Studying Mobile Internet Technologies with Agent Based Mean-Field Models

Abstract

Abstract. We analyze next generation cellular networks, offering connectivity to mobile users through LTE as well as WiFi. We develop a framework based on the Markovian agent formalism, which can model several aspects of the system, including the dynamics of user traffic and the allocation of the network radio resources. In particular, through a mean-field solution, we show the ability of our framework to capture the system behavior in flash-crowd scenarios, i.e., when a burst of traffic requests takes place in some parts of the network service area.

Modeling and Evaluating the Effects of Big Data Storage Resource Allocation in Global Scale Cloud Architectures

“…This is a shorthand to denote that the three parameters can depend on the whole solution x, that is on the number of agents: In literature on MAM, several different ways of computing parameters K, b and v have been proposed, each aimed at simulating a particular interaction mechanism tailored for specific applicative domain. For example in (Chiasserini et al, 2013) agents are used to model different Internet connection technologies, focusing on WiFi and LTE. In this work we propose an approach similar to the methodology presented in (Cordero et al, 2013).…”

Energy efficient offloading for competing users on a shared communication channel

“…Rahmati and Zhong (2007) proposed an online wireless network selection mechanism that trades off offloading transmission efficiency on an intermittently available WiFi network, and the energy consumption needed to search of a better WiFi connection. By monitoring the dynamics of user traffic and energy aware allocation of the radio network resource to mobile users, Gribaudo et al (2013) developed a framework based on a Markovian agent formalism to minimize user energy consumption.…”

Traffic offloading/onloading in multi-RAT cellular networks

“…In Markovian Agents, the interaction among the agents is modeled through functional transition rates that represent the speed at which agents move from one state to another. In this work, we have extended the functional rates presented in [13] in order to consider both an arbitrary number of neighboring BSs for each BS and time-dependent resource allocation policies. In the following, we denote by n…”