A Calculation of WLAN Dwell Time Model for Wireless Network Selection

In an integrated wireless and mobile network, selecting a desired a network is an important issue. Parameters such as system load, service characteristics and user mobility are the main criteria in network selection strategy. In this paper, we devise a mobility estimation method for a Mobile Node (MN) during initial network selection and Vertical Handover (VHO). The method relies on a new prediction dwelling time and the Call Holding Time (CHT) of a user. By comparing the predicted dwelling time with the CHT, a MN is able to make decision which network is suitable to be used in order to minimize the VHO. The proposed theoretical model has been validated by the MonteCarlo experiments. The simulation results demonstrate the validity of the proposed method

A calculation of WLAN dwell time model for wireless network selection

In an integrated wireless and mobile network, selecting a desired a network is an important issue. Parameters such as system load, service characteristics and user mobility are the main criteria in network selection strategy. In this paper, we devise a mobility estimation method for a Mobile Node (MN) during initial network selection and Vertical Handover (VHO). The method relies on a new prediction dwelling time and the Call Holding Time (CHT) of a user. By comparing the predicted dwelling time with the CHT, a MN is able to make decision which network is suitable to be used in order to minimize the VHO. The proposed theoretical model has been validated by the MonteCarlo experiments. The simulation results demonstrate the validity of the proposed method

Improving vehicular ad hoc networks (VANET) communication performance by using time gap following distance (TGFD) model

Today, there is a growing research study of IEEE 802.11p as one of option to help the drivers to travel more safely.Message dissemination protocols are primordial for safety vehicular applications. Periodic safety message (PSM) and Warning safety message (WSM) are two types of safety messages which may be exchanged between vehicles. In this paper we investigate the feasibility of deploying safety applications based on periodic message dissemination through simulation study with safety requirements as our priority concern.Vehicles are supposed to issue these messages constantly to inform their neighboring vehicles about their current status and use received messages for preventing possible unsafe situations on time. As reliability is the main concern in periodic message dissemination, a new metric called TGFD (Time Gap Following Distance) is defined which gives us more accurate benchmark for evaluating QoS in safety applications specifically.Thus, in order to improve the performance, the effective transmission TGFD studied

Security attacks taxonomy on bring your own devices (BYOD) model

Mobile devices, specifically smartphones, have become ubiquitous. For this reason, businesses are starting to develop “Bring Your Own Device” policies to allow their employees to use their owned devices in the workplace. BYOD offers many potential advantages: enhanced productivity, increased revenues, reduced mobile costs and IT efficiencies. However, due to emerging attacks and limitations on device resources, it is difficult to trust these devices with access to critical proprietary information. Therefore, in this paper, the potential attacks of BYOD and taxonomy of BYOD attacks are presented. Advanced persistent threat (APT) and malware attack are discussed in depth in this paper. Next, the proposed solution to mitigate the attacks of BYOD is discussed. Lastly, the evaluations of the proposed solutions based on the X. 800 security architecture are presented

Driver Drowsiness Detection and Monitoring System (DDDMS)

—The purpose of this paper is to develop a driver drowsiness and monitoring system that could act as an assistant to the driver during the driving process. The system is aimed at reducing fatal crashes caused by driver’s drowsiness and distraction. For drowsiness, the system operates by analysing eye blinks and yawn frequency of the driver while for distraction, the system works based on the head pose estimation and eye tracking. The alarm will be triggered if any of these conditions occur. Main part of the implementation of this system will be using python with computer vision, while Raspberry Pi, which is uniquely designed, for the hardware platform and the speaker for alarming. In short, this driver drowsiness monitoring system can always monitor drivers so as to avoid accidents in real time

