EOCC-TARA for Software Defined WBAN

Wireless Body Area Network (WBAN) is a promising cost-effective technology for the privacy confined military applications and healthcare applications like remote health monitoring, telemedicine, and e-health services. The use of a Software-Defined Network (SDN) approach improves the control and management processes of the complex structured WBANs and also provides higher flexibility and dynamic network structure. To seamless routing performance in SDN-based WBAN, the energy-efficiency problems must be tackled effectively. The main contribution of this paper is to develop a novel Energy Optimized Congestion Control based on Temperature Aware Routing Algorithm (EOCC-TARA) using Enhanced Multi-objective Spider Monkey Optimization (EMSMO) for SDN-based WBAN. This algorithm overcomes the vital challenges, namely energy-efficiency, congestion-free communication, and reducing adverse thermal effects in WBAN routing. First, the proposed EOCC-TARA routing algorithm considers the effects of temperature due to the thermal dissipation of sensor nodes and formulates a strategy to adaptively select the forwarding nodes based on temperature and energy. Then the congestion avoidance concept is added with the energy-efficiency, link reliability, and path loss for modeling the cost function based on which the EMSMO provides the optimal routing. Simulations were performed, and the evaluation results showed that the proposed EOCC-TARA routing algorithm has superior performance than the traditional routing approaches in terms of energy consumption, network lifetime, throughput, temperature control, congestion overhead, delay, and successful transmission rate

Congestion control for differentiated healthcare service delivery in emerging heterogeneous wireless body area networks

Rapid advances in Information and Communications Technologies are enabling the wide diffusion of healthcare systems which allow a continuous remote patient monitoring and diagnostics by doctors. The need for pervasive and ubiquitous healthcare services has accelerated the development of heterogeneous communication architectures that integrate one or more different types of wired and wireless network technologies such as those used in the Internet, and in cellular, wireless body networks, and ad hoc networks. However, these modern healthcare systems have established some additional critical requirements and challenges, compared to traditional wireless networks, such as reliability and the timely access to diagnostic information without failure. The main aim of this article is to propose a healthcare traffic control over the modern heterogeneous wireless network to avoid congestion phenomena and guarantee QoS (Quality of Service) in terms of service reliability and responsiveness. First, a proportional fair allocation control strategy at each healthcare terminal device/router is implemented to regulate the rate of data flow proportionally to the information priority. The priority can be related to both the bandwidth requirement for the reliable communication of a vital signal and to the level of emergency in specific acute care, clinical disease and outbreak/disaster situations. Secondly, we present a congestion control based on the adaptive fairness criterion that can deal with differentiated and dynamic healthcare scenarios. A simulator environment has been built to validate the effectiveness of the proposed approaches

Enhancing the efficiency of electricity utilization through home energy management systems within the smart grid framework

The concept behind smart grids is the aggregation of “intelligence” into the grid, whether through communication systems technologies that allow broadcast/data reception in real-time, or through monitoring and systems control in an autonomous way. With respect to the technological advancements, in recent years there has been a significant increment in devices and new strategies for the implementation of smart buildings/homes, due to the growing awareness of society in relation to environmental concerns and higher energy costs, so that energy efficiency improvements can provide real gains within modern society. In this perspective, the end-users are seen as active players with the ability to manage their energy resources, for example, microproduction units, domestic loads, electric vehicles and their participation in demand response events. This thesis is focused on identifying application areas where such technologies could bring benefits for their applicability, such as the case of wireless networks, considering the positive and negative points of each protocol available in the market. Moreover, this thesis provides an evaluation of dynamic prices of electricity and peak power, using as an example a system with electric vehicles and energy storage, supported by mixed-integer linear programming, within residential energy management. This thesis will also develop a power measuring prototype designed to process and determine the main electrical measurements and quantify the electrical load connected to a low voltage alternating current system. Finally, two cases studies are proposed regarding the application of model predictive control and thermal regulation for domestic applications with cooling requirements, allowing to minimize energy consumption, considering the restrictions of demand, load and acclimatization in the system