Enhanced Payload Data Reduction Approach for Cluster Head (CH) Nodes

In this paper, we suggested two approaches to minimizing the CH packet size by considering the accuracy of prediction of sensed data at the base station. The proposed coding schemes based relative difference (CS-RD) and based the factor of precision (CS-FP) instead of the absolute change method that has been used in recent work. The aim is to enhance the accuracy of prediction data at the base station. Therefore, the performance metric was evaluated in term of the accuracy of prediction data at the base station. Simulation results showed that the proposed approaches performed better in term of the accuracy of prediction data at the base station. Specifically, the distortion percentage and average Absolut error in the CS-RD and CS-FP method decreased by 50% and 88% better than the current new aggregation method (ADATDC). However, our proposed CS-FP showed a low reduction ratio for some states

Dynamic multiagent method to avoid duplicated information at intersections in VANETs

Vehicular ad hoc networks (VANETs) allow vehicles to contact one another to provide safety and comfort applications. However, mobility is a great challenge in VANETs. High vehicle speed causes topological changes that result in unstable networks. Therefore, most previous studies focused on using clustering techniques in roads to reduce the effect of vehicle mobility and enhance network stability. Vehicles stop moving at intersections, and their mobility does not impact clustering. However, none of previous studies discussed the impact of vehicle stopping at intersections on base stations (BSs). Vehicles that have stopped moving at intersections continue to send the same information to BSs, which causes duplicated information. Hence, this study proposes a new method named dynamic multiagent (DMA) to filter cluster information and prevent duplicated information from being sent to BSs at intersections. The performance of the proposed method was evaluated through simulations during the use of DMA and without-DMA (W-DMA) methods based on real data collected from 10 intersections in Batu Pahat City, Johor, Malaysia. Overall, the proposed DMA method results in a considerable reduction in duplicated information at intersections, with an average percentage of 81% from the W-DMA method

An efficient IoT-based smart water meter system of smart city environment

Water is a precious need of our lives. Due to the rapid population and urbanization, water usage monitoring is a significant problem facing our society. One solution is to control, analyze, and reduce the water consumption of the houses. The emerging of the Internet of Things (IoT) concept lately in our lives has offered the opportunity to establish water usageefficient smart devices, systems and applications for buildings and cities. Many studies have suggested designing an IoT-based smart meter system; however, the IoT sensor node has limited studies, especially in battery life. Therefore, this study aims to implement and analyze an efficient data collection algorithm for IoT-based smart metering applications in consideration with energy consumption. The system items used are Arduino Uno, Wi-Fi-ESP8266, and water flow sensors. The applied algorithm is an efficient data collection algorithm for water meter (EDCDWM) to reduce the number of packet transmissions. Arduino performed this system's implementation, while the simulation and analysis performed by MATLAB R2019b. The average percentage of energy saved by the applied algorithms of EDCDWM absolute change; and EDCDWM with relative differences in all nodes are around 60% and 93%, respectively

Genetic Algorithm Artificial Neural Network in Near Infrared Spectroscopic Quantification

The implantation of a genetic algorithm (GA) in quantitating components of interest in near infraredspectroscopic analysis could improve the predictive ability of a regression model. Thus, this study investigates thefeasibility of a single layer Artificial Neuron Network (ANN) that trained with Levenberg-Marquardt (SLM) coupledwith GA in predicting the boiling point of diesel fuel and the blood hemoglobin using near infrared spectral data. Theproposed model was compared with a well-known model of Partial Least Squares (PLS) with and without GeneticAlgorithm. Results show that the proposed model achieved the best results with root mean square error of prediction(RMSEP) of 3.6734 and correlation coefficient of 0.9903 for the boiling point, and RMSEP of 0.2349 and correlationcoefficient of 0.9874 among PLS with and without GA, and SLM without GA. Findings suggest that the proposed SLMGA is insusceptible to the number of iterations when the SLM was trained with excessive iteration after the optimaliteration number. This indicates that the proposed model is capable of avoiding overfitting issue that due to excessivetraining iteration

Simulation studies of diffserv policies for the internet traffic

Differentiated Services (Diffserv) is the Internet architecture that uses the queuing management schemes to provision the traffic flows in the Internet backbone system. It discriminates traffic flows to a finite aggregate of classes and provides scalability solution by simplifying the complexity functions at the edge routers. In this paper, we study the end-toend (e2e) Quality of Service (QoS) performance of File Transfer Protocol (FTP) and Constant Bit Rate (CBR) traffics transmitted over a Diffserv network. The Diffserv system applied the Token Bucket, Time Sliding Window Three Color Marker (TSW3CM) and Single Rate Three Color Marker (SRTCM) traffic provisioning policies. The e2e QoS parameters include delay, jitter, loss ratio and throughput are analyzed and compared among the policy types against the increment of traffic connections in the network system. We conclude that the FTP traffic could achieved the best overall delay performance using SRTCM policy and the best jitter performance using TSW3CM. The lowest overall loss ratio and the best throughput for FTP could be achieved using Token Bucket. Besides that, the CBR traffic has achieved the best overall delay performance using TSW3CM policy while the SRTCM policy provides the best jitter, loss ratio and throughput performances. The future works aims to design the combination of QoS aware routing, scheduling, and Diffserv queuing schemes that can adaptively maintain QoS for each type of traffic at optimum level

Developing smart tourism destinations with the Internet of Things

The internet of things (IoT) aims to connect the objects of everyday life by embedding internet-connected devices within them and sharing their information online. Smart technology that exploits IoT data offers new opportunities for the travel and hospitality industry. The IoT enables easy access and interaction with a wide variety of information for contexts such as transportation, attractions, tours, shopping and hotels. IoT big data tourism applications will need to integrate social media, content marketing, and wearable IoT devices. After outlining conceptual understandings of the IoT and its potential for smart cities, this chapter provides practical foundations for destination organizers and stakeholders in this emerging smart tourism paradigm