A study of dynamic network selection in wireless overlay network

WLAN has been considered as a compliment technology for cellular network in the heterogeneous wireless network. Thus, seamless connection between these technologies play important role as the performance indicator. In this paper, we consider the user's velocity and channel holding time to predict the user's dwelling time in the WLAN area to assist in the initial network selection. If the expected completion time is lower than the predictive travelling time within the coverage area, together with the load and service characteristics, the algorithm will select WLAN instead of cellular network. Based on the discrete-event simulation, the results show that the proposed solution has better performance as compared to the location-based (WLAN First) and mobility threshold proposals

Traffic offloading and its application in CRRM

Common Radio Resource Management (CRRM) and traffic offloading are both promising approaches in the heterogeneous wireless networks (HWN) to increase overall resource efficiency and system performance. WLAN has been widely used as a complementary service for cellular network operator to offload their traffic. Based on traffic characteristics, user mobility and load balance we propose a new CRRM scheme that include traffic offloading functionality. When a user arrives in out of hot-spot area and no resource is available, the algorithm will identify some of the traffic to be offloaded in the overlap area from cellular network to WLAN and release the resource for the new user to use. The proposed approach also attempts to minimize unnecessary vertical handover (VHO) between cellular and WLAN. The effectiveness of the scheme is assessed analytically using the theory of 3D-Markov Chain. Numerical results demonstrate that the proposed CRRM scheme increase the overall system throughput, reduce the new call blocking probability and provide less service costs to the users

User behavior based call admission control for traffic steering in Wi-Fi/cellular networks

The expanded growth in smartphones and applications, hence data traffic resulted in cellular networks being conspicuously overwhelmed with demand for resources. Service providers constantly looking for suitable technologies and mechanisms to reduce the network congestion by offloading the data traffic, where Wi-Fi is an excellent option. In the traffic steering process, network selection is the most vital process, as it affects the user’s network experience. This paper focuses on enhancing the procedure of Call Admission Control (CAC). Two key functions were introduced into the call admission procedure, namely Channel Reserve Engine (CRE) and Traffic Steering Policy (TSP). Based on the simulation results, it is found the proposed CAC reduces the call blocking probability as compared with conventional CAC. Thus, it is suitable to be implemented in WLAN/Cellular integration

A combination of mobility, load and services for network selection in heterogenous wireless network

WLAN has been considered as a compliment technology for cellular network in the heterogeneous wireless network. Thus, seamless connection between these technologies play important role as the performance indicator. In this paper, we consider the user's velocity and channel holding time to predict the user's dwelling time in the WLAN area to assist in the initial network selection. Based on the mobility prediction, network load and type of services, the proposed algorithm will select the most suitable radio access network for the user. In addition, we also incorporate the traffic offloading method in order to accept as many users to the system while maintaining the quality of service of the users. Through extensive discrete-event simulation, the results show that the proposed solution has better performance as compared to the location-based (WLAN First) and mobility threshold proposals

A Privacy Preservation Quality of Service (QoS) Model for Data Exposure in Android Smartphone Usage

An Android smartphone contains built-in and externally downloaded applications that are used for entertainment, finance, navigation, communication, health and fitness, and so on. The behaviour of granting permissions requested by apps might expose the Android smartphone user to privacy risks. The existing works lack a formalized mathematical model that can quantify user and system applications risks. No multifaceted data collector tool can also be used to monitor the collection of user data and the risk posed by each application. A benchmark of the risk level that alerts the user and distinguishes between acceptable and unacceptable risk levels in Android smartphone user does not exist. Hence, to address privacy risk, a formalized privacy model called PRiMo that uses a tree structure and calculus knowledge is proposed. An App-sensor Mobile Data Collector (AMoDaC) is developed and implemented in real life to analyse user data accessed by mobile applications through the permissions granted and the risks involved. A benchmark is proposed by comparing the proposed PRiMo outcome with the existing available testing metrics. The results show that Tools & Utility/Productivity applications posed the highest risk as compared to other categories of applications. Furthermore, 29 users faced low and acceptable risk, while two users faced medium risk. According to the benchmark proposed, users who faced risks below 25% are considered as safe. The effectiveness and accuracy of the proposed work is 96.8%