Scanless Fast Handoff Technique Based on Global Path Cache for WLANs

Wireless LANs (WLANs) have been widely adopted and are more convenient as they are inter-connected as wireless campus networks and wireless mesh networks. However, timesensitive multimedia applications, which have become more popular, could suffer from long end-to-end latency in WLANs.This is due mainly to handoff delay, which in turn is caused by channel scanning. This paper proposes a technique called Global Path-Cache (GPC) that provides fast handoffs in WLANs.GPC properly captures the dynamic behavior of the network andMSs, and provides accurate next AP predictions to minimize the handoff latency. Moreover, the handoff frequencies are treated as time-series data, thus GPC calibrates the prediction models based on short term and periodic behaviors of mobile users. Our simulation study shows that GPC virtually eliminates the need to scan for APs during handoffs and results in much better overall handoff delay compared to existing methods

Scanless Fast Handoff Technique Based on Global Path Cache for WLANs

Wireless LANs (WLANs) have been widely adopted and are more convenient as they are inter-connected as wireless campus networks and wireless mesh networks. However, timesensitive multimedia applications, which have become more popular, could suffer from long end-to-end latency in WLANs.This is due mainly to handoff delay, which in turn is caused by channel scanning. This paper proposes a technique called Global Path-Cache (GPC) that provides fast handoffs in WLANs.GPC properly captures the dynamic behavior of the network andMSs, and provides accurate next AP predictions to minimize the handoff latency. Moreover, the handoff frequencies are treated as time-series data, thus GPC calibrates the prediction models based on short term and periodic behaviors of mobile users. Our simulation study shows that GPC virtually eliminates the need to scan for APs during handoffs and results in much better overall handoff delay compared to existing methods

Behavior-Based Mobility Prediction for Seamless Handoffs in Mobile Wireless Networks

The field of wireless networking has received unprecedented attention from the research community during the last decade due to its great potential to create new horizons for communicating beyond the Internet. Wireless LANs (WLANs) based on the IEEE 802.11 standard have become prevalent in public as well as residential areas, and their importance as an enabling technology will continue to grow for future pervasive computing applications. However, as their scale and complexity continue to grow, reducing handoff latency is particularly important. This paper presents the Behavior-based Mobility Prediction scheme to eliminate the scanning overhead incurred in IEEE 802.11 networks. This is achieved by considering not only location information but also group, time-of-day, and duration characteristics of mobile users. This captures short-term and periodic behavior of mobile users to provide accurate next-cell predictions. Our simulation study of a campus network and a municipal wireless network shows that the proposed method improves the next-cell prediction accuracy by 23~43% compared to location-only based schemes and reduces the average handoff delay down to 24~25 ms

Behavior-Based Mobility Prediction for Seamless Handoffs in Mobile Wireless Networks

The field of wireless networking has received unprecedented attention from the research community during the last decade due to its great potential to create new horizons for communicating beyond the Internet. Wireless LANs (WLANs) based on the IEEE 802.11 standard have become prevalent in public as well as residential areas, and their importance as an enabling technology will continue to grow for future pervasive computing applications. However, as their scale and complexity continue to grow, reducing handoff latency is particularly important. This paper presents the Behavior-based Mobility Prediction scheme to eliminate the scanning overhead incurred in IEEE 802.11 networks. This is achieved by considering not only location information but also group, time-of-day, and duration characteristics of mobile users. This captures short-term and periodic behavior of mobile users to provide accurate next-cell predictions. Our simulation study of a campus network and a municipal wireless network shows that the proposed method improves the next-cell prediction accuracy by 23~43% compared to location-only based schemes and reduces the average handoff delay down to 24~25 ms

Wireless Handheld Solution for the Gaming Industry

of the essential elements of success in the gaming industry is the requirement of providing exceptional customer service. Technology plays a significant role in bringing state of the art solutions that enhance the overall customer experience. Currently a guest must go through multiple steps and a variety of departments to simply resolve issues with their player accounts (loyalty programs), update customer profiles, book hotel and restaurant reservations, sign up for promotions, etc. In order to effectively take care of these customers in both a timely and efficient manner, a wireless handheld device is needed that employees can carry with them to resolve and address these concerns. This project is aimed at identifying the proper wireless infrastructure for the gaming environment and also the wireless handheld device, such as an Ultra Mobile PC (UMPC) to effectively and efficiently take care of customers

Predicting expected TCP throughput using genetic algorithm

Predicting the expected throughput of TCP is important for several aspects such as e.g. determining handover criteria for future multihomed mobile nodes or determining the expected throughput of a given MPTCP subflow for load-balancing reasons. However, this is challenging due to time varying behavior of the underlying network characteristics. In this paper, we present a genetic-algorithm-based prediction model for estimating TCP throughput values. Our approach tries to find the best matching combination of mathematical functions that approximate a given time series that accounts for the TCP throughput samples using genetic algorithm. Based on collected historical datapoints about measured TCP throughput samples, our algorithm estimates expected throughput over time. We evaluate the quality of the prediction using different selection and diversity strategies for creating new chromosomes. Also, we explore the use of different fitness functions in order to evaluate the goodness of a chromosome. The goal is to show how different tuning on the genetic algorithm may have an impact on the prediction. Using extensive simulations over several TCP throughput traces, we find that the genetic algorithm successfully finds reasonable matching mathematical functions that allow to describe the TCP sampled throughput values with good fidelity. We also explore the effectiveness of predicting time series throughput samples for a given prediction horizon and estimate the prediction error and confidence.Peer ReviewedPostprint (author's final draft

