Ong Bi Lynn

Internet of Things (IoT): Taxonomy of security attacks

The Internet of Things (IoT) comprises a complex network of smart devices, which frequently exchange data through the Internet. Given the significant growth of IoT as a new technological paradigm, which may involve safety-critical operations and sensitive data to be put online, its security aspect is vital. This paper studies the network security matters in the smart home, health care and transportation domains. It is possible that the interruption might occur in IoT devices during operation causing them to be in the shutdown mode. Taxonomy of security attacks within IoT networks is constructed to assist IoT developers for better awareness of the risk of security flaws so that better protections shall be incorporated.

Energy consumption optimization with Ichi Taguchi method for Wireless Sensor Networks

Wireless Sensor Networks (WSN) consists of sensor nodes for monitoring and reporting sensible changes on a field to a specific server. One of the applications of WSN is large area monitoring, where sensor nodes are placed in far fields with limited power sources. Due to the adhered reason, the energy consumption of sensor nodes is considered as one of the major challenge in WSN. Many factor in WSN contributes to energy consumption such as Medium Access Control protocol (MAC), the network topology, and routing protocol. With the variety of factors that affects the energy consumption in WSN; the challenge of optimizing WSN networks toward a low energy consumption is becoming a hard problem. In the literature many efforts are paid for designing, implementing, and improving protocols in terms of power consumption. However, few efforts are paid for optimizing the existing protocols and other network parameters toward a green technology. This paper focuses in WSN infrastructure and protocols optimization by introducing the Ichi Taguchi (Taguchi) optimization method. Taguchi method is used to predict the best design parameters to achieve optimal performance parameters. Moreover, Taguchi method is used to optimize the energy consumed by sensor nodes against network protocols and network topology design parameters. A simulation experiments are curried out on the discrete event simulator OMNET++ for the purposes of this research paper. The obtained results show the impact of the network protocols toward the energy consumption. Furthermore, a proposed network topology and protocols set is introduced, and compared against the existing once.

Enhancement and analysis of TFRC performance for real-time data application: A survey

In this project, we propose an enhancement and analysis of transport control protocol friendly rate control (TFRC) for real-time data application (audio/video). Traditionally, real-time data transmission has been accomplished over the user datagram protocol (UDP). The challenging issues of using transport control protocol (TCP) are restrictive bandwidth and lagging. Additionally, it is widely known that TCP is ill-suited to real-time multimedia streaming application. Having known these issues, this project aims to study the possibilities for analysis and improvement of real-time data application using TFRC which is designed for long-lived streams. As known, there are many advantages of TFRC, which are congestion control and guaranteeing the required throughput. Therefore, this project explores and proposes the advantages of TFRC in transmitting and receiving real-time data which currently uses UDP. It is proposed that the investigation of TFRC in real-time data is conducted using simulation technique. During the simulation, the developed model is representing the real-time application for analyzing the performance of modified TFRC. The simulation study of this project is to analyze and evaluate some of restraint issues for real-time data application to use TFRC. As a solution, a few suggestions are discussed to overcome stated problem and make comparison and evaluation, which are aimed to get results about better performance between enhanced TFRC and UDP in terms of streaming real-time data.

The effects of CPU load & idle state on embedded processor energy usage

Device power consumption is a serious design consideration especially for embedded systems. By reducing the power consumption of a particular system, we could effectively prolong the runtime of the system, allowing for longer operational condition of a particular system. Previous studies have suggested that the power characteristics of a modern embedded processor have since been improved with manufacturers implementation of better energy-focused designs. Implementation of hardware optimization such as better clock and power gating have been shown to produce better energy usage during on-load and off-load processing. In this paper we benchmarked the energy use of a modern embedded processor and study the effects of idling time to the processor and system energy usage. We have found that the processor energy use is significantly reduced in the instant that the processor goes idle during the execution process. The idling time during a processing timeslice allows the processor to use significantly less energy without explicitly depending on a frequency scaling algorithm to reduce energy consumption. This power saving feature directly implemented inside the processor hardware have the possibility to render software based frequency scaling algorithm and DVFS method to be less effective in reducing energy usage.

