QoS Routing of VoIP using a Modified Widest-Shortest Routing Algorithm

Implementation of current real time services (of which one of the more important is Voice over IP) on the current Internet face many obstacles, among them the issue of routing. Quality of service (QoS) routing, attempts to provide real time services with the required guarantees to achieve acceptable performance. In this paper we study VoIP routing using the Quality of Service (QSR) network simulator utilizing the Widest-Shortest routing algorithm to provide QoS using different metrics. We show that this algorithm using a modified cost metric based on the hop-normalized is able to route real time traffic away from congested links thus providing acceptable jitter, end-to-end delay and throughput to satisfy real time services requirements

A machine learning-based early forest fire detection system utilizing vision and sensors’ fusion technologies

The paper aims at utilizing machine learning (ML) towards designing an early warning forest fire detection system. With the aid of the Internet of Things (IoT) and smart edge computing, an embedded system that utilizes sensors’ fusion technology, machine vision and ML to early detect forest fire has been proposed. Different from most of the proposed fire detection systems in the literature, which either utilize vision or sensors’-based approaches to detect the fire, the proposed system utilizes both approaches jointly, which in turn will make it more accurate for fire detection. Furthermore, this paper focuses on implementing the proposed system utilizing a smart edge node and discusses the incurred technical challenges and how they have been solved.This work has been in part supported by King Abdullah II Fund for development. Grant No.2022/6 and Jordan Design and Development Bureau(JODDB).info:eu-repo/semantics/publishedVersio

Map coverage of LoRaWAN signal’s employing GPS from mobile devices

Forests are remote areas with uneven terrain, so it is costly to map the range of signals that enable the implementation of systems based on wireless and long-distance communication. Even so, the interest in Internet of Things (IoT) functionalities for forest monitoring systems has increasingly attracted the attention of several researchers. This work demonstrates the development of a platform that uses the GPS technology of mobile devices to map the signals of a LoRaWAN Gateway. Therefore, the proposed system is based on concatenating two messages to optimize the LoRaWAN transmission using the Global Position System (GPS) data from a mobile device. With the proposed approach, it is possible to guarantee the data transmission when finding the ideal places to fix nodes regarding the coverage of LoRaWAN because the Gateway bandwidth will not be fulfilled. The tests indicate that different changes in the relief and large bodies drastically affect the signal provided by the Gateway. This work demonstrates that mapping the Gateway’s signal is essential to attach modules in the forest, agriculture zones, or even smart cities.This work has been supported by Fundação La Caixa and FCT - Fundação para a Ciência e Tecnologia within the Project Scope: UIDB/5757/2020. Thadeu Brito is supported by FCT PhD Grant Reference SFRH/BD/08598/2020. Beatriz Flamia Azevedo is supported by FCT PhD Grant Reference SFRH/BD/07427/2021.info:eu-repo/semantics/publishedVersio

Work in Progress – Establishing a Master Program in Cyber Physical Systems: Basic Findings and Future Perspectives

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper reports on the basic findings and future perspectives of a capacity building project funded by the European Union. The International Master of Science on Cyber Physical Systems (MS@CPS) is a collaborative project that aims to establish a master program in cyber physical systems (CPS). A consortium composed of nine partners proposed the project. Three partners are European and from Germany, UK and Sweden; while the other six partners are from the South Mediterranean region and include: Palestine, Jordan and Tunisia. The consortium is led by the University of Siegen in Germany who also manages the implementation of the work packages. CPS is an emerging engineering subject with significant economic and societal implications, which motivated the consortium to propose the establishment of a master program to offer educational and training opportunities at graduate level in the fields of CPS. In this paper, CPS as a field of study is introduced with an emphasis on its importance, especially with regard to meeting local needs. A brief description of the project is presented in conjunction with the methodology for developing the courses and their learning outcomes

Microcontroller Unit-Based Wireless Sensor Network Nodes: A Review

In this paper, a detailed review of microcontroller unit (MCU)-based wireless sensor node platforms from recently published research articles is presented. Despite numerous research efforts in the fast-growing field of wireless sensor devices, energy consumption remains a challenge that limits the lifetime of wireless sensor networks (WSNs). The Internet-of-Things (IoT) technology utilizes WSNs for providing an efficient sensing and communication infrastructure. Thus, a comparison of the existing wireless sensor nodes is crucial. Of particular interest are the advances in the recent MCU-based wireless sensor node platforms, which have become diverse and fairly advanced in relation to the currently available commercial WSN platforms. The recent wireless sensor nodes are compared with commercially available motes. The commercially available motes are selected based on a number of criteria including popularity, published results, interesting characteristics and features. Of particular interest is to understand the trajectory of development of these devices and the technologies so as to inform the research and application directions. The comparison is mainly based on processing and memory specifications, communication capabilities, power supply and consumption, sensor support, potential applications, node programming and hardware security. This paper attempts to provide a clear picture of the progress being made towards the design of autonomous wireless sensor nodes to avoid redundancy in research by industry and academia. This paper is expected to assist developers of wireless sensor nodes to produce improved designs that outperform the existing motes. Besides, this paper will guide researchers and potential users to easily make the best choice of a mote that best suits their specific application scenarios. A discussion on the wireless sensor node platforms is provided, and challenges and future research directions are also outlined

