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The advent of the Internet of Things (IoT) augurs new cutting-edge applications in modern life such as smart cities and smart grids. These applications require protocols more efficient for ensuring the reliability of data communications in the IoT networks. Many works state that IoT cannot meet their demands without application protocols improvement with Artificial Intelligence (AI) as IoT are expected to generate unprecedented traffic giving IoT researchers access to data that can help in studying and analyzing the demands and develop application protocols conceptions to meet the requirement of IoT applications. In literature, several works introduced AI in some layers of the TCP/IP model including wireless communication and routing. In this article, an evaluation of application protocols HTTP, MQTT, DDS, XMPP, AMQP, and CoAP has been presented; and subsequently, the power consumption prediction of MQTT and COAP based on the linear regression model is analyzed, in order to enhance data communications in IoT applications.

Prediction of power consumption in smart grid and microgrid systems has become a major issue, it represents one of the most important factors in energy management systems (EMS). Recently, several models based on artificial intelligence techniques have been proposed to predict electricity consumption and production, mainly for household energy efficiency. In this paper, we evaluate different algorithms to predict the daily power consumption in a university campus microgrid context. We investigate the implementation of different prediction models in three different real datasets, considering four performance indicators to analyze their accuracy, such as Mean Squared Error, Mean Absolute Error, Mean Absolute Percentage Error, and R-square. Different approaches using time series: ARIMA, SARIMA, machine learning: SVM, XGBOOST, and deep learning: RNN, LSTM, and LSTM-RNN hybrid model were evaluated. Results prove that deep learning approaches achieve better results than time series and machine learning forecasting models. In this work, we prove that the RNN-LSTM hybrid model is the most appropriate model for university campus microgrid case with an accuracy between 83% and 93%.

In order to gather data more efficiently, a clustering hierarchy algorithm is used for data communication in wireless sensor networks (WSNs). This algorithm is one of the major techniques to improve the energy efficiency in WSNs and it provides an effective manner to maximize the lifetime of WSNs. Hierarchical protocols based on clustering hierarchy are proposed to save energy of WSNs in which the nodes with higher remaining energy could be used to collect data and transmit it to a base station. However, most of the previous approaches based on clustering hierarchy have not considered the redundant data collected by the adjacent nodes or nodes overlap each other. In this paper, an enhanced clustering hierarchy (ECH) approach has been proposed to achieve energy efficiency in WSNs by using sleeping-waking mechanism for overlapping and neighboring nodes. Thus, the data redundancy is minimized and then network lifetime is maximized. In contrast of previous hierarchical routing protocols where all nodes are required for collecting and transmitting data, the proposed approach only requires the waking nodes to do these tasks, which are keys of energy consumption in WSNs. We implement (ECH) approach in homogeneous and heterogeneous networks. Results of the simulation show its effectiveness.

Energy efficiency is a major factor in designing wireless sensor networks (WSNs). Clustering design and grid-based scheme are one of the techniques to save energy in WSNs. However, for a mobile sink in WSNs, packet loss rate that occurs due to the sink mobility is also a significant challenge. Here, an enhanced routing-G i protocol for a mobile sink in WSNs has been proposed to not only enhance energy efficiency but also minimise the packet loss rate. Simulation results show that the proposed protocol is more efficient than the previous protocols in terms of the network lifespan, energy efficiency, and packet delivery ratio. Thus, the proposed approach in this work could further be adapted to investigate highly mobility of sink in WSNs.

The communication protocols are an essential part for the data communication of Internet of Things (IoT) applications. However, the selection of a communication protocol is challenging because it depends on the nature of the IoT system and its data transmission system. Copious communications protocols have been developed and employed by researchers based on their requirements in the last decade. Though, none of them is able to support all criteria requirements, like energy efficiency, security, quality of service, etc. Of all types of IoT systems, communication protocols are an ongoing dilemma for the IoT industry; consequently, it is important to analyze the comportments and mechanisms of this latter to determine their best-fit scenarios. Therefore, this paper presents an evaluation of established communication protocols HTTP, MQTT, DDS, XMPP, AMQP and CoAP for IoT applications. Firstly, it presents the broad comparison among these communication protocols to introduce their characteristics comparatively. Subsequently, it performs a detailed and in-depth analysis of the related process of gaining an understanding of their strengths and limitations. Therefore, based on this detailed evaluation, the user can determine their appropriate use for various IoT applications depending on their needs, efficiency, and suitability.

Energy consumption is a constraint in the design architecture of wireless sensor networks (WSNs) and internet of things (IoT). In order to overcome this constraint, many techniques have been proposed to enhance energy efficiency in WSNs. In existing works, several innovative techniques for the physical, the link, and the network layer of OSI model are implemented. Energy consumption in the WSNs is to find the best compromise of energy consumption between the various tasks performed by the objects, the detection, the processing, and the data communication tasks. It is this last task that consumes more energy. As a result, the main objective for the WSNs and the IoT is to minimize the energy consumed during this task. One of the most used solutions is to propose efficient routing techniques in terms of energy consumption. In this chapter, the authors present a review of related works on energy efficiency in WSNs and IoT. The network layer routing protocols are the main concerns in this chapter. The interest is focused on the issue of designing data routing techniques in WSNs and IoT.

