Latency Analysis of Cloud Infrastructure for Time-Critical IoT Use Cases

The time-critical Internet of Things (IoT) use cases such as driverless cars and robotic surgical arms need high bandwidth and low latency for real-time intelligent data processing and trained machine learning inference. Latency in real-time processing is influenced by many factors such as artificial intelligence (AI) computing algorithm, device processing capabilities, the frameworks, and also the distance from the cloud infrastructure. However, the geographical distance between the data origin and data processing is one of the major factors contributing to the network latency for timecritical IoT use cases. In this paper, we analyzed the latency from a particular client point based on the live data generated by their cloud data centers. The experiments were done through the big three cloud vendors, which are Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP). As a result, a time-critical IoT low latency approach is proposed in this paper

Dilemmas Of The English-Melanau Translators In Sarawak Language Technologies Project

The Sarawak Language Technology (SaL T) project aims to preserve languages through the use of language technologies such as machine translation of English and Bahasa Melayu to indigenous languages in Sarawak. and vice versa. As part of the larger project. a study was conducted to examine the difficulties encountered by the Melanau native speakers who were engaged to translate English texts to Melanau to provide the source data for the development of the English-Melanau translation software. A total of 20 Melanau translators were involved in the translation of a corpus of 1098 English sentences approximating 10,534 words (Including repeated words such as aku, kamu, dia). The translators were educated in English and Bahasa Melayu, and they had jobs ranging from government officers, teachers and students. They did not have degrees in translation but were chosen because of their familiarity with Melanau, English and/or Bahasa Melayu. The Interviews with the Melanau translators indicated that the areas of difficuffies include Melanaa being an oral language without a standardised spelling system, the foreignness of certain concepts to the Melanau language and culture as well as their unfamiliarity with particular expressions and concepts in the source language, English. Insights on improvements in the methodology of obtaining English-Melanau translations were also obtained from the study

Sociolinguistic input in English - Melanau translation

The Sarawak Language Technology (SaL T) project aims to preserve languages through the use of language technologies such as machine translation of English and Bahasa Melayu to indigenous languages in Sarawak. and vice versa. As part of the larger project. a study was conducted to examine the difficulties encountered by the Melanau native speakers who were engaged to translate English texts to Melanau to provide the source data for the development of the English-Melanau translation software. A total of 20 Melanau translators were involved in the translation of a corpus of 1098 English sentences approximating 10,534 words (Including repeated words such as aku, kamu, dia). The translators were educated in English and Bahasa Melayu, and they had jobs ranging from government officers, teachers and students. They did not have degrees in translation but were chosen because of their familiarity with Melanau, English and/or Bahasa Melayu. The Interviews with the Melanau translators indicated that the areas of difficuffies include Melanau being an oral language without a standardised spelling system, the foreignness of certain concepts to the Melanau language and culture as well as their unfamiliarity with particular expressions and concepts in the source language, English. Insights on improvements in the methodology of obtaining English-Melanau translations were also obtained from the study

An Interactive Courseware to Teach Mathematics for Children with Hearing Disabilities

This paper describes an interactive learning CD-based courseware that has been developed to assist school teachers using an effective approach to teach mathematics to special students in particular, hearing impaired students. As such, it overcomes the limitations of current e-learning systems that tend to ignore marginalised groups such as the disabled. A courseware module has been introduced to teach numbers, counting and basic mathematical operations to deaf students aged 7-10 years old. Students are able to learn sign language whereby animations, graphics, audios and videos are integrated to create the signs. Unlike traditional method of teaching; which tends to be teacher-centred and student remain as passive recipients; students are kept actively involved in the learning process and the teacher acts as a guide to facilitate their learning. Interactive activities and multimedia games are among the extra features that are employed allowing teachers to measure their students’ comprehension. The courseware has been experimented for teaching in a local school for the hearing impaired. Teachers provide positive feedbacks after implementation which shows that the courseware could be a potential assistive tool to teach this special group of students

A Survey on 6G Enabled Light Weight Authentication Protocol for UAVs, Security, Open Research Issues and Future Directions

This paper demonstrates a broad exploration of existing authentication and secure communication of unmanned aerial vehicles (UAVs) in a ‘6G network’. We begin with an overview of existing surveys that deal with UAV authentication in 6G and beyond communications, standardization, applications and security. In order to highlight the impact of blockchain and UAV authentication in ‘UAV networks’ in future communication systems, we categorize the groups in this review into two comprehensive groups. The first group, named the Performance Group (PG), comprises the performance-related needs on data rates, latency, reliability and massive connectivity. Meanwhile, the second group, named the Specifications Group (SG), is included in the authentication-related needs on non-reputability, data integrity and audit ability. In the 6G network, with blockchain and UAV authentication, the network decentralization and resource sharing would minimize resource under-utilization thereby facilitating PG targets. Furthermore, through an appropriate selection of blockchain type and consensus algorithms, the SG’s needs of UAV authentication in 6G network applications can also be readily addressed. In this study, the combination of blockchain and UAV authentication in 6G network emergence is reviewed as a detailed review for secure and universal future communication. Finally, we conclude on the critical identification of challenges and future research directions on the subjec

Evaluating The Alternative Assessment Practices in All Current Courses Offered by WC11 Programme

