A Wireless Sensor Network Routing Algorithm Based on Zigbee

2014 ◽  
Vol 513-517 ◽  
pp. 1845-1849
Author(s):  
Hua Rui Wu ◽  
Li Zhu
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Large Scale ◽  
Routing Algorithm ◽  
Network Routing ◽  
Routing Algorithms ◽  
Wireless Sensor ◽  
Quantitative Relation ◽  
Analysis Model

Routing strategy with effective and saving energy is an important problem in the research on the application of wireless sensor network into the farmland micro climate and soil moisture monitoring,it analyzed the disadvantage of the layered tree routing algorithm and ZigBee routing algorithms in energy saving, combined with ZigBee network topology,establishing an optimal node analysis model based on fuzzy decision, bringing forward a new routing algorithm which is suitable for large-scale farmland gradient environment, this new algorithm find out the quantitative relation between energy consumption and routing node selecting strategy,which can greatly decrease the route hop number by routing discovery mechanism and create an optimum goal group. Simulation results showed that compared with the layered tree and ZigBee routing algorithms,the new routing algorithms can significantly reduce the energy consumption of routing process.

Routing Algorithm in Wireless Sensor Networks Based on Multi-Optimization Function

2015 ◽  
Vol 741 ◽  
pp. 386-389
Author(s):  
Jian Zhang
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Network Performance ◽  
Routing Algorithm ◽  
Network Routing ◽  
Wireless Sensor ◽  
Selection Function ◽  
Optimization Function

As the deficiencies of present Wireless Sensor Network Routing Protocol in extending network lifetime and improving network performance, a kind of Routing Algorithm based on Multi-optimization Function is proposed in order to achieve the optimization goals of balancing network node energy consumption and extending network lifetime. By introducing parameters like available energy of nodes, routing hops and physical distance between nodes into routing selection function, optimum path is set up. Therefore, the integrated optimization of Wireless Sensor Network performance is realized. As NS2 emulation result shows, this algorithm has achieved higher transmission reliability, lower energy consumption and much longer network lifetime. Compared with traditional directed diffusion algorithm, the rate of data transmission success has risen by 15.3%, utilization ratio of network energy by 9.7%, and network lifetime by 37.8%. Routing Algorithm based on Multi-optimization Function has more advantages in Wireless Sensor Network.

INVESTIGATING A WIRELESS SENSOR NETWORK OPTIMAL LIFETIME SOLUTION FOR LINEAR TOPOLOGIES

2006 ◽  
Vol 07 (01) ◽  
pp. 91-99 ◽  
Author(s):  
Keith Hellman ◽  
Michael Colagrosso
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Nearest Neighbor ◽  
Analytic Solution ◽  
Routing Algorithm ◽  
Optimal Solution ◽  
Routing Algorithms ◽  
Wireless Sensor ◽  
Global Knowledge ◽  
Alternative Solutions

We investigate a known optimal lifetime solution for a linear wireless sensor network through simulation, and propose alternative solutions where a known optimal solution does not exist. The network is heterogeneous in the sensors' energy distribution and also in the amount of data each sensor must communicate. As a basis for comparison, we analyze the lifetime of a network using a simple, nearest-neighbor routing algorithm, and an analytic solution to the optimal lifetime of networks meeting certain constraints. Alternative solutions considered range from those requiring global knowledge of the network to solutions using only next-neighbor knowledge. We compare the performance of all the routing algorithms in simulation.

Wireless Sensor Network Mobile Agent Routing Based on the Improved Ant Colony Algorithm

2014 ◽  
Vol 587-589 ◽  
pp. 2339-2345
Author(s):  
Jia Yan Li ◽  
Jun Ping Wang
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Mobile Agent ◽  
Large Scale ◽  
Ant Colony Algorithm ◽  
Routing Algorithm ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Communication Overhead ◽  
Redundant Data

This paper proposes a new wireless sensor routing algorithm by combining the ant colony algorithm with the mobile agent technology. This algorithm considers the distance and path energy overhead among nodes and residual node energy, equalizes the energy overhead in the network, improves the update rule of the ant colony information elements and speeds up convergence of the ant colony algorithm to get the optimal values. The simulation results indicate that this algorithm can improve the globalization and convergence speed, effectively reduce redundant data transmission and communication overhead, extend the network lifecycle and be very suitable for a large-scale wireless sensor network compared to other mobile agent routing algorithms.

scholarly journals A Cross Unequal Clustering Routing Algorithm for Sensor Network

2013 ◽  
Vol 13 (4) ◽  
pp. 200-205 ◽  
Author(s):  
Wang Tong ◽  
Wu Jiyi ◽  
Xu He ◽  
Zhu Jinghua ◽  
Charles Munyabugingo
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Energy Loss ◽  
Sensor Network ◽  
Routing Algorithm ◽  
High Energy ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Long Distance ◽  
Cluster Heads

In the routing protocol for wireless sensor network, the cluster size is generally fixed in clustering routing algorithm for wireless sensor network, which can easily lead to the “hot spot” problem. Furthermore, the majority of routing algorithms barely consider the problem of long distance communication between adjacent cluster heads that brings high energy consumption. Therefore, this paper proposes a new cross unequal clustering routing algorithm based on the EEUC algorithm. In order to solve the defects of EEUC algorithm, this algorithm calculating of competition radius takes the node’s position and node’s remaining energy into account to make the load of cluster heads more balanced. At the same time, cluster adjacent node is applied to transport data and reduce the energy-loss of cluster heads. Simulation experiments show that, compared with LEACH and EEUC, the proposed algorithm can effectively reduce the energy-loss of cluster heads and balance the energy consumption among all nodes in the network and improve the network lifetime

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