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There have been significant advances in the field of Internet of Things (IoT) recently. At the same time there exists an ever-growing demand for ubiquitous healthcare systems to improve human health and well-being. In most of IoTbased patient monitoring systems, especially at smart homes or hospitals, there exists a bridging point (i.e., gateway) between a sensor network and the Internet which often just performs basic functions such as translating between the protocols used in the Internet and sensor networks. These gateways have beneficial knowledge and constructive control over both the sensor network and the data to be transmitted through the Internet. In this paper, we exploit the strategic position of such gateways to offer several higher-level services such as local storage, real-time local data processing, embedded data mining, etc., proposing thus a Smart e-Health Gateway. By taking responsibility for handling some burdens of the sensor network and a remote healthcare center, a Smart e-Health Gateway can cope with many challenges in ubiquitous healthcare systems such as energy efficiency, scalability, and reliability issues. A successful implementation of Smart e-Health Gateways enables massive deployment of ubiquitous health monitoring systems especially in clinical environments. We also present a case study of a Smart e-Health Gateway called UT-GATE where some of the discussed higher-level features have been implemented. Our proof-of-concept design demonstrates an IoT-based health monitoring system with enhanced overall system energy efficiency, performance, interoperability, security, and reliability.

Power management of NoC-based many-core systems with runtime application mapping becomes more challenging in the dark silicon era. It necessitates a multi-objective control approach to consider an upper limit on total power consumption, dynamic behaviour of workloads, processing elements utilization, per-core power consumption, and load on networkon-chip. In this paper, we propose a multi-objective dynamic power management method that simultaneously considers all of these parameters. Fine-grained voltage and frequency scaling, including near-threshold operation, and per-core power gating are utilized to optimize the performance. In addition, a disturbance rejecter is designed that proactively scales down activity in running applications when a new application commences execution, to prevent sharp power budget violations. Simulations of dynamic workloads and mixed time-critical application profiles show that our method is effective in honoring the power budget while considerably boosting the system throughput and reducing power budget violation, compared to the state-of-the-art power management policies.

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A novel Internet of Things based architecture supporting scalability and fault tolerance for healthcare is presented in this paper. The wireless system is constructed on top of 6LoWPAN energy efficient communication infrastructure to maximize the operation time. Fault tolerance is achieved via backup routing between nodes and advanced service mechanisms to maintain connectivity in case of failing connections between system nodes. The presented fault tolerance approach covers many fault situations such as malfunction of sink node hardware and traffic bottleneck at a node due to a high receiving data rate. A method for extending the number of medical sensing nodes at a single gateway is presented. A complete system architecture providing a quantity of features from bio-signal acquisition such as Electrocardiogram (ECG), Electroencephalography (EEG), and Electromyography (EMG) to the representation of graphical waveforms of these gathered bio-signals for remote real-time monitoring is proposed.

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