Integration of Mobile-IP and OLSR for a Universal Mobility

Trends in fourth generation (4G) wireless networks are clearly identified by the full-IP concept where all traffic (data, control, voice and video services, etc.) will be transported in IP packets. Many proposals are being made to enhance IP with the functionalities necessary to manage the mobility of nodes, so that networks can provide global seamless roaming between heterogeneous wireless and wired networks. In this paper, we focus on the management of universal mobility, including both large scale macro-mobility and local scale micro-mobility. We propose a hierachical architecture (i) extending micro-mobility management of a wireless access network to an ad-hoc access network, (ii) connecting this ad-hoc network to the Internet and (iii) integrating Mobile IP and OLSR, a routing protocol for ad-hoc networks, to manage universal mobility. This architecture is validated by an implementation based on DynamicsMobile-IP and OLSR version 7. We show how the brodcast of Mobile-IP Agent Advertisement can be optimized using OLSR MPR-flooding.     

An automated sensor nodes’ speed estimation for wireless sensor networks

Wireless sensor networks (WSNs) have become more and more notorious thanks to their numerous advantages. But, some of the WSN weaknesses, inherent to sensor nodes’ particularities (low memory, finite battery, etc.), make these networks vulnerable especially for some particular scenarios such as nodes’ mobility which alters the correct network functioning and completely compromises its normal behavior. Thus, we propose in this paper a novel mobility prediction model called the general Bayesian-based mobility prediction (G-BMP) model where sensor nodes’ speed values are derived based on a Bayesian inference paradigm and upon the occurrence of “expired links” and “non-expired links” events. Moreover, to make the implementation of G-BMP possible on sensor devices, we introduce some simplifications during the computation and the transmission of speed distributions. The evaluation of G-BMP using python illustrates the accuracy of the model in deriving the correct speed values in a timely manner. We also compare the performance of G-BMP to the native BMP model that only considers the expired link events when updating the nodes’ speed distributions. The results show that the convergence to real speed values within sensor nodes is faster with G-BMP than that with the native BMP model. In addition, all the simulations illustrate the accuracy of the simplifications used to reduce the overhead generated by the frequent exchange of speed distributions.     

Multicast tree structure and the power law

In this paper, we investigate structural properties of multicast trees that give rise to the so-called multicast power law. The law asserts that the ratio R(n) of the average number of links in a multicast tree connecting the source to n destinations to the average number of links in a unicast path, satisfies asymptotically R(n)/spl ap/cn/sup /spl phi//, 0相似文献