Clustered Coordinator SABTS (CC-SABTS) for Beacon Transmission in IEEE802.15.4 LR-WPAN

IEEE802.15.4 standard for Wireless Sensor Network (WSN) provides low-power transmission in the low-rate wireless personal area network (WPAN). It has three types of topology: star, peer-to-peer and cluster tree. Star topology has limit to expand network. Peer-to-peer topology has a complex multihop routing during network expansion due to the large number of full-function devices. A full-function device can act as coordinator and personal area network coordinator (PAN-C). Cluster tree topology is preferable because it can expand networks using less number of full-function devices and thus reduces complexity in routing messages. A cluster tree topology consists of a wireless PAN-C, several cluster coordinators and a number of end devices. The coordinators periodically transmit beacon frames to one another to allow synchronization and communication. However, collision will happen if the coordinators transmit beacon frames at the same time and will degrade the network performance. Different mechanisms have been introduced to solve the collision problem and one of the mechanisms is superframe adjustment and beacon transmission scheme (SABTS). SABTS calculates the precise time for beacon transmission by assigning an accurate value of beacon order and superframe order for PAN-C, cluster coordinators and end devices. As the number of cluster coordinator increases, SABTS method reiterates the calculation for beacon transmission time numerously. Hence, in order to decrease the iteration, this paper introduces clustered coordinator SABTS (CC-SABTS) by clustering coordinator nodes that are separated by two length radius. The performance of CC-SABTS is simulated and evaluated using NS2 simulation software. Result shows that CC-SABTS provides better average throughput, packet delivery ratio and end-to-end delay compared to the conventional SABTS

Design and analysis of remote monitoring and testing of telephone for highways

This thesis presents a design of a circuitry that enables highway telephones to be tested and monitored from remote offices. Research survey on remote monitoring and testing of telephone system for highways and its roles in providing road users in time of emergencies are also discussed

Variable Global Optimization min-sum (VGOMS) algorithm of decodeand-forward protocol for the relay node in the cooperative channel

The excessive delay due to the complexity of the decoding process at the relay node results in additional delays at the destination which is a significant issue in cooperative communication channels. A low complexity min-sum (MS) based algorithm called the Variable Global Optimization min-sum (VGOMS) algorithm has been developed to minimise the error corrective performance. The proposed VGOMS algorithm apply the optimization scaling factor at the bit node processing of the variable node operation which have significantly less complexity as compared with the check node operation or both variable node and check node operation. In this study, a straightforward Particle Swarm Optimization approach was used to determine the optimal scaling factor to obtain optimized error corrective performance of the algorithm. The proposed system model uses the channel combining large-scale and small-scale effects which used extensively in cooperative communications. The performance of the VGOMS algorithm performance was compared with four existing decoding algorithms (MS, OMS, NMS, SP) and was found better than the original min-sum (MS) in term of bit error rate (BER) performance and the first algorithm reach optimal BER in error floor region from 3 others existing decoding algorithm (MS, OMS, NMS) after Sum-Product (SP) algorithm. The VGOMS algorithm was therefore shown to have a significantly better compromise between the implementation of good error performance and low computational complexity

Utility-based Scheduling Frameworks for Efficient Quality-ofService Differentiation in a Mixture of Real-time and Nonreal-time Traffics

This paper proposes a utility-based scheduling framework for efficient differentiation of users’ Quality-of-Service (QoS) in a broadband wireless access system involving heterogeneous mixed traffic flows. The utility-based scheduling framework, called Maximum QoS Satisfaction (MQS), is based on three novel Radio Resource Allocation (RRA) techniques; delay-based scheduling policy for Real-Time (RT), minimumrate-based scheduling policy for Non-Real-Time (NRT) and a throughputbased scheduling policy for Best-Effort (BE) services. Simulation study shows that MQS achieves superior performances in terms of average system throughput and user satisfaction both in single and heterogeneous mixed traffic scenarios, when compared to some existing ones

Oil palm tree detection and counting for precision farming using deep learning CNN

Oil palm tree is a very important crop in Malaysia and other tropical areas. The number of oil palm trees in a plantation area is crucial as it could help to estimate the potential yield of palm oil, monitoring the growing situation of palm trees after plantation such as the age and the survival rate and also the amount of fertilizer and pesticides needed. In this paper, a deep learning-based oil palm tree detection and counting method is proposed and designed into a functioning app. Images of oil palm plantation are collected by using drones then they are pre-processed. The pre-processed images are used to train and optimize the convolutional neural network (CNN). After the CNN model is trained, it is used to predict the label for all the samples in an image dataset collected through the sliding window technique. Its performance is tested. The performance of the classifier is tested on three different tree conditions, from small number of properly separated trees to big number of crowded trees. Based on the result, accuracy ranging from 83.5% to 100% is obtained. Finally, the method is built into an application for a better user experience