WSNs have many applications in modern life. Thus, optimization of the network operation is required to maximize its lifetime. The energy is a major issue in order to increase the lifetime of WSNs. The clustering algorithm is one of the proposed algorithms to enhance the lifetime of WSNs. The operation of the clustering algorithm is divided into cluster heads (CHs) selection and cluster formation. However, most of the previous works have focused on CHs selection, and have not considered the cluster formation process, which is the important issue in clustering algorithm based routing schemes, and it can drastically affect the lifetime of WSNs. In this paper, a Fuzzy Logic based Clustering Algorithm for WSN (CAFL) has been proposed to improve the lifetime of WSNs. This approach uses fuzzy logic for CHs selection and clusters formation processes by using residual energy and closeness to the sink as fuzzy inputs in terms of CH selection, and residual energy of CH and closeness to CHs as fuzzy inputs in terms of clusters formation. Simulation results justify its efficiency.

The data communication task, in wireless sensor networks (WSNs), is a major issue of high energy consumption. A hierarchical design based on a clustering algorithm is one of the approaches to manage the data communication and save energy in WSNs. However, most of the previous approaches based on clustering algorithms have not considered the length of the data communication path, which is a direct relation to energy consumption in WSNs. In this article, a novel scheme of a clustering algorithm has been proposed for reducing the data communication distance in WSNs. Hierarchical routing protocols were implemented for homogeneous and heterogeneous networks. The results show that the proposed scheme is more efficient than other protocols.

The data communication task, in wireless sensor networks (WSNs), is a major issue of high energy consumption. A hierarchical design based on a clustering algorithm is one of the approaches to manage the data communication and save energy in WSNs. However, most of the previous approaches based on clustering algorithms have not considered the length of the data communication path, which is a direct relation to energy consumption in WSNs. In this article, a novel scheme of a clustering algorithm has been proposed for reducing the data communication distance in WSNs. Hierarchical routing protocols were implemented for homogeneous and heterogeneous networks. The results show that the proposed scheme is more efficient than other protocols.

Energy efficiency and throughput are critical factors in the design routing protocols of WSNs. Many routing protocols based on clustering algorithm have been proposed. Current clustering algorithms often use cluster head selection and cluster formation to reduce energy consumption and maximize throughput in WSNs. In this chapter, the authors present a new routing protocol based on smart energy management and throughput maximization for clustered WSNs. The main objective of this protocol is to solve the constraint of closest sensors to the base station which consume relatively more energy in sensed information traffics, and also decrease workload on CHs. This approach divides network field into free area which contains the closest sensors to the base station that communicate directly with, and clustered area which contains the sensors that transmit data to the base station through cluster head. So due to the sensors that communicate directly to the base station, the load on cluster heads is decreased. Thus, the cluster heads consume less energy causing the increase of network lifetime.

This paper presents an approach to integrate Wireless Sensor Networks into Internet. In WSN some sensors have two radio components: Zigbee radio which used on all sensors to send data within the WSN and WiMax radio which activated only on subset of sensors, indicated to as gateways, for sending data to Internet. Objective of our approach is to increase lifetime and throughput of WSN where sensors can join the Internet through gateway, to achieve this goal, we use link cost to select gateway. The link cost is the ratio between distance to Internet and energy level of sensor. The sensor has been selected as gateway which has minimum link cost. To ensure minimum link cost can be performed, we divided WSN into grids where, gateways have been selected in each grid. Results justify its accuracy.

Wireless sensors networks (WSNs) are realised as one of the most promising networking types that bridge the gap between the cyber and the things. Designing of routing protocols for WSNs is a challenging issue since sensors are mostly limited in energy and data processing. In this paper, we present a new routing technique for hierarchical routing protocols to enhance energy efficiency in WSNs, namely Routing-Gi. This technique divides network area into the inner grid and clustered grids. In an inner grid, the nodes transmit directly data to the base station (BS), whereas, in clustered grid, the nodes are organised into micro-grids and thus each node transmits data to the BS through it respective cluster head. in this case, the micro-grids help to avoid unbalanced energy consumption in WSNs. Thus, the workload is evenly distributed on nodes causing the efficient energy of network to enhance. The simulation results prove the effectiveness of our technique.

Les péritonites primitives sont rares chez des patients sans facteurs de risques. Elles simulent les péritonites secondaires. C'est pourquoi leur diagnostic ne peut être que peropératoire. Nous rapportons deux cas de péritonites primitives dans le but de discuter leurs aspects diagnostique et thérapeutiques.