AUTOMATIC SPEED VARIATION SYSTEM IN AUTOMOBILE LINKED WITH DOORS

The sudden accidents often occur when passengers traveling on the footpath of public transport at high speed. The sudden fall from footsteps at that speed may cause serious risk to passengers. In this paper, we present a passengers safety system that has two major features, one is to detect the passengers present in the footpath of the vehicle and the other one is to maintain the speed of the vehicle based on the detection of passengers in the footpath. The present work used IOT system that contains an ultrasonic sensor to detect passengers in a given area. Based on the sensor output of detection of passengers, the door of public transport will automatically open/close and also it will maintain or increase the speed of the bus based on the results. The development of this IOT system also implements an IEEE 802.11 technology to transmit the signal from public transport to mobile apps. The monitoring and controlling mobile application are developed which can receive/transmit the data from/to the controller of the system by using IEEE 802.11. This mobile application shows the status of detection of passengers, door status, and also the real-time speed of the public transport. Keywords – Passenger safety, IoT, Monitoring system, Wireless Communication.

Contextual Bandit Based Rate Adaptation Mechanism for IEEE 802.11 Mobile Wireless LANs

<div>Rate adaptation (RA) is used in IEEE 802.11 WLANs to determine the optimal datarate for a particular channel condition. It becomes especially difficult to determine the optimal datarate for the new High-Throughput WLANs (802.11ac/ax) since the number of available datarates in these standards are very high. Moreover, a mobile environment poses additional challenge in RA as the channel conditions will keep on changing from time to time. In this paper, we propose a Contextual Bandits based Rate Adaptation (ContRA) algorithm for mobile users in IEEE 802.11ac/ax standards. Based on the Received Signal Strength Indicator (RSSI) range that the receiver is currently in, the RA algorithm tries to determine the optimal rate from the rate set suitable for packet transmission in that RSSI range. Performance studies show that the proposed RA algorithm is able to adapt to changing channel conditions and quickly choose a suitable datarate for those channel conditions.</div>

Contextual Bandit Based Rate Adaptation Mechanism for IEEE 802.11 Mobile Wireless LANs

<div>Rate adaptation (RA) is used in IEEE 802.11 WLANs to determine the optimal datarate for a particular channel condition. It becomes especially difficult to determine the optimal datarate for the new High-Throughput WLANs (802.11ac/ax) since the number of available datarates in these standards are very high. Moreover, a mobile environment poses additional challenge in RA as the channel conditions will keep on changing from time to time. In this paper, we propose a Contextual Bandits based Rate Adaptation (ContRA) algorithm for mobile users in IEEE 802.11ac/ax standards. Based on the Received Signal Strength Indicator (RSSI) range that the receiver is currently in, the RA algorithm tries to determine the optimal rate from the rate set suitable for packet transmission in that RSSI range. Performance studies show that the proposed RA algorithm is able to adapt to changing channel conditions and quickly choose a suitable datarate for those channel conditions.</div>

Goodput Modelling and Optimisation of Channel Assignment For Planning IEEE 802.11Wireless Backhaul Networks

<p>IEEE 802.11Wireless backhaul networks (WBNs) provide scalable and cost-effective solutions for interconnecting small-cell networks and backbone networks or Internet. With newer and farther reaching applications being developed in IEEE 802.11 WBNs, such as smart grids and intelligent transportation systems, users expect high goodput and better fairness. However, some performance issues in IEEE 802.11 protocols such as border effect, exposed nodes and hidden nodes are exacerbated as network densification occurs, leading to goodput degradation and severe unfairness such as flow starvation (extreme low goodput). These issues may cause an IEEE 802.11 WBN to form a bottleneck and impact the overall network performance. Therefore, in-depth study is required in order to improve the IEEE 802.11 WBN planning to achieve better goodput and fairness. This research aims to improve IEEE 802.11 WBN planning through goodput modelling and optimising channel assignment. A novel simple goodput distribution model is proposed to predict goodput and fairness in IEEE 802.11 WBNs. Simulation results show that the proposed goodput model accurately predicts goodput with consideration of carrier sensing effect and traffic demands. Based on this goodput model, a new interference model is proposed to more realistically reflect both local and global interference in IEEE 802.11 WBNs. With the proposed interference model, two anti-starvation channel assignments have been developed to prevent flow starvation. Simulation validations show that the new anti-starvation channel assignments effectively prevent flow starvation and improve network fairness in IEEE 802.11 WBNs. This research also optimises channel assignment to achieve desired fairness and goodput. A multi-objective optimisation problem is formulated and a new fitness function is designed to evaluate a channel allocation with accurate prediction of goodput and fairness. Utilising the new fitness function, two multi-objective channel assignments have been developed to achieve both fairness and goodput. Compared with existing channel assignments through simulation, the proposed multi-objective channel assignments provide a set of feasible solutions that meet desired fairness and goodput. This research helps network planners or service providers to improve the IEEE 802.11 WBN planning from predicting network performance to optimising goodput and fairness. The proposed goodput model, interference model, and fitness function are also useful for node placement, and optimising routing and scheduling in IEEE 802.11 WBNs.</p>

