Monitoring and controlling smart grid assets in a timely and reliable manner is highly desired for emerging smart grid applications. Wireless Sensor Networks (WSNs) are anticipated to be widely utilized in a broad range of smart grid applications due to their numerous advantages along with their successful adoption in various critical areas including military and health care. Despite these advantages, the use of WSNs in such critical applications has brought forward a new challenge of fulfilling the Quality of Service (QoS) requirements of these applications. Providing QoS support is a challenging issue due to highly resource constrained nature of sensor nodes, unreliable wireless links and harsh operation environments. In this thesis we critically investigate the problem of QoS provisioning in WSNs. We identify challenges, limitations and requirements for applying QoS provisioning for WSNs in smart grid applications. We find that the topic of data prioritization techniques at the MAC layer to provide delay bounds in condition monitoring applications is not well developed. We develop six novel QoS schemes that provide data differentiation and reduce the latency of high priority traffic in a smart grid context. These schemes are namely; Delay-Responsive Cross layer (DRX), Fair and Delay-aware Cross layer (FDRX), Delay-Responsive Cross layer with Linear backoff (LDRX), Adaptive Realistic and Stable Model (ARSM), Adaptive Inter-cluster head Delay Control (AIDC) and QoS-aware GTS Allocation (QGA). Furthermore, we propose a new Markov-based model for IEEE 802.15.4 MAC namely, Realistic and Stable Markov-based (RSM). RSM considers actual network conditions and enhances the stability of the WSNs. We show through analytical and simulation results that all of the presented schemes reduce the end-to-end delay while maintaining good energy consumption and data delivery values. |