No abstract

Communication and information technologies play crucial roles in the smart grid system. Wireless communications offer many unique features to utilities. Real-time capability and high efficiency under heavy load are vital capabilities for smart grid wireless communications. However, the existing medium access control (MAC) protocols for low-rate and short-range wireless transfer in the literature mainly aim to achieve the objectives of low energy consumption and self-configuration and rarely address these requirements under heavy traffic intensity. This paper presents a real-time, efficient, and lightweight MAC (RE-MAC) protocol to support smart grid applications, based on priority node polling and a hybrid scheme. The upper bounds of packet delay are determined using the embedded Markov chain method, and the simulation results demonstrate that the protocol can achieve predictable, real-time, and efficient performance.

The system of post-earthquake information rapid report can make people survive the aftershock, therefore the alarm of seismograph nodes in the system should be transferred as soon as possible. In this paper, a priority node MAC protocol for mobile ad hoc networks is proposed. The priority node token ring approach is used for the transmission of low delay information. By the embedded Markov chain method, the mean queue length of the high priority node and the general node are obtained, and verified by simulations. The delay performance was studied with simulations, the mean delay of the high priority node is less than the general node, and the high priority node owns low delay transmission even when traffic intensity is heavy. According to the total traffic delay, this protocol outperforms the CSMA priority MAC protocol, and our protocol keeps low delay of the high priority node and general node without dropping frames under the heave load. This feature is essential for earthquake surveillance.

Disaster monitoring is a primary task for wireless sensor networks. Systems for the rapid reporting of earthquake information are a crucial aspect of disaster monitoring. Furthermore, during emergency rescue after a large earthquake, wireless sensor networks can provide pictures and sound information to save lives. Therefore, when accompanied by multimedia data flow, the alert and seismic data sent by the seismic monitoring nodes must be sufficiently fast. We present herein the architecture of a collaborative disaster-monitoring system that can obtain seismic data in a highly energy-efficient manner. In this paper, a hybrid superior node token ring MAC scheme is proposed for disaster monitoring in wireless sensor networks. This scheme consists of set-up and steady-state stages. A clustering approach was proposed for heterogeneous networks during the set-up stage. The proposed MAC operates in the duty cycle mode at the steady-state stage and is based on the virtual token ring of ordinary nodes, the polling all the superior nodes in one period, and alert transmissions with a low-power listening and shortened preamble approach during the sleep state. The proposed scheme can simultaneously satisfy the requirements of three types of data in disaster-monitoring applications. Based on embedded Markov chains, a model of the proposed MAC was developed and the mean queue length, mean cycle time, and mean upper bound of the frame delay were obtained. Using simulations under various conditions, the clustering approach performed better than the pLEACH approach, and the theoretical results of the proposed MAC were verified. We found that alerts and superior data have outstanding delay and throughput performances even under heavy traffic intensity, and the proposed MAC can provide a data rate of several hundred kb/s for superior and ordinary data. Considering all three types of data, the frame delay performances of the proposed MAC are better than those of the WirelessHART and DRX schemes, and the alert data of the proposed MAC have a maximum frame delay of 15 ms. These satisfy the application requirements of disaster monitoring.