Goodput Modelling and Optimisation of Channel Assignment For Planning IEEE 802.11Wireless Backhaul Networks

<p>IEEE 802.11Wireless backhaul networks (WBNs) provide scalable and cost-effective solutions for interconnecting small-cell networks and backbone networks or Internet. With newer and farther reaching applications being developed in IEEE 802.11 WBNs, such as smart grids and intelligent transportation systems, users expect high goodput and better fairness. However, some performance issues in IEEE 802.11 protocols such as border effect, exposed nodes and hidden nodes are exacerbated as network densification occurs, leading to goodput degradation and severe unfairness such as flow starvation (extreme low goodput). These issues may cause an IEEE 802.11 WBN to form a bottleneck and impact the overall network performance. Therefore, in-depth study is required in order to improve the IEEE 802.11 WBN planning to achieve better goodput and fairness. This research aims to improve IEEE 802.11 WBN planning through goodput modelling and optimising channel assignment. A novel simple goodput distribution model is proposed to predict goodput and fairness in IEEE 802.11 WBNs. Simulation results show that the proposed goodput model accurately predicts goodput with consideration of carrier sensing effect and traffic demands. Based on this goodput model, a new interference model is proposed to more realistically reflect both local and global interference in IEEE 802.11 WBNs. With the proposed interference model, two anti-starvation channel assignments have been developed to prevent flow starvation. Simulation validations show that the new anti-starvation channel assignments effectively prevent flow starvation and improve network fairness in IEEE 802.11 WBNs. This research also optimises channel assignment to achieve desired fairness and goodput. A multi-objective optimisation problem is formulated and a new fitness function is designed to evaluate a channel allocation with accurate prediction of goodput and fairness. Utilising the new fitness function, two multi-objective channel assignments have been developed to achieve both fairness and goodput. Compared with existing channel assignments through simulation, the proposed multi-objective channel assignments provide a set of feasible solutions that meet desired fairness and goodput. This research helps network planners or service providers to improve the IEEE 802.11 WBN planning from predicting network performance to optimising goodput and fairness. The proposed goodput model, interference model, and fitness function are also useful for node placement, and optimising routing and scheduling in IEEE 802.11 WBNs.</p>

Bandwidth-Based Wake-Up Radio Solution through IEEE 802.11 Technology

IEEE 802.11 consists of one of the most used wireless access technologies, which can be found in almost all consumer electronics devices available. Recently, Wake-up Radio (WuR) systems have emerged as a solution for energy-efficient communications. WuR mechanisms rely on using a secondary low-power radio interface that is always in the active operation mode and is in charge of switching the primary interface, used for main data exchange, from the power-saving state to the active mode. In this paper, we present a WuR solution based on IEEE 802.11 technology employing transmissions of legacy frames by an IEEE 802.11 standard-compliant transmitter during a Transmission Opportunity (TXOP) period. Unlike other proposals available in the literature, the WuR system presented in this paper exploits the PHY characteristics of modern IEEE 802.11 radios, where different signal bandwidths can be used on a per-packet basis. The proposal is validated through the Matlab software tool, and extensive simulation results are presented in a wide variety of scenario configurations. Moreover, insights are provided on the feasibility of the WuR proposal for its implementation in real hardware. Our approach allows the transmission of complex Wake-up Radio signals (i.e., including address field and other binary data) from legacy Wi-Fi devices (from IEEE 802.11n-2009 on), avoiding hardware or even firmware modifications intended to alter standard MAC/PHY behavior, and achieving a bit rate of up to 33 kbps.

Experimental Study on the Performance of Rate Adaptation Algorithm in IEEE 802.11g Networks

