Talmai Oliveira

Handling network uncertainty in heterogeneous wireless networks

With the constant evolution of wireless communication access technologies, there is a clear trend for mobile clients (MC) to be equipped with multiple interfaces for simultaneous access to different types of networks. This has been denominated a heterogeneous wireless networks. However, in order to achieve a desired quality of service while satisfying the users requirements, MCs must take advantage of the inherent characteristics of these access technologies, and rely on adaptable decision making mechanism for data forwarding. Unfortunately, route selection satisfying multiple constraints has proven to be NP-Complete, and although various heuristic algorithms have been proposed, they assume that the network state information is static and both the users and networks constraints are clearly specified. This paper focuses on the imprecise and dynamic nature of the network conditions while satisfying multiple - often contradicting - constraints. A fuzzy logic model is proposed which aims at translating the uncertainty factor of the network conditions to accurate values using the fuzzy logic tools and techniques. We then perform a thorough analysis of the metric values offered by various wireless technologies, and derive crisp values for the imprecise network parameters. A sensitivity analysis reflecting the performance of, and relative importance of metrics on each network is carried out. These results are shown to impact users decision in handing over data to the appropriate interface.

A V2X-based approach for reduction of delay propagation in vehicular Ad-Hoc networks

In this paper we investigate the time delay propagation rates in a Vehicular Ad-Hoc Network, where vehicular connectivity is supported by both Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) protocols. In our vision, seamless connectivity issues in a VANET with nearby network infrastructure, can be fixed by an opportunistic choice of a vehicular protocol between V2V and V2I. Such a decision is taken by each vehicle whenever it needs to transmit messages. Our technique — called as Vehicle-to-X — represents a handoff procedure between V2V and V2I, and vice versa, in order to keep vehicles connected independent of mobility issues and traffic scenarios. We investigate the time delay as a performance metric for protocol switching, and present the time propagation rates which occur when vehicles are transmitting warning messages, via V2V or V2I. Simulation results show how the simultaneous usage of pre-existing network infrastructure, together with inter-vehicular communications, provides low delays; while traditional opportunistic vehicular communications increases the transmission time delays and does not guarantee seamless connectivity to vehicles.

A practical distance estimator through distributed RSSI/LQI processing — An experimental study

The received signal strength indicator (RSSI) and the link quality indicator (LQI) are metrics that are commonly available in commercial off-the-shelf (COTS) sensor hardware. The former has been widely regarded as a cheap alternative for distance estimation and node localization. However, experimentally RSSI has been shown to behave in an inconsistent manner, even in ideal scenarios, and serve at best as bounds for distances. The latter is effectively a measure of chip error rate, and can be used to identify higher quality transmissions, and the combination RSSI/LQI can be expected to make more precise estimates with the tradeoff of increased delay and estimation cost. In this paper, we describe our distance estimation system that uses these two metrics and test our hypothesis purely through experimental measurements using sensor nodes. Results indicate that such a combination of metrics can be used to provide a tighter bound on the range of estimated distances.

Accurate Distance Estimation Using Fuzzy based combined RSSI/LQI Values in an Indoor Scenario: Experimental Verification

The received signal strength indicator (RSSI) and the link quality indicator (LQI) are the metrics that are commonly available in commercial off-the-shelf (COTS) sensor hardware. The former has been widely regarded as the main source for distance estimation and node localization. However, experimentally RSSI has been shown to behave in an inconsistent manner, even in ideal scenarios, and serve at best as bounds for distances. The latter is effectively a measure of chip error rate, and can be used to identify higher quality transmissions, and the combination RSSI/LQI can be expected to make more precise estimates with the tradeoff of increased delay and estimation cost. In this paper, we describe our distance estimation system that uses these two metrics and test our hypothesis purely through experimental measurements using sensor nodes. Results indicate that such a combination of metrics can be used to provide a tighter bound on the range of estimated distances. We then quantify the improvement in distance estimation by relying on these two metrics. Through a unique classification using fuzzy logic and TBM, we developed an algorithm that is capable of precise distance estimation within the range of 100cm to 400cm, on at least 80% of the times while reaching accuracy as high as 100%.

Reducing Unnecessary Handovers: Call Admission Control Mechanism between WiMAX and Femtocells

Femtocells are capable of providing services in shadowed areas of the WiMAX macrocell (cell coverage enhancement) and can relieve traffic from the macrocell networks, reduce infrastructure costs for the network operators, allow for network capacity increase, and provide needed service quality in an indoor environment. However, conventional handover methods cannot support a good enough performance under different mobility patterns and dynamic network conditions. This work introduces an appropriate call admission control and proposes a resource management scheme that significantly reduces unnecessary handovers. Simulation results are shown to validate our performance predictions.

Exploring load balancing in heterogeneous networks by rate distribution

We present a mechanism for optimum distribution of internet traffic over heterogeneous network environment. A heterogeneous network can be considered as a combination of multiple homogenous networks available simultaneously to the end users. For simplicity, each network has been modeled as a M/M/1 queue. We aim to minimize the number of jobs in each queue subject to constraints. The optimization problem has been achieved through the use of Lagrange multiplier. Depending on their service rate the formulation done in this work is shown to optimally divide the rate of incoming traffic into different networks.

The Node Reliability Approach to Broadcasting in Manets: Raising Reliability With Low End-to-End Delay

This paper evaluates how well a significant number of broadcasting protocols for MANETs behave when under a realistic scenario of momentary failures and topology changes, which is represented by an omission fault model. Reliable protocols which use additional mechanisms to ensure higher delivery rates beyond best- effort guarantees - have been proposed, but they exhibit unacceptably high end-to-end delays. As a result of the study conducted, a new mechanism that helps to enhance the reliability of deterministic broadcasting protocols is proposed. The mechanism allows for scalability, and is capable of ensuring good delivery rates (in spite of failures) while maintaining lower end-to-end delays. Simulation results demonstrate the efficacy of the mechanism.

Stochastic approximate dynamic programming with link estimation for high quality path selection in Wireless Mesh Networks

A lot of work has recently been published regarding metrics that could identify high quality paths in Wireless Mesh Networks (WMN). While results are encouraging, no optimal strategy has yet been identified that could estimate link quality and incorporate both the link reliability measurements as well as the bandwidth capacity. Furthermore, link estimation remains an open problem. Considering multi-user environment, any optimal solution would also need to consider multiple communication flows. These arguments have led us to study an approximate dynamic programming (DP) solution capable of utilizing limited network knowledge and stochastic process. Instead of proposing yet another link metric, we analyze a stochastic DP solution to the routing problem using a well established routing metric. Unlike deterministic DP where communication demands are fixed a priori and an optimal path is calculated before any real demands are known, we consider a more realistic scenario with stochastic metrics and formulate the optimal strategy for routing in WMNs. Performance results are given using simulation results.

Using minimization of maximal regret for interface selection in a heterogeneous wireless network

Integration of various wireless access technologies have pushed the evolution of mobile clients (MC) to be equipped with multiple interfaces for simultaneously accessing different network technologies. In these heterogeneous wireless networks (HWNs), MCs (and the underlying network) must be able to quickly and dynamically adapt to varying network conditions so as to satisfy required communication constraints. However, unlike their machine counterparts, MCs tend to have very vague and uncertain demands. This paper focuses on imprecise and dynamic nature of the MCs demands, while fulfilling multiple - often contradicting - constraints. The problem of uncertain decision making is considered by utilizing techniques from the multiple criteria decision making area. At each MC, an enhanced minimization of maximal regret (MMR) ranks available network interfaces and this maps imprecise user constraints to ranked interfaces.