Optimal Cluster Head Positioning Algorithm for Wireless Sensor Networks

Wireless sensor networks (WSNs) are increasingly gaining popularity, especially with the advent of many artificial intelligence (AI) driven applications and expert systems. Such applications require specific relevant sensors’ data to be stored, processed, analyzed, and input to the expert systems. Obviously, sensor nodes (SNs) have limited energy and computation capabilities and are normally deployed remotely over an area of interest (AoI). Therefore, proposing efficient protocols for sensing and sending data is paramount to WSNs operation. Nodes’ clustering is a widely used technique in WSNs, where the sensor nodes are grouped into clusters. Each cluster has a cluster head (CH) that is used to gather captured data of sensor nodes and forward it to a remote sink node for further processing and decision-making. In this paper, an optimization algorithm for adjusting the CH location with respect to the nodes within the cluster is proposed. This algorithm aims at finding the optimal CH location that minimizes the total sum of the nodes’ path-loss incurred within the intra-cluster communication links between the sensor nodes and the CH. Once the optimal CH is identified, the CH moves to the optimal location. This suggestion of CH re-positioning is frequently repeated for new geometric position. Excitingly, the algorithm is extended to consider the inter-cluster communication between CH nodes belonging to different clusters and distributed over a spiral trajectory. These CH nodes form a multi-hop communication link that convey the captured data of the clusters’ nodes to the sink destination node. The performance of the proposed CH positioning algorithm for the single and multi-clusters has been evaluated and compared with other related studies. The results showed the effectiveness of the proposed CH positioning algorithm

SCSAP: Spiral Clustering Based on Selective Activation Protocol for industrial tailored WSNs

Wireless Sensor Networks (WSNs) are generally deployed with low-cost devices that have low power consumption and small-size sensor nodes. They can be used in several monitoring and control applications such as; health, agriculture, and environment. With the advent of Industry 4.0 and Artificial Intelligence (AI), WSNs attracted many industrial applications and specific implementation scenarios. In general, the sensor nodes compromising of WSNs consume vast energy during tracking and monitoring. This poses a challenge especially since most of WSNs are battery-operated and have very limited energy sources. Therefore, it is important to optimize power consumption and prolong the lifetime of WSNs. Many protocols have been proposed with emphasis on data forwarding and routing. These protocols, however, have not been designed to address interference and transmissions issues, such as communication link instability and packet drops. In addition, a quiet substantial amount of energy would be consumed during transmission, which leads to a degradation in network performance. In this research, an effective solution is proposed based on Spiral Clustering Based on Selective Activation Protocol (SCSAP). The objective is to enhance energy consumption and improve network performance, which makes it a good candidate for several Industrial tailored WSNs. In this solution, the network nodes are classified into two types; super and normal. Super nodes have a significant power source and are utilized to construct clusters and act as Cluster Heads (CHs). They have pre-defined locations with an optimized number of nodes selected for the best coverage that is determined in the Stable Election Protocol (SEP). As a result, the power consumption is reduced in the dynamic formatting of clusters. Normal nodes, on the other hand, are static. They have limited power and are connected to the super nodes. Normal nodes operate in two modes; active and sleep. In the active mode, they send data to the CHs and the Time Division Multiple Access (TDMA) is used to guarantee that the transmitted data are correctly received by the other nodes and that the power consumption of re-transmission is largely reduced. The simulation results of SCSAP have shown a 40% enhancement of network lifetime over the Threshold-sensitive Stable Election Protocol (TSEP). They have also shown that SCASP’s remaining power has descended slower than the Low-energy Adaptive Clustering Hierarchy (LEACH) protocol

Microcontroller Unit-Based Wireless Sensor Network Nodes: A Review

In this paper, a detailed review of microcontroller unit (MCU)-based wireless sensor node platforms from recently published research articles is presented. Despite numerous research efforts in the fast-growing field of wireless sensor devices, energy consumption remains a challenge that limits the lifetime of wireless sensor networks (WSNs). The Internet-of-Things (IoT) technology utilizes WSNs for providing an efficient sensing and communication infrastructure. Thus, a comparison of the existing wireless sensor nodes is crucial. Of particular interest are the advances in the recent MCU-based wireless sensor node platforms, which have become diverse and fairly advanced in relation to the currently available commercial WSN platforms. The recent wireless sensor nodes are compared with commercially available motes. The commercially available motes are selected based on a number of criteria including popularity, published results, interesting characteristics and features. Of particular interest is to understand the trajectory of development of these devices and the technologies so as to inform the research and application directions. The comparison is mainly based on processing and memory specifications, communication capabilities, power supply and consumption, sensor support, potential applications, node programming and hardware security. This paper attempts to provide a clear picture of the progress being made towards the design of autonomous wireless sensor nodes to avoid redundancy in research by industry and academia. This paper is expected to assist developers of wireless sensor nodes to produce improved designs that outperform the existing motes. Besides, this paper will guide researchers and potential users to easily make the best choice of a mote that best suits their specific application scenarios. A discussion on the wireless sensor node platforms is provided, and challenges and future research directions are also outlined