Using Machine Learning and Big Data Analytics to Prioritize Outpatients in HetNets

In this paper, we introduce machine learning approaches that are used to prioritize outpatients (OP) according to their current health state, resulting in self-optimizing heterogeneous networks (HetNet) that intelligently adapt according to users' needs. We use a naïve Bayesian classifier to analyze data acquired from OPs' medical records, alongside data from medical Internet of Things (IoT) sensors that provide the current state of the OP. We use this machine learning algorithm to calculate the likelihood of a life-threatening medical condition, in this case an imminent stroke. An OP is assigned high-powered resource blocks (RBs) according to the seriousness of their current health state, enabling them to remain connected and send their critical data to the designated medical facility with minimal delay. Using a mixed integer linear programming formulation (MILP), we present two approaches to optimizing the uplink side of a HetNet in terms of user-RB assignment: a Weighted Sum Rate Maximization (WSRMax) approach and a Proportional Fairness (PF) approach. Using these approaches, we illustrate the utility of the proposed system in terms of providing reliable connectivity to medical IoT sensors, enabling the OPs to maintain the quality and speed of their connection. Moreover, we demonstrate how system response can change according to alterations in the OPs' medical conditions

Energy efficiency considerations in software‐defined wireless body area networks

Wireless body area networks (WBAN) provide remote services for patient monitoring which allows healthcare practitioners to diagnose, monitor, and prescribe them without their physical presence. To address the shortcomings of WBAN, software-defined networking (SDN) is regarded as an effective approach in this prototype. However, integrating SDN into WBAN presents several challenges in terms of safe data exchange, architectural framework, and resource efficiency. Because energy expenses account for a considerable portion of network expenditures, energy efficiency has to turn out to be a crucial design criterion for modern networking methods. However, creating energy-efficient systems is difficult because they must balance energy efficiency with network performance. In this article, the energy efficiency features are discussed that can widely be used in the software-defined wireless body area network (SDWBAN). A comprehensive survey has been carried out for various modern energy efficiency models based on routing algorithms, optimization models, secure data delivery, and traffic management. A comparative assessment of all the models has also been carried out for various parameters. Furthermore, we explore important concerns and future work in SDWBAN energy efficiency

A priority-based energy efficient multi-hop routing protocol with congestion control for wireless body area network

Wireless Body Area Networks (WBANs) are advanced and integrated monitoring networks for healthcare applications. In these networks, different types of Biomedical Sensor Nodes (BSNs) are used to monitor physiological parameters of the human body. The BSNs have limited resources such as energy, memory and computation power. These limited resources make the network challenging especially in terms of energy consumption. Efficient routing schemes are required to save the energy during communication processes. Additionally, the BSNs generate sensitive and non-sensitive data packets, which need to be routed according to their priority. In order to address these problems, a priority-based Energy Efficient Multihop Routing protocol with congestion control (3EMR) for wireless body area network was developed that comprises of three different schemes. First, an Optimal Next-hop Selection (ONS) scheme was developed based on the cost function of routing parameters to dynamically select best next-hop for forwarding data packets. Second, a Priority Based Routing (PBR) scheme was developed to forward data packets according to data priority, which is based on sensitivity of the data with regards to patience’s life. Third, a Congestion Avoidance and Mitigation (CAM) scheme was developed to save energy consumption and packet loss due to congestion by considering packet flow adjustment and congestion zone avoidance based strategy. It improvement is benchmarked against related solutions, and they are Healthcare-aware Optimized Congestion Avoidance (HOCA), Differentiated Rate control for Congestion (DRC), Priority based Cross Layer Routing (PCLR), Even Energy-consumption and Backside Routing (EEBR), and Energy Efficient Routing (EER) scheme. The simulation results demonstrated that the 3EMR scheme achieved significant improvement in terms of increased network lifetime by 31.4%, increased throughput by 33.2%, reduced packet loss 30.9%, increased packet delivery ratio by 21.1% and reduced energy consumption 26.8%. Thus, the proposed routing scheme has proven to be an energy efficient solution for data communication in wireless body area networks

Multi-constrained mechanism for intra-body area network quality-of-service aware routing in wireless body sensor networks

Wireless Body Sensor Networks (WBSNs) have witnessed tremendous research interests in a wide range of medical and non-medical fields. In the delaysensitive application scenarios, the critical data packets are highly delay-sensitive which require some Quality-of-Service (QoS) to reach the intended destinations. The categorization of data packets and selection of poor links may have detrimental impacts on overall performance of the network. In WBSN, various biosensors transmit the sensed data towards a destination for further analysis. However, for an efficient data transmission, it is very important to transmit the sensed data towards the base station by satisfying the QoS multi-constrained requirements of the healthcare applications in terms of least end-to-end delay and high reliability, throughput, Packet Delivery Ratio (PDR), and route stability performance. Most of the existing WBSN routing schemes consider traffic prioritization to solve the slot allocation problem. Consequently, the data transmission may face high delays, packet losses, retransmissions, lack of bandwidth, and insufficient buffer space. On the other hand, an end-to-end route is discovered either using a single or composite metric for the data transmission. Thus, it affects the delivery of the critical data through a less privileged manner. Furthermore, a conventional route repair method is considered for the reporting of broken links which does not include surrounding interference. As such, this thesis presents the Multi-constrained mechanism for Intra- Body Area Network QoS aware routing (MIQoS) with Low Latency Traffic Prioritization (LLTP), Optimized Route Discovery (ORD), and Interference Adaptive Route Repair (IARR) schemes for the healthcare application of WBSN with an objective of improving performance in terms of end-to-end delay, route stability, and throughput. The proposed LLTP scheme considers various priority queues with an optimized scheduling mechanism that dynamically identifies and prioritizes the critical data traffic in an emergency situation to enhance the critical data transmission. Consequently, this will avoid unnecessary queuing delay. The ORD scheme incorporates an improved and multi-facet routing metric, Link Quality Metric (LQM) optimizes the route selection by considering link delay, link delivery ratio, and link interference ratio. The IARR scheme identifies the links experiencing transmission issues due to channel interference and makes a coherent decision about route breakage based on the long term link performance to avoid unnecessary route discovery notifications. The simulation results verified the improved performance in terms of reducing the end-to-end delay by 29%, increasing the throughput by 22% and route stability by 26% as compared to the existing routing schemes such as TTRP, PA-AODV and standard AODV. In conclusion, MIQoS proves to be a suitable routing mechanism for a wide range of interesting applications of WBSN that require fast, reliable and multi-hop communication in heavily loaded network traffic scenarios

A Priority based Cross Layer Routing Protocol for healthcare applications

Wireless body area networks (WBANs) represent one of the most promising approaches for improving the quality of life, allowing remote patient monitoring and other healthcare applications. Data dissemination and medium access in a WBAN are critical issues that impact the network reliability, the efficiency and the total energy consumed by the network. In this paper, we propose a Priority-based Cross Layer Routing Protocol (PCLRP) along with a Priority Cross Layer Medium Access Channel protocol (PCLMAC) for healthcare applications. PCLRP combined with PCLMAC ensures reliable traffic dissemination and customized channel access for intra- and inter-body communications. Simulation results show that the proposed protocol achieves customized quality of services and outperforms state of the art existing protocols in terms of power consumption, packet delivery ratio and delay