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The Effect of Routing Protocols on End-to-End Delay and Energy consumption in event driven Wireless Sensor Networks


D.D.Chaudhary, V. M. Wadhai, L.M.Waghmare


Vol. 10  No. 10  pp. 19-23


Wireless Sensor Networks (WSN) have become an very important technology for many applications such as the monitor and control of physical environment in Military, Industry and civilian areas, Home automation, Disaster monitoring and control, Target detection, Target tracking, Tactical systems and so on. Since power requirement of sensor nodes is depends on range of application and its availability is limited, so that energy efficient protocols has to be design in order to extend the lifetime of the networks. In most of the applications it is very difficult to replace the battery after its expiry and in some applications tiny sensor nodes typically operate with a small size of battery power so that energy efficient operations is very important issue. Energy conservation at MAC layer is found to be the most effective one because it controls the radio operations directly. In addition to this end-to-end delay is also one of the most critical issues for WSN application. Sensor networks deployed in industrial environment have very strict timing constraints on operation and its final end-to-end delay. However, the end-to-end delay is difficult to predict and measure for event- driven sensor networks, where nodes generate and propagate data only when an event of interest occur and thereby producing unpredictable traffic load. In this paper analyses is done for the end to end delay and energy consumption in event driven wireless sensor network by using two protocols i.e. Ad-hoc On-demand Distance Vector (AODV) and Destination Sequence Distance Vector (DSDV), under IEEE 802.11 as MAC layer protocol. The simulation results shows that end to end delays by using DSDV are lesser than AODV and it also shows slightly lower energy consumption than AODV in different traffic conditions.


AVDV, DSDV, End-to-end delay, Energy consumption, Wireless sensor networks