Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2014 Dec 2;14(12):22811-47.
doi: 10.3390/s141222811.

On the MAC/network/energy performance evaluation of Wireless Sensor Networks: Contrasting MPH, AODV, DSR and ZTR routing protocols

Carolina Del-Valle-Soto  1 , Carlos Mex-Perera  2 , Aldo Orozco-Lugo  3 , Mauricio Lara  4 , Giselle M Galván-Tejada  5 , Oscar Olmedo  6
Affiliations

On the MAC/network/energy performance evaluation of Wireless Sensor Networks: Contrasting MPH, AODV, DSR and ZTR routing protocols

Carolina Del-Valle-Soto et al. Sensors (Basel). .

Abstract

Wireless Sensor Networks deliver valuable information for long periods, then it is desirable to have optimum performance, reduced delays, low overhead, and reliable delivery of information. In this work, proposed metrics that influence energy consumption are used for a performance comparison among our proposed routing protocol, called Multi-Parent Hierarchical (MPH), the well-known protocols for sensor networks, Ad hoc On-Demand Distance Vector (AODV), Dynamic Source Routing (DSR), and Zigbee Tree Routing (ZTR), all of them working with the IEEE 802.15.4 MAC layer. Results show how some communication metrics affect performance, throughput, reliability and energy consumption. It can be concluded that MPH is an efficient protocol since it reaches the best performance against the other three protocols under evaluation, such as 19.3% reduction of packet retransmissions, 26.9% decrease of overhead, and 41.2% improvement on the capacity of the protocol for recovering the topology from failures with respect to AODV protocol. We implemented and tested MPH in a real network of 99 nodes during ten days and analyzed parameters as number of hops, connectivity and delay, in order to validate our Sensors 2014, 14 22812 simulator and obtain reliable results. Moreover, an energy model of CC2530 chip is proposed and used for simulations of the four aforementioned protocols, showing that MPH has 15.9% reduction of energy consumption with respect to AODV, 13.7% versus DSR, and 5% against ZTR.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
Multi-parent hierarchical (MPH) link formation process.
Figure 2.
Figure 2.
Wireless nodes.
Figure 3.
Figure 3.
Real network.
Figure 4.
Figure 4.
Average delay per day in source nodes.
Figure 5.
Figure 5.
Average delay per day in relay nodes.
Figure 6.
Figure 6.
Average hops per day in source nodes.
Figure 7.
Figure 7.
Average hops per day in relay nodes.
Figure 8.
Figure 8.
Average number of tries per day in source nodes.
Figure 9.
Figure 9.
Average number of tries per day in relay nodes.
Figure 10.
Figure 10.
Network topology.
Figure 11.
Figure 11.
Average retransmissions and CSMA/CA retries vs. time (s).
Figure 12.
Figure 12.
The percent of overhead vs. time.
Figure 13.
Figure 13.
Percentage of discovered routes vs. time.
Figure 14.
Figure 14.
Recovery time depending on the percent of nodes off for the four protocols.
Figure 15.
Figure 15.
Conceptual scheme.
Figure 16.
Figure 16.
Flowchart scheme of the energy model for node i.
Figure 17.
Figure 17.
Global energy consumption.
Figure 18.
Figure 18.
Local energy consumption.
Figure 19.
Figure 19.
Consumed energies for AODV, DSR, ZTRand MPH.
See this image and copyright information in PMC

References

    1. Baronti P., Pillai P., Chook V., Chessa S., Gotta A., Hu Y. Wireless sensor networks: A survey on the state of the art and the 802.15.4 and ZigBee standards. Comput. Commun. 2006;30:1655–1695.
    1. Mahapatra A., Anand K., Agrawal D. QoS and energy aware routing for real-time traffic in wireless sensor networks. Comput. Commun. 2006;29:437–445.
    1. Wo X., Chen G., Das S. Avoiding Energy Holes in Wireless Sensor Networks with Nonuniform Node Distribution. IEEE Trans. Parallel Distrib. Syst. 2008;19:710–720.
    1. Chen J., Li J., He S., Sun Y., Chen H. Energy-Efficient Coverage Based on Probabilistic Sensing Model in Wireless Sensor Networks. IEEE Commun. Lett. 2010;14:833–835.
    1. Gao Q., Blow K.J., Holding D.J., Marshall I.W., Peng X.H. Radio range adjustment for energy efficient wireless sensor networks. Ad Hoc Netw. 2006;4:75–82.

Publication types

MeSH terms

LinkOut - more resources