The involvement of wireless sensor networks in large-scale real-time applications is exponentially growing. These applications can range from hazardous area supervision to military applications. In such critical contexts, the simultaneous improvement of the quality of service and the network lifetime represents a big challenge. To meet these requirements, using multiple mobile sinks can be a key solution to accommodate the variations that may affect the network. Recent studies were based on predefined mobility models for sinks and relied on multi-hop routing techniques. Besides, most of these studies focused only on improving energy consumption without considering QoS metrics. In this paper, multiple mobile sinks with random mobile models are used to establish a tradeoff between power consumption and the quality of service. The simulation results show that using hierarchical data routing with random mobile sinks represents an efficient method to balance the distribution of the energy levels of nodes and to reduce the overall power consumption. Moreover, it is proven that the proposed routing methods allow for minimizing the latency of the transmitted data, increasing the reliability, and improving the throughput of the received data compared to recent works, which are based on predefined trajectories of mobile sinks and multi-hop architectures.

For large-scale distributed systems, Data centric communication based on the publish/subscribe paradigm plays a key role on traffic volume control. More data filtering efficient and adaptive to different traffic conditions bring some solutions at the high layers of the communication model. DDS and OPC-DX are the most adopted solutions, in real-time data centric sensor networks. Some Real-time transport and MAC protocols are proposed in the literature to support these types of networks. Existing MAC protocols, scheduling based, collision free, contention based or hybrid schemes focus more on optimizing system throughput and do not adequately consider the requirements of sensor networks. The key challenge remains to provide predictable delay and/or prioritization guarantees while minimizing overhead packets and energy consumption. It is widely known that control area networks (CAN) are used in real-time, distributed and parallel processing. In this paper we propose to use of the WCAN protocol in data centric communications model to manage concurrency.