DOI:10.20894/IJCNES.
Periodicity: Bi Annual.
Impact Factor:
SJIF:5.217
Submission:Any Time
Publisher:IIR Groups
Language:English
Review Process:
Double Blinded
A sensor network typically comprises a large number of low-power, low-cost, tiny embedded devices with sensing capabilities, which are networked together to collect, process, and deliver information about a physical phenomenon of interest. The position of the nodes could be engineered or predetermined, such as in structural health monitoring, where nodes are placed at optimal locations to maximize the fidelity of measured vibrations for accurate and reliable diagnosis about the health of the structure. On other occasions, nodes could be placed randomly, allowing deployment of networks over inaccessible terrains or in disaster recovery operations. Wireless Sensor Networks (WSN) [1] have appeared as one of the most prominent enabling technologies of Micro-Electro-Mechanical Systems (MEMS)MEMS, which combines automated sensing, embedded computing, and wireless capabilities into tiny devices, bringing promises of understanding and incrementing nature at scales that were unimaginable before. Just like the invention of microscope has let us see things that were previously invisible to the naked eye, wireless sensor networks have enabled us not only to detect and measure a physical phenomenon with accuracy even at the microscopic level, but also to communicate the measured information across distances using the wireless medium. Wireless Sensor Networks is focused on developing low-power sensing the devices to enable large-scale, distributed, networked sensor system through the sense-IT project. This Concept is used for Data Communication as well as mobile computing is very purpose to used for wireless sensor networks. Deployment of sensor networks are increasing either manually or randomly to monitor physical environments in different applications such as military, agriculture, medical transport, industry etc. In monitoring of physical environments, the most important application of wireless sensor network is monitoring of critical conditions. The most important in monitoring application like critical condition is the sensing of information during emergency state from the physical environment where the network of sensors is deployed. In order to respond within a fraction of seconds in case of critical conditions like explosions, fire and leaking of toxic gases, there must be a system which should be fast enough. A big challenge to sensor networks is a fast, reliable and fault tolerant channel during emergency conditions to sink (base station) that receives the events. The main focus of this thesis is to discuss and evaluate the performance of two different routing protocols like Ad hoc On Demand Distance Vector (AODV) and Dynamic Source Routing (DSR) for monitoring of critical conditions with the help of important metrics like throughput and end-to-end delay in different scenarios. On the basis of results derived from simulation a conclusion is drawn on the comparison between these two different routing protocols with parameters like end-to-end delay and throughput.
