Since mobile devices are equipped with limited battery power, it is essential to have efficient power management mechanisms in mobile broadband networks such as mobile WiMAX that enable always on connectivity and provide high throughputs. In recent times Voice over IP (VoIP) has emerged as an important and dominant application in broadband mobile networks such as WiMAX. VoIP traffic is uniquely characterized by small packets sent regularly at periodic intervals and are bound by strict latency requirements for satisfactory user experience. This paper presents novel mechanisms to achieve enhanced power saving during a VoIP session by exploiting unique characteristics of VoIP traffic in next generation mobile WiMAX networks based on IEEE 802.16m standard. The analytical model and simulation results indicate that proposed methods reduce the average power consumption during a VoIP call by up to 70% compared to the existing IEEE 802.16m draft specifications. Moreover, the simulation results closely match our proposed analytical model.

Mobility management protocols operating from different layers of the classical protocol stack (e.g., link, network, transport, and application layers) have been proposed in the last several years. These protocols achieve different handoff performance for different types of applications. In this paper, mobile applications are grouped into five different classes, class A through class E, based on their mobility management requirements. Analytical models are developed to investigate the handoff performance of the existing mobility management protocols for these application classes. The analysis shows that applications of a particular class experience different handoff performance when different mobility management protocols are used. Handoff performance comparisons of different mobility management protocols are carried out to decide on the suitable mobility management protocol for a particular application class. The results of mathematical analysis advocate the use of transport layer mobility management for class B and class C applications, mobile IP for non-real-time class D and class E applications, and session initiation protocol-based mobility management for real-time class D and class E applications. Moreover, through analytical modeling, the parameters that influence the handoff performance of mobility management protocols are identified. These parameters can be used to design new application-adaptive techniques to enhance the handoff performance of the existing mobility management protocols.

Next-generation wireless systems (NGWS) integrate different wireless networks, each of which is optimized for some specific services and coverage area to provide ubiquitous communications to the mobile users. It is an important and challenging issue to support seamless handoff management in this integrated architecture. The existing handoff management protocols are not sufficient to guarantee handoff support that is transparent to the applications in NGWS. In this work, a cross-layer (layer 2 + 3) handoff management protocol, CHMP, is developed to support seamless intra and intersystem handoff management in NGWS. Cross-layer handoff management protocol uses mobile's speed and handoff signaling delay information to enhance the handoff performance of mobile IP that is proposed to support mobility management in wireless IP networks. First, the handoff performance of mobile IP is analyzed with respect to its sensitivity to the link layer (layer 2) and network layer (layer 3) parameters. Then, a cross-layer handoff management architecture is developed using the insights learnt from the analysis. Based on this architecture, the detailed design of CHMP is carried out. Finally, extensive simulation experiments are carried out to evaluate the performance of CHMP. The theoretical analysis and simulation results show that CHMP significantly enhances the performance of both intra and intersystem handoffs

A novel algorithm called velocity estimation using the power spectral density (VEPSD), which uses the Doppler spread in the received signal envelope to estimate the velocity of a mobile user (MU), is introduced in this paper. The Doppler spread is estimated using the slope of the power spectral density (PSD) of the received signal envelope. The performance of the VEPSD algorithm is evaluated in both Rayleigh and Rician fading environments. The sensitivity of the estimation error to additive white Gaussian noise (AWGN), Rice factor (K), and the angle of arrival of the line-of-sight (LOS) component is analyzed and compared with the level crossing rate (LCR) and covariance-based velocity estimators. Simulation results show that VEPSD estimates the velocity of MUs accurately. It is also shown that VEPSD can be used for velocity estimation under nonisotropic scattering and is well suited for next-generation wireless systems (NGWSs).

Per-flow network traffic measurements are needed for effective network traffic management, network performance assessment, and detection of anomalous network events such as incipient DoS attacks. Explicit measurement of per-flow traffic statistics is difficult in backbone networks because tracking the possibly hundreds of thousands of flows needs correspondingly large high-speed memories. To reduce the measurement overhead, many previous papers have proposed the use of random sampling and this is also used in commercial routers (Cisco's Net Flow). Our goal is to develop a new scheme that has very low memory requirements and has quick convergence to within a prespecified accuracy. We achieve this by use of a novel approach based on sampling two-runs to estimate per-flow traffic. (A flow has a two-run when two consecutive samples belong to the same flow). Sampling two-runs automatically biases the samples towards the larger flows thereby making the estimation of these sources more accurate. This biased sampling leads to significantly smaller memory requirement compared to random sampling schemes. The scheme is very simple to implement and performs extremely well