Most of the MAC protocols proposed for the wireless sensor networks (WSN) assume sensor nodes to be static and therefore they usually fail or provide very bad network performance in mobile sensor networks. Since WSN mobile applications have become popular nowadays, there is a need for MAC protocols that consider mobility. In this paper, we propose a mobility-aware MAC protocol for WSN that can work with satisfactory performance in both stationary and mobile sensor networks. Furthermore, most of the WSN mobile applications are considered critical ones (e.g. a patient assistance system which monitors patients' health via wearable bio-sensors). Such applications require very quick responses. So, in addition to handling mobility, the proposed MAC protocol considers the problem of latency as well. In summary, this paper proposes a WSN MAC protocol (MD-SMAC) that is considered to be mobility-aware, delay-sensitive and provides satisfactory level of energy efficiency. In addition, we study the performance of the proposed MD-SMAC protocol by simulating it using the NS-2 simulator and comparing it to other WSN MAC protocols. The results show that the MD-SMAC protocol outperforms other existing WSN MAC protocols in terms of mobility-handling, delay-reduction, and energy-efficiency in scenarios involving mobile sensors.
Social networks and Internet of things are two paradigms when integrated a new paradigm Internet of Everything is established that has its impact on revolutionizing various fields such as engineering, industry and healthcare. Social networks became nowadays of the most important web services on which people heavily rely, thus became a major source for information extraction for rational decision making considering individuals as social or socio sensors. Furthermore, people using sensors especially biological sensors enabled the use of internet of things technology in building intelligent healthcare systems. One of the challenges facing the design of such systems is the design of an intelligent recommender system that is able to deal with such big data. For that, this paper proposes a framework to develop an enhanced intelligent expert advisor-based health monitoring and disease awareness system. The proposed framework enables the researchers to design advisory systems that are able to observe physiological signals through the use of different bio sensors and integrate it with historical medical data together with the massive data collected from social networks to provide accurate alerts and recommendations for many ailments inspected. The proposed Framework is designed to facilitate generic, dynamic and scalable process of integrating different types of social networks and bio sensors.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.