Christos Tsiaras

Towards a comprehensive framework for QOE and user behavior modelling

While the modeling of QoE has made significant advances over the last couple of years, currently existing models still lack an integration of user behavior aspects and user context factors along with the consideration of appropriate temporal scales. Therefore, the goal of this paper is to present a comprehensive QoE and user behavior model providing a framework which allows joining a multitude of existing modeling approaches under the perspectives of service provider benefit, user well-being and technical system performance. In addition, we discuss the role of a broad range of corresponding influence factors, with a specific emphasis on user and context issues, and illustrate our proposal through a series of related use cases.

Towards Evaluating Type of Service Related Quality-of-Experience on Mobile Networks

Quality of Service (QoS) metrics have been traditionally used to evaluate the perceived quality of services delivered by network operators. However, these metrics are not suitable for evaluating the experience of an end-user. The experience of a user is quantified based upon activities such as speed of web page loading, quality of video streaming, or voice quality of Internet-telephony. Due to the temporal and geographical nature of mobile networks, the perceived experience of a user may change based on location and time. Mobile operators may prioritize certain services over others, leading to a service type dependent Quality of Experience (QoE). In this paper we present a mobile application developed to gather metrics necessary to evaluate QoE in a mobile environment. Our approach towards obtain not just a general, but service specific mean opinion score (MOS) to quantify QoE is also discussed. Initial experiments and measurement tests show that it is possible for the same operator to deliver different QoE based on service and even time-of-day.

A deterministic QoE formalization of user satisfaction demands (DQX)

Measuring the impact of technical variables, such as latency, bandwidth, or resources priority-access, on Quality-of-Experience (QoE) of various services demands an extensive feedback from end-users, when those variables change. Estimating QoE in a given scenario becomes harder, when non-technical variables, such as price, need to be considered in addition to technical ones. In any case, detailed feedback that correlates all variables affecting QoE is needed by end-users for each service separately. In this work a deterministic mathematical model (DQX) encapsulating user demands, service characteristics, and variable specifications is proposed to formalize the QoE calculation, considering one or multiple and diverse variables. The output of QoE functions presented here can be normalized such that results will be compatible with the five-point scale Mean Opinion Score (MOS), proposed by the ITU-T.

Optimal and achievable cost/delay tradeoffs in delay-tolerant networks

Tradeoffs between the packet delivery delay and various types of packet transportation cost are a recurring theme in Delay-Tolerant Networks (DTNs). In this work we study such tradeoffs, first in a general and then in a mobile wireless setting. In the general setting, we capture the tradeoff between the delivery delay of a packet and its transportation cost (which comprises a transmission component and a storage component) on the cost-delay plane using the Optimal Cost/Delay Curve (OC/DC), for the case when the packet follows optimal routes, and the Achievable Cost/Delay Curve (AC/DC), for the case when a specific (suboptimal) routing protocol is used. Applying the framework of the general setting to mobile wireless DTNs, we evaluate a novel set of geographic routing protocols with delay-tolerant features against both state-of-the-art routing protocols (using their respective average AC/DCs) and also optimal routing (described in terms of the average OC/DC). Compared to the state-of-the-art protocols, our protocols are shown to achieve cost/delay tradeoffs much closer to the optimal one.

VoIP-based calibration of the DQX model

In the Internet Protocol (IP) ecosystem, Quality-of-Experience (QoE) is important information needed by Service Providers (SP) to improve their services. However, end-users satisfaction, which can be reflected by QoE metrics, cannot be easily measured like technical variables, such as bandwidth and latency. QoE can either be estimated through mathematical models or it can be measured through an experimental setup. In this work a Voice-over-Internet Protocol-based (VoIP) QoE measurement setup has been designed to capture end-users QoE in VoIP services. The data measured during these experiments are used to define all necessary parameters of the Deterministic QoE model (DQX) in this VoIP scenario. Such a calibration of the model is essential to adapt it to the particular service and its technical and non-technical conditions in which it is used. Furthermore, those DQX results achieved are compared with those results of the IQX Hypothesis and the E-Model, being proposed by the ITU-T. Thus, it is finally shown that DQX can capture more accurately end-users QoE in VoIP scenarios.

