 (23)
[37]  
Poryazov SA, 2019, 2019 14TH INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES, SYSTEMS AND SERVICES IN TELECOMMUNICATIONS (TELSIKS 2019), P360, DOI [10.1109/TELSIKS46999.2019.9002295, 10.1109/telsiks46999.2019.9002295]
[38]   A Systematic Review of Quality of Service in Wireless Sensor Networks using Machine Learning: Recent Trend and Future Vision [J].
Pundir, Meena ;
Sandhu, Jasminder Kaur .
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2021, 188
[39]  
Sheldon M., 2005, P IEEE MASS WASH DC
[40]  
Shiltagh N.A., 2019, Int. J. Electr. Comput. Eng, V9, P2880, DOI [10.11591/ijece.v9i4.pp2880-2892, DOI 10.11591/IJECE.V9I4.PP2880-2892]