Wireless Sensor Network
Wireless Sensor Network ( WSN) is composed of multiple sensors for monitoring physical or environmental conditions. Low power and low processing are the main features of nodes in the Wireless Sensor Network. Therefore, energy usage and lifetime in WSN applications must be optimized.
This topic proposes a new approach to minimizing energy usage, increasing sensor nodes’ longevity in the wireless sensor networks, and maintaining energy for a long time.
The first stage focuses on a process of Scheduling algorithm when the network tries to sense the data, and it consists of sleep and wake-up model. A task cycle will be introduced, as all nodes in the system regularly change their states when they sleep and wake up. Every sensor node is active and senses the object in a particular region, and other nodes are in the sleep state. It saves energy from sleep state sensors, and the sleep state sensor wakes up in the specific time interval and sends the question packet to the active node to determine the need for its presence or not. If the active sensor sends a ‘necessary’ packet, it activates the sensor to cover the region. It sleeps the active sensor during this time, the energy of the node calculated and updated in a table. When the energy level reaches a threshold value, the nodes change their states each other. As anyone node is in active in the range, the energy of neighbor nodes are minimized and life time increased.
The second step offers the possibility to route the information through active nodes if the object identified by the node is increased by the bandwidth. The initial path to send data from source to destination is chosen by a shortest path algorithm. The path changes its way based on energy levels during the routing energy of all nodes, and when the energy decreases at a specific level. The secondary route is chosen based on the energy-intensive nodes. In addition to the current algorithm , the proposed algorithm allows for an optimal increase in network lifespan, energy consumption and performance.
A hybrid of sensing and routing teachings improve the Network Life time, and Reduce the Energy Consumption.
Algorithm Involved : Any Scheduling Algorithm and Dijeshtra Shortest Path .
Simulation Tool : NS2
Testing Hardware to increase bandwidth : MICA 2 Mode