An automatic and on-demand MNO selection mechanism

A manual selection of the Mobile Network Operator (MNO) to be used on a mobile device is possible through the respective user interface. Furthermore, mobile devices can be adjusted to select automatically the MNO based on the strongest signal strength, among the list of those MNOs the Subscriber Identity Module (SIM) card is allowed to be registered with. However, so far in modern mobile operating systems, such as Android and iOS, there is no available method in the public developers Application Programming Interface (API), which allows for an automatic and on-demand selection of the MNO by third-party applications. Recently, various research approaches assume the existence of an automatic and on-demand MNO selection mechanism to achieve different goals, such as breaking the termination rates monopoly (AbaCUS) or minimizing the non-ionizing radiation of mobile/wearable devices. The interest of such a mechanism has been raised three years ago by the Android developers community. Thus, this work here presents an automatic and on-demand MNO selection mechanism, that has been designed and implemented on the Android platform. For evaluation purposes the energy and end-to-end (e2e) time consumption while switching among MNOs using this mechanism is evaluated and as an applied example the data consumption of AbaCUS signaling messages is measured.

On the cost/delay tradeoff of wireless delay tolerant geographic routing

In Delay Tolerant Networks (DTNs), there is a fundamental tradeoff between the aggregate transport cost of a packet and the delay in its delivery. We study this tradeoff in the context of geographical routing in wireless DTNs. We first specify the optimal cost/delay tradeoff, i.e., the tradeoff under optimal network operation, using a dynamic network construction termed the Cost/Delay Evolving Graph (C/DEG) and the Optimal Cost/Delay Curve (OC/DC), a function that gives the minimum possible aggregate transportation cost versus the maximum permitted delivery delay. We proceed to evaluate the performance of two known delay tolerant geographic routing rules, i.e., MOVE and AeroRP, a delay tolerant version of the geographic routing rule that selects as next relay the node for which the cost-per-progress ratio is minimized, and finally two novel rules, the Balanced Ratio Rule (BRR) and the Composite Rule (CR). The evaluation is in terms of the aggregate packet transmission cost as a function of the maximum permitted packet delivery delay. Simulations show that CR achieves a cost/delay tradeoff that is overall the closest to the optimal one specified by the OC/DC, while BRR achieves the smallest aggregate transmission costs for large packet delays and a fixed transmission cost model.

Schengen Routing: A Compliance Analysis

Schengen Routing was proposed as a countermeasure to traffic monitoring activities practiced by intelligence agencies. This work here presents the results of a larger-scale measurement performed to quantify Schengen Routing compliance in today’s Internet. Based on 3388 TCP, UDP, and ICMP traceroute measurements executed from RIPE Atlas probes located in over 1100 different Autonomous Systems (AS) in the Schengen Area, it was found that 34.5% to 39.7% of these routes are Schengen-compliant, while compliance levels vary from 0% to 80% among countries. Finally, an approach was developed that allows end-users to determine whether a specific route to a host is Schengen-compliant or not.

An NFC Relay Attack with Off-the-shelf Hardware and Software

Passive Near Field Communication NFC devices, such as contactless smart cards, use NFC to communicate with other devices without any physical connection or an internal battery source, deriving power inductively via the radio field generated by the NFC reader device. Today, many Point-of-Sale PoS terminals, credit cards, and also mobile devices are NFC-capable and facilitate contactless payments. Although the communication range is typically limited to a few centimeters, NFC attacks exist that exploit such contactless communication channels. This paper focuses on NFC relay attacks and shows that a practical relay attack on public transport PoS terminals, using off-the-shelf mobile devices and hardware, is feasible. Finally, countermeasures are discussed with the main finding that currently the best countermeasure against relay attacks is to physically shield an NFC device.

Automatic and on-demand Mobile Network Operator (MNO) selection mechanism demonstration

The use of smartphones has been increasing in the last few years. Many open standards and accessible Application Programming Interfaces (API) make it easier for developers to achieve their ideas and many communities, such as xda developers, or stackoverflow provide good questions and answers concerning mobile application development. Questions on how to search for available MNOs and how to switch a Mobile Network Operator (MNO) programmatically on Android devices already arose in 2010. Until the work concluded here, an answer of those questions have not been published. The main reason is that there are no methods provided in the public Android API that allows for performing such tasks. In this work here two mechanisms allowing for (a) an automatic and on-demand MNO selection and (b) an MNO look-up mechanism have been developed for the Android platform. The efficiency of these mechanisms has been evaluated with respect to power and time consumption.