Elastic QoS Scheduling with Step-by-Step Propagation in IEEE 802.11e Networks with Multimedia Traffic

The spreading diffusion of wireless devices and the crowded coexistence of multimedia applications greedy of bandwidth and with strict requirements stress the service provisioning offered by wireless technologies. WiFi is a reference for wireless connectivity and it requires a continuous evolution of its mechanism in order to follow increasingly demanding service needs. In particular, despite the evolution of physical layer, some critical contexts, such as industrial networks, telemedicine, telerehabilitation, and virtual training, require further refined improvements in order to ensure the respect of strict real-time service requirements. In this paper an in-depth analysis of Dynamic TXOP HCCA (DTH) MAC enhanced centralized scheduler is illustrated and it is further refined introducing a new improvement, DTH with threshold. DTH and DTH with threshold can be integrated with preexisting centralized schedulers in order to improve their performances, without any overprovisioning that can negatively impact on the admission control feasibility test. Indeed, without modifying the centralized scheduler policy, they combine together the concepts of reclaiming transmission time and statistical estimation of the traffic profile in order to provide, at each polling, an instantaneous transmission time tailored to the variable traffic requirements, increasing, when necessary, the service data rate. These mechanisms can coexist with advanced physical layer-based solutions, providing the required service differentiation. Experimental results and theoretical analysis, based on elastic scheduler theory, show that they are effective especially in the case of Variable Bit Rate traffic streams in terms of transmission queues length, packets loss, delay, and throughput

Performance Modeling and Analysis of Wireless Local Area Networks with Bursty Traffic

The explosive increase in the use of mobile digital devices has posed great challenges in the design and implementation of Wireless Local Area Networks (WLANs). Ever-increasing demands for high-speed and ubiquitous digital communication have made WLANs an essential feature of everyday life. With audio and video forming the highest percentage of traffic generated by multimedia applications, a huge demand is placed for high speed WLANs that provide high Quality-of-Service (QoS) and can satisfy end user’s needs at a relatively low cost. Providing video and audio contents to end users at a satisfactory level with various channel quality and current battery capacities requires thorough studies on the properties of such traffic. In this regard, Medium Access Control (MAC) protocol of the 802.11 standard plays a vital role in the management and coordination of shared channel access and data transmission. Therefore, this research focuses on developing new efficient analytical models that evaluate the performance of WLANs and the MAC protocol in the presence of bursty, correlated and heterogeneous multimedia traffic using Batch Markovian Arrival Process (BMAP). BMAP can model the correlation between different packet size distributions and traffic rates while accurately modelling aggregated traffic which often possesses negative statistical properties. The research starts with developing an accurate traffic generator using BMAP to capture the existing correlations in multimedia traffics. For validation, the developed traffic generator is used as an arrival process to a queueing model and is analyzed based on average queue length and mean waiting time. The performance of BMAP/M/1 queue is studied under various number of states and maximum batch sizes of BMAP. The results clearly indicate that any increase in the number of states of the underlying Markov Chain of BMAP or maximum batch size, lead to higher burstiness and correlation of the arrival process, prompting the speed of the queue towards saturation. The developed traffic generator is then used to model traffic sources in IEEE 802.11 WLANs, measuring important QoS metrics of throughput, end-to-end delay, frame loss probability and energy consumption. Performance comparisons are conducted on WLANs under the influence of multimedia traffics modelled as BMAP, Markov Modulated Poisson Process and Poisson Process. The results clearly indicate that bursty traffics generated by BMAP demote network performance faster than other traffic sources under moderate to high loads. The model is also used to study WLANs with unsaturated, heterogeneous and bursty traffic sources. The effects of traffic load and network size on the performance of WLANs are investigated to demonstrate the importance of burstiness and heterogeneity of traffic on accurate evaluation of MAC protocol in wireless multimedia networks. The results of the thesis highlight the importance of taking into account the true characteristics of multimedia traffics for accurate evaluation of the MAC protocol in the design and analysis of wireless multimedia networks and technologies

Wireless local area network management frame denial- of-service attack detection and mitigation schemes

Wireless Local Area Networks (WLAN) are increasingly deployed and in widespread use worldwide due to its convenience and low cost. However, due to the broadcasting and the shared nature of the wireless medium, WLANs are vulnerable to a myriad of attacks. Although there have been concerted efforts to improve the security of wireless networks over the past years, some attacks remain inevitable. Attackers are capable of sending fake de-authentication or disassociation frames to terminate the session of active users; thereby leading to denial of service, stolen passwords, or leakage of sensitive information amongst many other cybercrimes. The detection of such attacks is crucial in today's critical applications. Many security mechanisms have been proposed to effectively detect these issues, however, they have been found to suffer limitations which have resulted in several potential areas of research. This thesis aims to address the detection of resource exhaustion and masquerading DoS attacks problems, and to construct several schemes that are capable of distinguishing between benign and fake management frames through the identification of normal behavior of the wireless stations before sending any authentication and de-authentication frames. Thus, this thesis proposed three schemes for the detection of resource exhaustion and masquerading DoS attacks. The first scheme was a resource exhaustion DoS attacks detection scheme, while the second was a de- authentication and disassociation detection scheme. The third scheme was to improve the detection rate of the de-authentication and disassociation detection scheme using feature derived from an unsupervised method for an increased detection rate. The effectiveness of the performance of the proposed schemes was measured in terms of detection accuracy under sophisticated attack scenarios. Similarly, the efficiency of the proposed schemes was measured in terms of preserving the resources of the access point such as memory consumptions and processing time. The validation and analysis were done through experimentation, and the results showed that the schemes have the ability to protect wireless infrastructure networks against denial of service attacks