<p>IEEE 802.11 technology provides a low-cost wireless networking solution. In the last few years, we have seen that the demand for high-bandwidth wireless local area networks increases rapidly, due to the proliferation of mobile devices such as laptops, smart phones and tablet PCs. This has driven the widespread deployment of IEEE 802.11 wireless networks to provide Internet access. However, wireless networks present their own unique problems. Wireless channel is extremely variable and can be affected by a number of different factors, such as collisions, multipath fading and signal attenuation. As such, rate adaptation algorithm is a key component of IEEE 802.11 standard which is used to vary the transmission data rate to match the wireless channel conditions, in order to achieve the best possible performance. Rate adaptation algorithm studies and evaluations are always hot research topics. However, despite its popularity, little work has been done on evaluating the performance of rate adaptation algorithms by comparing the throughput of the algorithm with the throughput of the fixed rates. This thesis presents an experimental study that compares the performance ofMikroTik rate adaptation algorithm andMinstrel rate adaptation algorithm against fixed rates in an IEEE 802.11g network. MikroTik and Minstrel rate adaptation algorithm are most commonly used algorithm around the world. All experiments are conducted in a real world environment in this thesis. In a real world environment, wireless channel conditions are not tightly being controlled, and it is extremely vulnerable to interference of surrounding environment. The dynamic changes of wireless channel conditions have a considerable effect on the performance of rate adaptation algorithms. The main challenge of evaluating a rate adaptation algorithm in a real world environment is getting different experiment behaviours from the same experiment. Experiment results may indicate many different behaviours which due to the leak of wireless environment controlling. Having a final conclusion from those experiment results can be a challenge task. In order to perform a comprehensive rate adaptation algorithm evaluation. All experiments run 20 times for 60 seconds. The average result and stand deviation is calculated. We also design and implement an automation experiment controlling program to help us maintain that each run of experiment is following exactly the same procedures. In MikroTik rate adaptation algorithm evaluation, the results show in many cases that fixed rate outperforms rate adaptation. Our findings raise questions regarding the suitability of the adopted rate adaptation algorithm in typical indoor environments. Furthermore, our study indicates that it is not wise to simply ignore fixed rate. A fine selection of a fixed rate could be made to achieve desired performance. The result ofMinstrel rate adaptation evaluation show that whilst Minstrel performs reasonably well in static wireless channel conditions, in some cases the algorithm has difficulty selecting the optimal data rate in the presence of dynamic channel conditions. In addition, Minstrel performs well when the channel condition improves frombad quality to good quality. However, Minstrel has trouble selecting the optimal rate when the channel condition deteriorates from good quality to bad quality. By comparing the experimental results between the performance of rate adaptation algorithms and the performance of fixed data rate against different factors, the experiment results directly pointed out the weakness of these two rate adaptation algorithms. Our findings from both experiments provide useful information on the design of rate adaptation algorithms.</p>

Experimental Study on the Performance of Rate Adaptation Algorithm in IEEE 802.11g Networks

<p>IEEE 802.11 technology provides a low-cost wireless networking solution. In the last few years, we have seen that the demand for high-bandwidth wireless local area networks increases rapidly, due to the proliferation of mobile devices such as laptops, smart phones and tablet PCs. This has driven the widespread deployment of IEEE 802.11 wireless networks to provide Internet access. However, wireless networks present their own unique problems. Wireless channel is extremely variable and can be affected by a number of different factors, such as collisions, multipath fading and signal attenuation. As such, rate adaptation algorithm is a key component of IEEE 802.11 standard which is used to vary the transmission data rate to match the wireless channel conditions, in order to achieve the best possible performance. Rate adaptation algorithm studies and evaluations are always hot research topics. However, despite its popularity, little work has been done on evaluating the performance of rate adaptation algorithms by comparing the throughput of the algorithm with the throughput of the fixed rates. This thesis presents an experimental study that compares the performance ofMikroTik rate adaptation algorithm andMinstrel rate adaptation algorithm against fixed rates in an IEEE 802.11g network. MikroTik and Minstrel rate adaptation algorithm are most commonly used algorithm around the world. All experiments are conducted in a real world environment in this thesis. In a real world environment, wireless channel conditions are not tightly being controlled, and it is extremely vulnerable to interference of surrounding environment. The dynamic changes of wireless channel conditions have a considerable effect on the performance of rate adaptation algorithms. The main challenge of evaluating a rate adaptation algorithm in a real world environment is getting different experiment behaviours from the same experiment. Experiment results may indicate many different behaviours which due to the leak of wireless environment controlling. Having a final conclusion from those experiment results can be a challenge task. In order to perform a comprehensive rate adaptation algorithm evaluation. All experiments run 20 times for 60 seconds. The average result and stand deviation is calculated. We also design and implement an automation experiment controlling program to help us maintain that each run of experiment is following exactly the same procedures. In MikroTik rate adaptation algorithm evaluation, the results show in many cases that fixed rate outperforms rate adaptation. Our findings raise questions regarding the suitability of the adopted rate adaptation algorithm in typical indoor environments. Furthermore, our study indicates that it is not wise to simply ignore fixed rate. A fine selection of a fixed rate could be made to achieve desired performance. The result ofMinstrel rate adaptation evaluation show that whilst Minstrel performs reasonably well in static wireless channel conditions, in some cases the algorithm has difficulty selecting the optimal data rate in the presence of dynamic channel conditions. In addition, Minstrel performs well when the channel condition improves frombad quality to good quality. However, Minstrel has trouble selecting the optimal rate when the channel condition deteriorates from good quality to bad quality. By comparing the experimental results between the performance of rate adaptation algorithms and the performance of fixed data rate against different factors, the experiment results directly pointed out the weakness of these two rate adaptation algorithms. Our findings from both experiments provide useful information on the design of rate adaptation algorithms.</p>