Improving Mobile Sensor Connectivity Time in the IEEE 802.15.4 Networks

In the IEEE 802.15.4 medium access control (MAC) protocol for wireless sensor networks, a sensor node needs to associate with a coordinator before it starts sending or receiving data. The sensor node will mostly choose the nearest coordinator to associate with. However, this method is not suitable for a constantly moving sensor node because it will end up switching coordinators too often due to short connectivity time. The IEEE 802.15.4 has a simplistic and inadequate method of choosing a coordinator in this context. In this paper, we introduce a method to increase the mobile sensor node connectivity time with its co-ordinator in IEEE 802.15.4 beacon-enabled mode. Our method is based on the timestamp of the beacons received from the nearby coordinators and filtering weak beacon signals. By choosing the coordinator which has sent the most recent received beacon with good signal quality, we increase the moving node connectivity time with the coordinator. Our technique results in significant improvement by reducing the number of times the moving node switches coordinators. This increases the throughput and reduces the wasted power in frequent associations

Performance Evaluation of IEEE 802.15.4 for Mobile Sensor Network

The IEEE 802.15.4 standard medium access control (MAC) protocol for low rate wireless personal area networks (LRWPAN) is design mainly for static sensor networks and its capability to support mobile sensor networks has not yet been established. To the best knowledge of authors, this is the first paper that evaluates the suitability of IEEE 802.15.4 MAC in mobile sensor networks environment. We evaluate the performance based on node\u27s speed and beacon order, and observe the effect on energy usage, packet delivery ratio and time required to associate with its coordinator. From the experiment we observe that the moving nodes experienced serious problems in association and synchronization and show results on energy usage, throughput , association and reassociation rate with different speeds of moving node. We also identify some key research problems that need to be addressed for successful implementations of IEEE 802.15..4 in mobile sensor networks environment

MS-ADS: multistage spectrogram image-based anomaly detection system for IoT security.

The innovative computing idea of Internet-of-Things (IoT) architecture has gained tremendous popularity over the last decade, resulting in an exponential increase in the connected devices and the data processed in the IoT networks. Since IoT devices collect a massive amount of sensitive information exchanged over the traditional internet, security has become a prime concern due to the more frequent generation of network anomalies. A network-based anomaly detection system can provide the much-needed efficient security solution to the IoT network by detecting anomalies at the network entry points through constant traffic monitoring. Despite enormous efforts by researchers, these detection systems still suffer from lower detection accuracy in detecting anomalies and generate a high false alarm rate and false-negative rate in classifying network traffic. To this end, this paper proposes an efficient Multistage Spectrogram image-based network Anomaly Detection System (MS-ADS) using a deep convolution neural network that utilizes a short-time Fourier Transform to transform flow features into spectrogram images. The results demonstrate that the proposed method achieves high detection accuracy of 99.98% with a reduction in the false alarm rate to 0.006% in classifying network traffic. Also, the proposed scheme improves predicting the anomaly instances by 0.75% to 4.82%, comparing the benchmark methodologies to exhibit its efficiency for the IoT network. To minimize the computational and training cost for the model re-training phase, the proposed solution demonstrates that only 40500 network flows from the dataset suffice to achieve a detection accuracy of 99.5%

Performance Evaluation of Beacon Enabled IEEE 802.15.4 MAC for Mobile Wireless Sensor Networks under NS-2

Wireless Sensor Network (WSN) has a large number of nodes capable of sensing, communicating and computing. WSNs have limitations due to limited storage, processing and transmission power. The IEEE802.15.4 Medium Access Control (MAC) protocol is used for low-rate wireless personal area network (LR-WPAN). LR-WPAN is basically designed for static wireless sensor networks. However, from literatures, we observed that IEEE802.15.4 is able to support weak mobility in mobile sensor networks [7]. This paper evaluates the IEEE802.15.4 MAC for strong mobility in mobile sensor network environments. We evaluate the performance of IEEE802.15.4 MAC based on both static and mobile coordinators, and taking into account two parameters which are speed and number of beacon orders. We observed the effect on association period, disassociation, and synchronization between the mobile node and the coordinator in strong mobility of mobile nodes. From the experiments, we obtained results on throughput, association and synchronization with different speed and beacon orders. We found that the IEEE802.15.4 cannot maintain association period in strong mobility. The weaknesses of mobile node association attempt and synchronization process degrade the overall performance of a network. We also identify some research problems that need to be addressed for successful implementation of MAC protocol with strong mobility in Mobile Wireless Sensor Networks

