Channel Access Management in Data Intensive Sensor Networks

There are considerable challenges for channel access in Data Intensive Sensor Networks - DISN, supporting Data Intensive Applications like Structural Health Monitoring. As the data load increases, considerable degradation of the key performance parameters of such sensor networks is observed. Successful packet delivery ratio drops due to frequent collisions and retransmissions. The data glut results in increased latency and energy consumption overall. With the considerable limitations on sensor node resources like battery power, this implies that excessive transmissions in response to sensor queries can lead to premature network death. After a certain load threshold the performance characteristics of traditional WSNs become unacceptable. Research work indicates that successful packet delivery ratio in 802.15.4 networks can drop from 95% to 55% as the offered network load increases from 1 packet/sec to 10 packets/sec. This result in conjunction with the fact that it is common for sensors in an SHM system to generate 6-8 packets/sec of vibration data makes it important to design appropriate channel access schemes for such data intensive applications.In this work, we address the problem of significant performance degradation in a special-purpose DISN. Our specific focus is on the medium access control layer since it gives a fine-grained control on managing channel access and reducing energy waste. The goal of this dissertation is to design and evaluate a suite of channel access schemes that ensure graceful performance degradation in special-purpose DISNs as the network traffic load increases.First, we present a case study that investigates two distinct MAC proposals based on random access and scheduling access. The results of the case study provide the motivation to develop hybrid access schemes. Next, we introduce novel hybrid channel access protocols for DISNs ranging from a simple randomized transmission scheme that is robust under channel and topology dynamics to one that utilizes limited topological information about neighboring sensors to minimize collisions and energy waste. The protocols combine randomized transmission with heuristic scheduling to alleviate network performance degradation due to excessive collisions and retransmissions. We then propose a grid-based access scheduling protocol for a mobile DISN that is scalable and decentralized. The grid-based protocol efficiently handles sensor mobility with acceptable data loss and limited overhead. Finally, we extend the randomized transmission protocol from the hybrid approaches to develop an adaptable probability-based data transmission method. This work combines probabilistic transmission with heuristics, i.e., Latin Squares and a grid network, to tune transmission probabilities of sensors, thus meeting specific performance objectives in DISNs. We perform analytical evaluations and run simulation-based examinations to test all of the proposed protocols