scholarly journals A New TDMA Scheduling Algorithm for Data Collection over Tree-Based Routing in Wireless Sensor Networks

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Vahid Zibakalam

Data collection is one of the most important tasks in Wireless Sensor Networks (WSNs) where a set of sensors measure properties of a phenomenon of interest and send their data to the sink. Minimizing the delay of the data collection is important for applications in which certain actions based on deadline are needed, such as event-based and mission-critical applications. Time Division Multiple Access (TDMA) scheduling algorithms are widely used for quick delivery of data with the objective of minimizing the time duration of delivering data to the sink, that is, minimizing the delay. In this paper, we propose a new centralized TDMA scheduling algorithm that is based on nodes congestion for general ad hoc networks. In the proposed algorithm, the scheduling is obtained using colouring of the original network. Colouring the original network is accomplished based on congestion degree of nodes. The simulation results indicate that the performance of our algorithm is better than that of node-based and level-based scheduling algorithms. We will also show that the performance of our proposed algorithm depends on the distribution of the nodes across the network.

2012 ◽  
Vol 4 ◽  
pp. 32-37
Author(s):  
Jin Song Chen

This paper introduces the basics of wireless sensor networks, focusing on the concept of sensor network data collection, data collection mechanisms, data collection in-network data aggregation, data collection and data collection applications Research. This paper presents the data collection in WSN node scheduling concept, analyzed the two data collection in WSN scheduling mechanism, which is based on data collection interval node scheduling mechanism and turn the data based on perceived probability of node sleep scheduling mechanism.


2016 ◽  
Vol 4 (1) ◽  
pp. 41-45
Author(s):  
Ho-Ting Wu ◽  
◽  
Chih-Ching Chen ◽  
Kai-Wei Ke ◽  
Song-Ferng Wang

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