Fast Association Process (FAP) of Beacon Enabled for IEEE 802.15.4 in Strong Mobility

In strong mobility the mobile node association with a coordinator (static or mobile) is an important part of IEEE802.15.4 protocol. This research analyzes the mobile node association attempt process flows in detail. This research also proposes an enhanced association procedure names Fast Association Process (FAP) in strong mobility. FAP is introduced with new Association_Data request MAC command that increases the association period and provides fast association process in strong mobility. It reduces the redundant service primitives, avoid collision and decrease association attempt process delay. Comparing FAP with the original IEEE802.15.4 protocol, the number of association service primitives in FAP is 67% less than the original protocol, and the simulation results show that the association attempt time decreases 75%. FAP will get fast association attempt as the number of mobile nodes increased and nodes having strong mobility. It can be widely used in mobile wireless sensor network application

Using Latent Semantic Analysis for Automated Grading Programming Assignments

Traditionally, computer programming assignments are graded manually by educators. As this task is tedious, timeconsuming and prone to bias, the need for automated grading tool is necessary to reduce the educators' burden and avoid inconsistency and favoritism. Recent researches have claimed that Latent Semantic Analysis (LSA) has the ability to represent human cognitive knowledge to assess essays, retrieving information, classification of documents and indexing. In this paper, we adapt LSA technique to grade computer programming assignments and observe how far it can be applied as an alternative approach to traditional grading methods by human. The grades of the assignments are generated from the cosine similarity that shows how close students' assignments to the model answers in the latent semantic vector space. The results show that LSA is not able to detect orders of computer programming and symbols; however, LSA is able to grade assignments faster and consistently, which avoid bias and reduces the time spent by human

Load balancing based on nodes distribution in mobile sensor network

In a large scale mobile sensor network, some coordinators may exhaust energy earlier if they are connected with excessive number of mobile nodes compared to the others. Balancing the load could stable and prolong the network lifetime, maximizes coordinators capabilities and improves net-work performance. In this paper, a mechanism to balance the coordinators' load based on the distribution of mobile sensor nodes in IEEE 802.15.4 protocol is presented. In this scheme, a coordinator is a static cluster head that collects data from the associated mobile sensor nodes. From the simulation results, the load balancing scheme successfully balances the distribution of mobile sensor nodes that attached to each coordinators. This therefore balances the energy consume among the coordinators and indirectly, delay in data reception is reduced when there are large number of mobile nodes in the system

The Influence of k-Constant to Delay Performance of RI-MAC Protocol for Wireless Sensor Networks

In this paper, we introduce a new method to improve the delay performance of RI-MAC protocol, that was originated from the basic concept of IEEE 802.11e EDCA. The delay issue is critical in wireless sensor network (WSN) because it brings up other issues such as energy wastage and limiting its applications. Therefore, the parameter that determine the delay performance, the BeaconTimeout of the RI-MAC protocol will need to be further optimized in order to achieve better delay performance particularly in applications that involved long transmission range. Hence, we introduce the k constant to go with the conventional RI-MAC protocol in order to achieve that. We first evaluate the delay performance of the conventional RI-MAC in long transmission range application focuses on range from 250 to 850 m. The performance evaluation has been carried out through computer simulation of WSN where the relationship and the influence of the proposed k constant in relation to different transmission ranges are also determined. The reason to focus on extended transmission range is to enable wider physical coverage of WSN to use even lesser sensor nodes for better implementation cost effectiveness. The significance of this paper is to highlight that by applying an optimized k constant, the delay performance of the overall network can be maintained at its optimum level. © 2017 Springer Science+Business Media New Yor

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