Comparison Of Q-Coverage P-Connectivity Sensor Node Scheduling Heuristic Between Battery Powered Wsn & Energy Harvesting Wsn

2020 ◽  
Vol 10 ◽  
Author(s):  
Sunita Upta ◽  
Sakar Gupta ◽  
Dinesh Goyal
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Sensor Node ◽  
High Energy ◽  
Wireless Sensor ◽  
Node Scheduling ◽  
Qos Parameters ◽  
Coverage And Connectivity ◽  
Scheduling Heuristic

: A serious problem in Wireless Sensor Networks (WSNs) is to attain high-energy efficiency as battery powers a node, which has limited stored energy. They can’t be suitably replaced or recharged. Appearance of renewable energy harvesting techniques and their combination with sensors gives Energy Harvesting Wireless Sensor Networks (EH-WSNs). Therefore, the area shifts from energy preservation to reliability of the network. For reliability, Coverage and Connectivity are important Quality of Service (QoS) parameters. Many sensor node scheduling heuristics have been developed in past. Some of them focus on more than single order of Coverage and Connectivity. If reliability is main concern for a WSN, then definitely there is a need to incorporate Q-Coverage and P-Connectivity in WSN. Lifetime of a WSN decreases while considering Q-Coverage and P-Connectivity. After some time network dies and it is of no use. Therefore, there is a trade-off between reliability and lifetime of a WSN. If EH-WSN is used, then lifetime of a WSN increases as well as Q-Coverage and P-Connectivity QoS parameters can used for achieving reliability. This paper proposes a sensor node scheduling heuristic for EH-WSN considering Q-Coverage and P-Connectivity. A comparison of a Q-Coverage and P-Connectivity sensor node scheduling heuristic when used between battery powered WSN & EH-WSN is done. Comparison shows that lifetime using EH-WSN is much greater as compared to battery powered WSN. This research is beneficial for real time WSN applications where EH-WSN provides power regularly without any intervention.

scholarly journals Basic MAC Scheme for RF Energy Harvesting Wireless Sensor Networks: Throughput Analysis and Optimization

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1822
Author(s):  
Choi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Sensor Node ◽  
Wireless Sensor ◽  
Basic Medium ◽  
Rf Energy Harvesting ◽  
Mac Scheme ◽  
Rf Energy ◽  
Off Time

Traditionally, how to reduce energy consumption has been an issue of utmost importance in wireless sensor networks. Recently, radio frequency (RF) energy harvesting technologies, which scavenge the ambient RF waves, provided us with a new paradigm for such networks. Without replacement or recharge of batteries, an RF energy harvesting wireless sensor network may live an eternal life. Against theoretical expectations, however, energy is scarce in practice and, consequently, structural naiveté has to be within a MAC scheme that supports a sensor node to deliver its data to a sink node. Our practical choice for the MAC scheme is a basic one, rooted in ALOHA, in which a sensor node simply repeats harvesting energy, backing off for a while and transmitting a packet. The basic medium access control (MAC) scheme is not able to perfectly prevent a collision of packets, which in turn deteriorates the throughput. Thus, we derive an exact expression of the throughput that the basic MAC scheme can attain. In various case studies, we then look for a way to enhance the throughput. Using the throughput formula, we reveal that an optimal back-off time, which maximizes the total throughput, is not characterized by the distribution but only by the mean value when the harvest times are deterministic. Also, we confirm that taking proper back-off times is able to improve the throughput even when the harvest times are random. Furthermore, we show that shaping the back-off time so that its variance is increased while its mean remains unchanged can help ameliorate the throughput that the basic MAC scheme is able to achieve.

scholarly journals A sensor node scheduling algorithm for heterogeneous wireless sensor networks

2019 ◽  
Vol 15 (1) ◽  
pp. 155014771982631 ◽  
Author(s):  
Zhangquan Wang ◽  
Yourong Chen ◽  
Banteng Liu ◽  
Haibo Yang ◽  
Ziyi Su ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Optimization Model ◽  
Sensor Node ◽  
Scheduling Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Node Scheduling ◽  
Heterogeneous Wireless Sensor Networks