Performance Investigation of Joint User-Proportional Fair Scheduling Algorithm in LTE-Advanced System with Carrier Aggregation

Carrier Aggregation (CA) is a promising technology that proposed by 3GPP in the latest LTEAdvanced (LTE-A) criterions in order to satisfy the future IMT-Advanced mobile networks demands. While CA allows aggregation of component carriers (CCs) dispersed within and transversely in diverse bands (intra/inter-band), CA is expected to offer a powerful boost to the user throughput in LTEAdvanced system. In addition, it will permit the achievement of the target peak data rates in excess of 1 Gbps in the downlink and 500 Mbps in the uplink in which the users has the right to use up to 100 MHz total of bandwidth. The mixture of LTE-A and LTE users within a multi-carrier LTE-A network may perhaps exist simultaneously. Each of them has various CA capabilities. The former has the ability to assign on multiple CCs, whereas the later can allocate on one CC. Moreover, they demand diverse QoS requirements which present new challenges to optimize the performance of LTE-Advanced system. Therefore, the choice of scheduling strategies plays a key role in guaranteeing desirable end to end system performance. The study of this paper will be beneficial for understanding the radio resource management (RRM) function with carrier aggregation feature. In addition, this article presents the Joint UserProportional Fair scheduling scheme (JUS-PF) for resource allocation and its impacts on two deployment scenarios which are LTE-A users and mixture (LTE/LTE-A) users’ scenario in terms of average user throughput, cell edge user throughput, and fairness.

Performances of Machine Learning Algorithms for Binary Classification of Network Anomaly Detection System

The rapid growth of technologies might endanger them to various network attacks due to the nature of data which are frequently exchange their data through Internet and large-scale data that need to be handle. Moreover, network anomaly detection using machine learning faced difficulty when dealing the involvement of dataset where the number of labelled network dataset is very few in public and this caused many researchers keep used the most commonly network dataset (KDDCup99) which is not relevant to employ the machine learning (ML) algorithms for a classification. Several issues regarding these available labelled network datasets are discussed in this paper. The aim of this paper to build a network anomaly detection system using machine learning algorithms that are efficient, effective and fast processing. The finding showed that AODE algorithm is performed well in term of accuracy and processing time for binary classification towards UNSW-NB15 dataset.

QoS Based Independent Carrier Scheduling Scheme for Heterogeneous Services in 5G LTE-Advanced Networks

Efficient user-level QoS provisioning for heterogeneous services is of vital importance in future 5G Long-Term Evolution-Advanced (LTE-A) with Carrier Aggregation (CA) mobile system. The CA is very vital technique which invented by 3GPP for creating the huge virtual carrier bandwidths to support the 5G LTE-A network with unprecedented speed of data transmission and minimal latency. To the best of our knowledge, in order to support and fulfill the user level QoS obligations for diversified services “Real-Time (RT) and Non-Real-Time (NRT)”, one of the main challenges in the presence of CA is to offer robust and suitable resource scheduling scheme. In this paper, the authors propose an efficient scheduling scheme, termed as “QoS based Independent Carrier (QoS-IC)” by designing Round-Robin with Service (RR-S) method for ensuring the load balancing based on the user’s service in 5G LTE-A system. In addition, a user-level Quality of Service aware packet scheduling for OFDMA resource blocks suitable to multi-services system is proposed by introducing the service utility factor. The design objective is to guarantee the user quality of service (QoS) and equitable allocation of radio resources among users. Extensive simulation outcomes demonstrate that our scheduling algorithm offers significantly better QoS performance in terms of packet drop rate (PDR), variance of packet drop rate, and the average packet delay for RT traffic as well as satisfying the minimum transmission rate demand for NRT traffic.

Power Consumption Optimization Based on B-MAC Protocol for Multi-Scenario WSN by Taguchi Method

Wireless sensor network (WSN) is exploited in diverse applications. Further, the variety of WSN applications it let the door open for researchers to deal with WSN challenges. However, the critical issue faced WSN is the prolong lifetime of sensor nodes. Additionally, the topology of a wireless sensor network often changes frequently due to node failure, damage, addition, movement, and energy depletion which effect change in the network topology lead to a multi-scenario network. This paper aimed to study the effect of multi-scenario on the MAC protocol WSN for energy efficiency. The proposed method is based on Taguchi method. Further, Berkeley-MAC (B-MAC) protocol parameters are optimized for different WSN scenarios. Moreover, simulation experiments are carried out by OMNET++ to prove the work in this paper. The obtained results show that Taguchi B-MAC optimizing reduces the power consumption of WSN for a multi-scenario network.

Optimization of B-MAC Protocol for Multi-scenario WSN by Differential Evolution Algorithm

The Energy efficiency is a critical issue which confronts the wireless sensor network (WSN). A lot of research work on reducing power consumption at WSN MAC protocols is present till date. Generally, WSN sensor nodes might go through different scenario requirements such as mobility and traffic requirement. The adhered problem and energy consumption requirements in WSN highlights the need for robust MAC protocol. This paper aims to reduce the power consumption of the B-MAC protocol by utilizing multi-objective optimization method named; the Differential Evolution (DE) algorithm for multi-scenarios WSN. Further, simulation experiments are carried out on the discrete event simulator OMNET++ for the purposes of this paper. Moreover, the experimental analysis shows the improvement the energy consumption of (DE-BMAC) for two scenarios without an effect of performance network.