5G Heterogeneous Networks (HetNets) represent a promising solution to meet the continuous traffic demand originated mainly by the new mobile applications with real and non-real time requirements, new devices, cloud services, IoT and the novel IoE applications. The incorporation of traffic offloading techniques to deal with these demands is an essential part to be implemented in the future networks. Current techniques are focused on implementing policies about how to address the traffic between end users and a network entity (e.g., Macrocell or Small Cell). However, a number of issues can arise if the network topology is not considered in order to transport the traffic from sources to destinations. In this work we present a new traffic distribution technique that takes advantage of the expected 5G Heterogeneous Networks capabilities to bring significant gains in traffic distribution, resilience and overall network capacity improvements in such networks. Our technique is oriented to establishing topologies that improve the overall connectivity by incorporating communication links between any network component (e.g., small cell to small cell, macrocell to macrocell) as a way to offload traffic from congested zones. Our experimental results shows that the proposed scheme outperform traditional HetNets.

En este artículo presentamos un nuevo enfoque de acceso al medio de capa cruzada que utiliza información topológica de la red para seleccionar la probabilidad de transmisión de cada nodo. En el esquema propuesto, la probabilidad de acceder al canal es asignada en función tanto de la entropía topológica de la red, como de la probabilidad individual de cada nodo de ser elegido por el algoritmo de enrutamiento como retransmisor en un flujo de datos de extremo-a-extremo. La entropía topológica de la red mide la capacidad de dicha red para distribuir el tráfico entre los nodos que la componen. Valores de entropía baja indican que el tráfico tenderá a concentrarse en regiones particulares de la red y que por lo tanto la probabilidad de que los nodos localizados en dichas regiones experimenten contención, es alta. En este caso, la probabilidad de acceso al medio de los nodos que se encuentran en esas regiones deberá ser seleccionada de forma tal que se reduzca la probabilidad de que experimenten contención. Experimentos de simulación muestran que el esquema propuesto logra ganancias de desempeño en términos del caudal, la probabilidad de experimentar colisiones y el retardo extremo-a-extremo.

Wireless sensor networks are composed of many nodes distributed in a region of interest to monitor different environments and physical variables. In many cases, access to nodes is not easy or feasible. As such, the system lifetime is a primary design parameter to consider in the design of these networks. In this regard, for some applications, it is preferable to extend the system lifetime by actively reducing the number of packet transmissions and, thus, the number of reports. The system administrator can be aware of such reporting reduction to distinguish this final phase from a malfunction of the system or even an attack. Given this, we explore different mathematical functions that drastically reduce the number of packet transmissions when the residual energy in the system is low but still allow for an adequate number of transmissions. Indeed, in previous works, where the negative exponential distribution is used, the system reaches the point of zero transmissions extremely fast. Hence, we propose different dampening functions with different decreasing rates that present oscillations to allow for packet transmissions even at the end of the system lifetime. We compare the system performance under these mathematical functions, which, to the best of our knowledge, have never been used before, to find the most adequate transmission scheme for packet transmissions and system lifetime. We develop an analytical model based on a discrete-time Markov chain to show that a moderately decreasing function provides the best results. We also develop a discrete event simulator to validate the analytical results.

This paper presents the spectral gap-based topology control algorithm (SGTC) for wireless backhaul networks, a novel approach that employs the Laplacian Spectral Gap (LSG) to find expander-like graphs that optimize the topology of the network in terms of robustness, diameter, energy cost, and network entropy. The latter measures the network’s ability to promote seamless traffic offloading from the Macro Base Stations to smaller cells by providing a high diversity of shortest paths connecting all the stations. Given the practical constraints imposed by cellular technologies, the proposed algorithm uses simulated annealing to search for feasible network topologies with a large LSG. Then, it computes the Pareto front of the set of feasible solutions found during the annealing process when considering robustness, diameter, and entropy as objective functions. The algorithm’s result is the Pareto efficient solution that minimizes energy cost. A set of experimental results shows that by optimizing the LSG, the proposed algorithm simultaneously optimizes the set of desirable topological properties mentioned above. The results also revealed that generating networks with good spectral expansion is possible even under the restrictions imposed by current wireless technologies. This is a desirable feature because these networks have strong connectivity properties even if they do not have a large number of links.