WC11 Network Computing Programme offeredBachelor of Computer Science with Honours (Network Computing) since 2003. The curriculum structure covers fundamental and advance network computing concepts on the use of computers and other devices in a linked network, rather than as unconnected, stand-alone devices. Network computing is a dynamic area of study. Therefore, teaching and learning approaches for network computing has to adapt with the progressive development of the network technologies

Mobile sink for data collection in wireless sensor networks

The work in this thesis investigates the problem of designing a path for a mobile sink, like an Unpiloted Aerial Vehicle (UAV), to traverse a sensing field and collect data from a network of wireless sensor nodes.\ua0 This problem is investigated as an optimization problem with a range of different network architectures, different network constraints and different objective functions.The thesis develops a new multi-level optimization framework which provides excellent solutions across a range of different scenarios.\ua0 This framework starts with a Travelling Salesperson Problem (TSP) tour, generated with a simulated annealing framework.\ua0 It then uses a gradient-descent style optimization framework to test for new waypoint positions which optimize the objective function, which initially is minimum tour time.\ua0 Since tour time consists of the travel time (determined by the TSP tour of waypoints) plus additional stopping time for data collection, an inner optimization loop, based on Linear Programming, is used to find a communications schedule for a specific trial tour which minimizes stopping time, and hence minimizes tour time.\ua0 Unique amongst previously published solutions, this algorithm is able to model radio ranges with data rates that vary with range in arbitrary increments.In particular, three different research questions are posed relating to several different scenarios.\ua0 High quality, minimum tour time data collection paths are generated for known data loads at sensor nodes, using an algorithm variant called TSP-DC.\ua0 In comparison with previously published solutions, it is shown to provide superior tour times.Next, a second variant, called TSP-DA is developed to deal with the situation where data loads are unknown when the tour is first developed, and the algorithm needs to recalculate paths when new nodes are encountered.\ua0 Again results are better than a pre-planned worst case tour, and in most cases are close to the tour time with known loads.The extra cost of re-evaluating the tour is investigated, and if cloud computing support is available, then the recalculation time cost is small compared to the tour time saved.The computational complexity of the algorithms are investigated.\ua0 Theoretical and experimental analyses show that TSP-DC has O(n2) complexity and TSP-DA has O(n3) complexity.Another algorithm variant, TSP-EM, is developed which minimizes energy consumption of the mobile sink, which gives good results, and is able to automatically adapt to different scenarios, such as the difference between ground robot and UAV energy costs.\ua0\ua0The final algorithm variant, TSP-ST, was able to optimize the tour path for network architectures where data could be forwarded from leaf nodes to relay nodes to cluster heads.\ua0 In this case, an added constraint was the amount of energy at each sensor node, which could be different for every node.\ua0\ua0\ua0 Again, the algorithm could generate good paths, across a broader range of scenarios than previously published algorithms.\ua0 For example, with low node energy or low radio range, the sink would visit every node.\ua0 For high node energy and a fully connected network, the network would forward data through a multi-hop tree to a single cluster head closest to the sink base station.This multi-level optimization framework is a significant new contribution, combining three different optimization methods (simulated annealing, gradient descent, linear programming) to provide a uniquely powerful framework for optimized path planning

Poster Abstract: Energy Efficient Mobile Data Collection from Sensor Networks with Range-Dependent Data Rates

This work presents a variation of a data collection problem referred as TSP-Data Collection (TSP-DC). Previously we have demonstrated that a two-stage algorithm using Linear Programming Optimization and Gradient-Descent Optimization (LPO-GDO) is able to solve TSP-DC for minimum tour time. This poster abstract shows that LPO-GDO is also able to solve TSP-DC for an objective function of minimum energy, giving different solutions for different relative energy costs of data transmission and sink movement, and for high or low data loads at sensor nodes

Mobile Data Collection from Sensor Networks with Range-Dependent Data Rates

An algorithm, Travelling Salesperson Problem for Data Collection (TSP-DC), is presented which can plan tours for collected data from sensor nodes using a mobile sink. This is the first work which can deal with multiple different data ranges and data loads for each sensor node. Linear programming is used to schedule data transmissions to different nodes to reduce the overall tour time. Simulation results show that the algorithm reduces tour time by up to 70% compared to previous approaches. A further enhancement, TSP-DA (TSP with Dynamic Adjustment) is able to dynamically recalculate tours when the actual data loads at nodes become known, and in some cases, it can outperform tours with prior knowledge of data loads

S-ADS: Spectrogram Image-based Anomaly Detection System for IoT networks

The Internet of things (IoT) is the smart concept of connecting devices equipped with various sensors, actuators, memory, computational and communicational capabilities using the traditional internet. Since these devices collect a huge amount of sensitive data shared over the internet, the security of an IoT network is of utmost importance due to the more frequent generation of network anomalies. A network-based intrusion detection system (NIDS) is one such tool that can provide much-needed security by shielding the entry points of the IoT network through continuous scanning of network traffic for any suspicious behavior. Recent NIDS experiences low detection accuracy and high false alarm rate (FAR) in detecting network anomalies. To this end, this paper proposes an efficient Spectrogram image-based Anomaly Detection System (S-ADS) using the deep convolutional neural network. The proposed solution is evaluated on the spectrogram images dataset adopted from the Bot-IoT dataset. The experimental results illustrate the effectiveness of the proposed solution by achieving the improvement of �. % − �. �% in the detection accuracy with the reduction in the FAR by �. �% − %