Modern mobile devices (e.g., laptops, smartphones, tablets, etc.) are capable to run a wide set of different applications, with increasing throughput demands. At the same time, those devices are equipped with a set of heterogeneous interfaces to wireless access networks (e.g., Wi-Fi, UMTS/LTE-A, WiMAX, etc.). This paper proposes a decentralized load balancing algorithm based on game theory (and in particular on the concept of Wardrop equilibrium), which, according to the feedback gathered from the environment, is able: (i) to balance the traffic among the available wireless access technologies, with the aim of increasing the overall throughput and, consequently, to satisfy the needs of the users; (ii) to be reactive to possible network status changes (e.g., increasing of packet loss probability, link failures, etc.), by performing technology handover. The simulations show the higher performances obtained by the proposed algorithm, in terms of application throughput, compared to two approaches: one which statically choose a unique technology and the other one which dynamically choose the technology with the current smallest packet loss.
A decentralized load balancing algorithm for heterogeneous wireless access networks
ODDI, GUIDO;SURACI, VINCENZO
2014-01-01
Abstract
Modern mobile devices (e.g., laptops, smartphones, tablets, etc.) are capable to run a wide set of different applications, with increasing throughput demands. At the same time, those devices are equipped with a set of heterogeneous interfaces to wireless access networks (e.g., Wi-Fi, UMTS/LTE-A, WiMAX, etc.). This paper proposes a decentralized load balancing algorithm based on game theory (and in particular on the concept of Wardrop equilibrium), which, according to the feedback gathered from the environment, is able: (i) to balance the traffic among the available wireless access technologies, with the aim of increasing the overall throughput and, consequently, to satisfy the needs of the users; (ii) to be reactive to possible network status changes (e.g., increasing of packet loss probability, link failures, etc.), by performing technology handover. The simulations show the higher performances obtained by the proposed algorithm, in terms of application throughput, compared to two approaches: one which statically choose a unique technology and the other one which dynamically choose the technology with the current smallest packet loss.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
