Enhancing Decision Making through Combined Classification Techniques and Probabilistic Data Analysis for Ubiquitous Healthcare Anomaly Monitoring

A multi-agent data-analytics-based approach to ubiquitous healthcare monitoring is presented in this paper. The proposed architecture gathers a patient’s vital data using wireless body area networks, and the transmitted information is separated into binary component parts and divided into related dataset categories using several classification techniques. A probabilistic procedure is then used that applies a normal (Gaussian) distribution to the analysis of new medical entries in order to assess the gravity of the anomalies detected. Finally, a data examination is carried out to gain insight. The results of the model and simulation show that the proposed architecture is highly efficient in applying smart technologies to a healthcare system, as an example of a research direction involving the Internet of Things, and offers a data platform that can be used for both medical decision making and the patient’s wellbeing and satisfaction with their medical treatment

An Improved Adaptive CoAP Congestion Control Algorithm

The Constrained Application Protocol (CoAP) is one of the most emerging messaging protocols that have successfully fulfilled the need of the lightweight feature required to handle communication between constrained devices in IoT environment. However, these devices are generating a huge amount of messages and notifications which cause the network congestion. Then, the challenge addressed in this paper; consists of designing a suitable congestion control mechanism for CoAP that ensures a safe network operation while keeping the use of network resources efficient. To do so, this paper presents an improved congestion control algorithm for the estimation of a Retransmission Time Out (RTO) value to use in each transaction based on the packet loss ratio and the Round-Trip Time RTT of the previous transmission. A comprehensive analysis and evaluation of simulated results show that the proposed mechanism can appropriately achieve higher performance compared to the basic CoAP congestion control and alternative algorithms based on TCP

The SDN-MQTT for an interoperable smart home

This paper presents the design of SDN-MQTT for a smart home. It is a system combining the SDN technology that solves many technological difficulties in traditional networks, and the MQTT protocol that is arguably the most widely used for resource constrained IoT devices. These two technologies enable heterogeneous IoT devices to be interoperable and interact without any problems. Our proposed work ensures two levels of interoperability

An Improved Adaptive CoAP Congestion Control Algorithm

The Constrained Application Protocol (CoAP) is one of the most emerging messaging protocols that have successfully fulfilled the need of the lightweight feature required to handle communication between constrained devices in IoT environment. However, these devices are generating a huge amount of messages and notifications which cause the network congestion. Then, the challenge addressed in this paper; consists of designing a suitable congestion control mechanism for CoAP that ensures a safe network operation while keeping the use of network resources efficient. To do so, this paper presents an improved congestion control algorithm for the estimation of a Retransmission Time Out (RTO) value to use in each transaction based on the packet loss ratio and the Round-Trip Time RTT of the previous transmission. A comprehensive analysis and evaluation of simulated results show that the proposed mechanism can appropriately achieve higher performance compared to the basic CoAP congestion control and alternative algorithms based on TCP.</p

STRUCTURE OF GRÖBNER BASES WITH RESPECT TO BLOCK ORDERS

Abstract. In this paper we study the structure of Gröbner bases with respect to block orders. We extend Lazard’s theorem and the Gianni-Kalkbrenner theorem to the case of a zero-dimensional ideal whose trace in the ring generated by the first block of variables is radical. We then show that they do not hold for general zero-dimensional ideals. 1

Moving to the Edge-Cloud-of-Things: Recent Advances and Future Research Directions

Cloud computing has significantly enhanced the growth of the Internet of Things (IoT) by ensuring and supporting the Quality of Service (QoS) of IoT applications. However, cloud services are still far from IoT devices. Notably, the transmission of IoT data experiences network issues, such as high latency. In this case, the cloud platforms cannot satisfy the IoT applications that require real-time response. Yet, the location of cloud services is one of the challenges encountered in the evolution of the IoT paradigm. Recently, edge cloud computing has been proposed to bring cloud services closer to the IoT end-users, becoming a promising paradigm whose pitfalls and challenges are not yet well understood. This paper aims at presenting the leading-edge computing concerning the movement of services from centralized cloud platforms to decentralized platforms, and examines the issues and challenges introduced by these highly distributed environments, to support engineers and researchers who might benefit from this transition

An Efficient Approach for Storage Balancing in Wireless Sensor Networks

the use of mobile sinks in data collection has received much attention in recent years. In fact, mobility was introduced to solve problems that occur in data gathering with static sinks such as hotspots, quick energy depletion of sensor nodes and so on. Using mobile sinks provides an effective mechanism to improve reliability, security as well as connectivity within the network. Nevertheless, the sink’s mobility poses new challenges, especially when the sink follows an unpredictable movement while gathering data. In this case, the network will experience huge latency and suffer from significant packet loss particularly when sensor nodes do not have enough memory storage to buffer collected data between two successive visits of the mobile sink. In this paper we propose a new approach in which sensor nodes cooperate to manage the storage and prevent packet drops. When a node’s memory is almost full, it offloads its data to its neighbor nodes in function of their free spaces.  In case there are no neighbor nodes with sufficient storage space, the sink is urgently notified about the overloaded region that needs to be rapidly dumped. Simulation results reveal that our proposed approach decreases drastically the loss of packets and balances the sensor network

A Context-Aware Framework to Manage the Priority of Injured Persons Arriving at Emergencies

The integration of Internet of Medical Things (IoMT) in Hospital system has modified the traditional medical service as a reactive system based on hospitalization and diseases to a preventive and interoperable system based mainly on the interactive data flow between patient and health professionals. Using medical connected objects (MCOs), medical data is collected and processed. According to gathered data, the new medical system should be able to sort patient states based on urgent and critical vital signs, and consequently priorities are defined. In this paper, we direct our attention to manage priority in hospital emergencies in order to adapt dynamically operations and interactions with different stakeholders according to the changes in their execution context. Indeed, based on data sensed from MCOs implemented in ambulances, emergency rooms might be prepared to receive injured persons like victims of road accidents or other incidents. Therefore, we design a context-aware monitoring framework for injured people based on gathered medical data to manage priorities