Anna V. Guglielmi

A Markov analysis of automatic repeat request for video traffic transmission

This paper presents a study of the automatic repeat request (ARQ) technique applied to the transmission of multimedia traffic, e.g., video content. In the literature, retransmission-based techniques are usually investigated by means of queueing theory and assuming a homogeneous flow of identical packets, which are sent and possibly retransmitted all in the same way. However, multimedia packets are the result of an incremental encoding that leverages spatial and temporal redundancy, which is naturally present in the raw data. As a result, the flow is inherently made of packets with different roles, which should also be treated differently by the ARQ mechanism. Thus, we assume that different levels of error protection are applied, and also we model the decoding process at the receiver as accounting for a dependence relationship among the packets. Moreover, since error correlation has a strong impact on the performance, we consider a transmission over a Markov channel where we tune not only the error probability but also the average error burst size. This enables the derivation of several performance metrics in an entirely analytical manner via Markov analysis. Finally, some numerical results are explored and possible applications on the development of guidelines for multimedia transmission are discussed.

Markov models for electric vehicles: the role of battery parameters and charging point frequency

Electric vehicles represent a promising choice to decrease pollution and reducing fossil fuel consumption. However, their limited autonomy poses a challenge that prevents them from being suitable for many car users. Several practical solutions are sought to avoid this problem, in particular one may think of enhancing the battery capacity, reducing the charging time, or increasing the frequency of charging points. In this paper, we discuss how these aspects can be integrated by a proper Markov model, thereby offering a neat analytical solution to investigate all these problems. Some preliminary results are also shown to demonstrate the descriptiveness of the model. Further investigation can frame the proposed contribution within an optimization framework, maintaining an analytical context.

Analysis of strategic security through game theory for mobile social networks

in mobile social networks, legitimate transmitting nodes can be contrasted by malicious attackers acting on the purpose of disrupting communication. Our aim is to use game theory to identify malicious nodes. With respect to previous similar formulations, we consider a wider array of action options for the players, notably we include a choice about whether to engage or not in packet exchanging, and also malicious activity and its prevention. This leads to a structured analysis of the resulting game, resulting in different equilibria. We use a Bayesian Game where the critical parameter is the likelihood that the unknown agent is malicious. Investigating on the Nash equilibria in pure/mixed strategies found, we can see how in some cases the malicious behavior of the nodes can be tolerated since a trade-off between their presence and the effect of damages that they caused can be reached.

Markov analysis of video transmission based on differential encoded HARQ

In this paper, we analyze hybrid automatic repeat request applied to the transmission of video content over the wireless channel. Retransmission-based techniques are usually applied to queueing systems assuming a homogeneous flow of identical packets, which are all transmitted and possibly retransmitted in the same way. However, multimedia packets are encoded with incremental methods leveraging spatial and temporal redundancy and as such, they have different roles and should be treated differently by the retransmission mechanism. Therefore, our work considers a selective retransmission scheme with unequal error protection applied to a multimedia flow subdivided into distinguishable packets. We assume a binary channel with memory and non-zero round-trip time. We utilize discrete-time Markov chains to model the channel and the transmission/retransmission system. This enables a closed-form derivation of performance metrics via Markov analysis. Numerical results are discussed and possible implications on multimedia communications are evaluated.

Social Communication to Improve Group Recognition in Mobile Networks

In this paper, we consider the problem of recognizing groups of similar nodes within a mobile network. Nodes belonging to the same group have the same preferences, e.g., in terms of friendship with other nodes. However, due to limited communication range, each node has a partial view of the network and is aware only of its friendship relationships with the immediate neighbors. Depending on how large the communication range actually is, the problem can be in principle solved by clustering nodes by classifying the friendship relationships on a scale from -1 to +1 (sure not friendship to sure friendship, with unknown nodes classified as 0). However, if the communication range is small, this approach leads to large errors. We show how a simpler procedure based on the exchange of social information in a collaborative fashion is able to achieve better results than more expensive clustering algorithms. Also, these two approaches can be combined by clustering nodes after exchanging a given amount of social information, thus improving the overall results.

Bayesian game analysis of a queueing system with multiple candidate servers

We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.