Energy based proficiency analysis of ad-hoc routing protocols in wireless sensor networks

In a densely deployed sensor node network, each sensor nodes sense data and transmit it to a particular sink through multi-hop communications. Sensor nodes deployed nearby the sink node need to convey some extra data and control packets and therefore undergo much quicker energy depletion rates and so they have considerably smaller lifespan. This may discontinue network from functioning for a long time. Herein, we have analyzed the lifetime of sensor networks by using AODV, DSR, DYMO and ZRP protocol under different node density. Network Lifetime, throughput, energy consumption analysis, Average end to end delay, work efficiency, packet delivery ratio and packet latency (jitter) of each protocol has been demonstrated. The research of the usefulness of some prevailing methodologies towards lifespan estimation of sensor network has been carried out and simulation results are used to confirm the analysis. Behavior of protocols is observed under different energy models like generic, mica-motes and micaz. ZRP protocol consumes maximum energy under generic model and least energy under Micaz model. Average energy consumption is highest for generic model. For small number of nodes jitter of DYMO is more while for large number of nodes ZRP produces maximum jitter. DYMO produces maximum end to end delay while AODV produces minimum delay. Micaz model give maximum lifetime to a network. Energy consumption in transmission and receiving is highest for generic model. Throughput, work efficiency and packet delivery ratio is highest for DSR protocol.

[1]  Mahendra Srivastava,et al.  Performance Analysis of ZRP over AODV, DSR and DYMO for MANET under Various Network Conditions using QualNet Simulator , 2013 .

[2]  Charles E. Perkins,et al.  Ad-hoc on-demand distance vector routing , 1999, Proceedings WMCSA'99. Second IEEE Workshop on Mobile Computing Systems and Applications.

[3]  Weili Wu,et al.  Wireless Sensor Networks and Applications , 2008 .

[4]  Israr Ullah,et al.  BeeSensor: An energy-efficient and scalable routing protocol for wireless sensor networks , 2012, Inf. Sci..

[5]  Dilli Ravilla,et al.  Energy Management in Zone Routing Protocol (ZRP) , 2012 .

[6]  David A. Maltz,et al.  DSR: the dynamic source routing protocol for multihop wireless ad hoc networks , 2001 .

[7]  Jonathan Billington,et al.  On Modelling and Analysing the Dynamic MANET On-Demand (DYMO) Routing Protocol , 2009, Trans. Petri Nets Other Model. Concurr..

[8]  Ian F. Akyildiz,et al.  Sensor Networks , 2002, Encyclopedia of GIS.

[9]  Ramesh Govindan,et al.  Wireless sensor networks , 2003, Comput. Networks.

[10]  Qing-hua Li,et al.  A Novel Sink Mobility Off-line Algorithm for Avoiding Energy Hole in Wireless Sensor Network , 2014, J. Comput..

[11]  Kok-Poh Ng,et al.  Energy-balanced dynamic source routing protocol for wireless sensor network , 2013, 2013 IEEE Conference on Wireless Sensor (ICWISE).

[12]  Anshul Shrotriya,et al.  Energy Efficient Modeling of Wireless Sensor Networks Based on Different Modulation Schemes Using QualNet , 2012 .

[13]  Weili Wu,et al.  Wireless Sensor Networks and Applications (Signals and Communication Technology) , 2007 .

[14]  Kalpana Sharma,et al.  Comparative Analysis of Routing Protocols in Ad-hoc Networks , 2014 .

[15]  Xin Jin,et al.  An elaborate chronological and spatial analysis of energy hole for wireless sensor networks , 2013, Comput. Stand. Interfaces.