To improve the regional coverage rate and network lifetime of heterogeneous wireless sensor networks, a sensor node scheduling algorithm for heterogeneous wireless sensor networks is proposed. In sensor node scheduling algorithm, heterogeneous perception radius of sensor node is considered. Incomplete coverage constraint and arc coverage interval are analyzed. Regional coverage increment optimization model, arc coverage increment optimization model, and residual energy optimization model are proposed. Multi-objective scheduling model is established using weight factors and integrated function. Furthermore, the heuristic method is proposed to solve the multi-objective optimization model, and scheduling scheme of heterogeneous sensor nodes is obtained. When the network is in operation for a period of time, some sensor nodes are invalid and relevant regions are uncovered. The repair method is proposed to wake up sleep sensor nodes and repair the coverage blind area. The simulation results show that if keeping the same regional coverage rate, sensor node scheduling algorithm improves network lifetime, increases number of living sensor nodes, and keeps average node energy consumption at a low level. Under certain conditions, sensor node scheduling algorithm outperforms DGREEDY, two-tiered scheduling, and minimum connected cover.

scholarly journals Optimizing Maximum Monitoring Frequency and Guaranteeing Target Coverage and Connectivity in Energy Harvesting Wireless Sensor Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Xuecai Bao ◽  
Longzhe Han ◽  
Xun He ◽  
Wenqun Tan ◽  
Tanghuai Fan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Problem Formulation ◽  
Wireless Sensor ◽  
Target Coverage ◽  
Monitoring Methods ◽  
Monitoring Frequency ◽  
Average Maximum ◽  
Coverage And Connectivity

Improving the quality of monitoring and guaranteeing target coverage and connectivity in energy harvesting wireless sensor networks (EH-WSNs) are important issues in near-perpetual environmental monitoring. Existing solutions only focus on the utility of coverage or energy efficient coverage by considering target connectivity for battery-powered WSNs. This paper focuses on optimizing the maximum monitoring frequency with guaranteed target coverage and connectivity in EH-WSNs. We first analyzed the factors affecting monitoring quality and the energy harvesting model. Thereafter, we presented the problem formulation and proposed the algorithm for maximizing monitoring frequency and guaranteeing target coverage and connectivity (MFTCC) that is based on graph theory. Furthermore, we presented the corresponding distributed implementation approach. On the basis of the existing energy harvesting prediction model, expensive simulations show that the proposed MFTCC algorithm achieves high average maximum monitoring frequency and energy usage ratio. Moreover, it obtains a higher throughput than existing target monitoring methods.

scholarly journals Energy-Efficiency of Dual-Switched Branch Diversity Receiver in Wireless Sensor Networks

2011 ◽  
Vol 7 (2) ◽  
pp. 130-137
Author(s):  
Ghaida AL-Suhail
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Channel Coding ◽  
Sensor Node ◽  
High Energy ◽  
Wireless Sensor ◽  
Bch Code ◽  
Improve Energy Efficiency ◽  
Diversity Receiver

In this paper, we develop an analytical energy efficiency model using dual switched branch diversity receiver in wireless sensor networks in fading environments. To adapt energy efficiency of sensor node to channel variations, the optimal packet length at the data link layer is considered. Within this model, the energy efficiency can be effectively improved for switch-and-stay combiner (SSC) receiver with optimal switching threshold. Moreover, to improve energy efficiency, we use error control of Bose-Chaudhuri-Hochquengh (BCH) coding for SSC-BPSK receiver node compared to one of non-diversity NCFSK receiver of sensor node. The results show that the BCH code for channel coding can improve the energy efficiency significantly for long link distance and various values of high energy consumptions over Rayleigh fading channel.

Effects of Energy Harvesting Rate on Lifetime and Throughput Capacity in Wireless Sensor Networks

2014 ◽  
Vol 981 ◽  
pp. 482-485 ◽  
Author(s):  
Yang Zeng ◽  
Xue Dan Zhang ◽  
Yu Han Dong
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
High Energy ◽  
Throughput Capacity ◽  
Wireless Sensor ◽  
Transmission Power ◽  
High Transmission ◽  
Source Sink ◽  
High Energy Consumption

Energy-harvesting Wireless sensor networks have gained more and more attention in recent years. For traditional battery-powered WSNs, the effect of transmission power on the throughput capacity and the lifetime have been well studied. The throughput capacity of WSNs is defined usually as the largest common throughput that can be provided to each source-sink pair nodes. Researches showed that high transmission power increases the throughput capacity of WSNs However, the high transmission power leads to a high energy consumption, thus the tradeoffs between the capacity and the lifetime under different transmission power have been analyzed.

Sign in / Sign up

Export Citation Format

Share Document