Abstract
The emerging global communication and service infrastructures need to be more and more pervasive, high-performing and reliable. The underlying scenario is basically characterized by decentralization, autonomy, and general lack of coordination among the heterogeneous network entities, the network in turn intrinsically being a common playground for a large number of users. These users exhibit various degrees of intentional or unintentional non cooperative behaviour, while competing for shared and often scarce resources. Besides, they increasingly demand also stable connection and seamless access to the network resources, by means of the enormous potential offered by the new wireless equipments and capabilities.
The combination of uncoordination and wireless access induces a degree of dynamism never experienced before, that must be necessarily faced by the emerging services and applications, and calls for a pressing solution of the resulting scientific and technological challenges. In such a highly elusive and mutable setting, the focus of the present project is that of evaluating the impact on the network performance induced by the combination of the lack of users cooperation/collaboration and the presence of users mobility/dynamism. To this respect, the general mismatch between the network optimization goals and the competing users private interests, motivates the following research directions:
1) modeling and analyzing the consequences of the autonomous users behaviour on the network performance;
2) accounting for specific features imposed by the dynamic nature of these networks (e.g., users mobility, wireless medium, unreliable connectivity, etc.);
3) investigating the influence of the different degrees of users social knowledge on users behaviour when analyzing items 1) and 2) above, and, consequently, on the system performance and on the induced mobility patterns and network topology; 4) evaluating the solutions developed in 1), 2), and 3) also through extensive simulations.
More in detail, we plan to face the above points as follows:
1) In the depicted scenario, useful tools and insights come from the integration of algorithmic ideas with techniques borrowed from Mathematical Economics and Game Theory. The two fundamental approaches adopted in this setting will be pursued in the project: i) resorting on concepts of equilibria to characterize solutions consistent with the presence of rational and selfish users that have limited or no capabilities of cooperating, and ii) designing pricing/incentive mechanisms enforcing users cooperation with the system, by resorting on tools coming from algorithmic mechanism design.
2) We will also take into account specific features of these emerging networks, e.g., user mobility and prominent wireless nature of communications. In particular, inspired by the new trend emerging in Network Theory, we will consider the challenging and almost-unexplored goal of providing a rigorous algorithmic approach to Opportunistic Networking, where node dynamism/mobility is considered a resource (rather than a hurdle) to be exploited in network optimization in response to weak/intermittent connectivity. We will also be concerned with other related issues, like energy saving when implementing given communication patterns and efficient spectrum utilization through interference confinement.
3) As it is often unrealistic to assume that a user of an uncoordinated pervasive network has a complete knowledge of the other users and of their strategies, another goal of this research project is that of evaluating the impact on the network performance of incomplete knowledge driven by the social relationships configuration.
Such configurations also reflect on the mobility patterns of the users, thus influencing also the network topology and connectivity. Therefore, in studying issues 1) and 2) described above, we will also borrow concepts from the theory of social networks. The combination of computational, game theoretical and social aspects approaches is then a key ingredient in facing this point.
4) Designing an accurate analytical framework able to capture at the same time the various network features such as mobility, wireless link unreliability, social relationships and so forth, is a typically difficult task. Thus, the algorithms/protocols developed in 1), 2), and 3) will be evaluated not only through theoretical/analytical performance estimation, but also through extensive simulations. We plan to carry out simulations both at a high-level, in order to understand general performance trends in very large (thousands of nodes) and heterogenous networks, and at a more refined level, in order to accurately estimate performances in medium sized networks (a few hundred of nodes). As a final outcome, the most significant algorithm/protocols and application scenarios will be packaged in a software tool (a "demonstrator") which will be made available to the research community.
The combination of uncoordination and wireless access induces a degree of dynamism never experienced before, that must be necessarily faced by the emerging services and applications, and calls for a pressing solution of the resulting scientific and technological challenges. In such a highly elusive and mutable setting, the focus of the present project is that of evaluating the impact on the network performance induced by the combination of the lack of users cooperation/collaboration and the presence of users mobility/dynamism. To this respect, the general mismatch between the network optimization goals and the competing users private interests, motivates the following research directions:
1) modeling and analyzing the consequences of the autonomous users behaviour on the network performance;
2) accounting for specific features imposed by the dynamic nature of these networks (e.g., users mobility, wireless medium, unreliable connectivity, etc.);
3) investigating the influence of the different degrees of users social knowledge on users behaviour when analyzing items 1) and 2) above, and, consequently, on the system performance and on the induced mobility patterns and network topology; 4) evaluating the solutions developed in 1), 2), and 3) also through extensive simulations.
More in detail, we plan to face the above points as follows:
1) In the depicted scenario, useful tools and insights come from the integration of algorithmic ideas with techniques borrowed from Mathematical Economics and Game Theory. The two fundamental approaches adopted in this setting will be pursued in the project: i) resorting on concepts of equilibria to characterize solutions consistent with the presence of rational and selfish users that have limited or no capabilities of cooperating, and ii) designing pricing/incentive mechanisms enforcing users cooperation with the system, by resorting on tools coming from algorithmic mechanism design.
2) We will also take into account specific features of these emerging networks, e.g., user mobility and prominent wireless nature of communications. In particular, inspired by the new trend emerging in Network Theory, we will consider the challenging and almost-unexplored goal of providing a rigorous algorithmic approach to Opportunistic Networking, where node dynamism/mobility is considered a resource (rather than a hurdle) to be exploited in network optimization in response to weak/intermittent connectivity. We will also be concerned with other related issues, like energy saving when implementing given communication patterns and efficient spectrum utilization through interference confinement.
3) As it is often unrealistic to assume that a user of an uncoordinated pervasive network has a complete knowledge of the other users and of their strategies, another goal of this research project is that of evaluating the impact on the network performance of incomplete knowledge driven by the social relationships configuration.
Such configurations also reflect on the mobility patterns of the users, thus influencing also the network topology and connectivity. Therefore, in studying issues 1) and 2) described above, we will also borrow concepts from the theory of social networks. The combination of computational, game theoretical and social aspects approaches is then a key ingredient in facing this point.
4) Designing an accurate analytical framework able to capture at the same time the various network features such as mobility, wireless link unreliability, social relationships and so forth, is a typically difficult task. Thus, the algorithms/protocols developed in 1), 2), and 3) will be evaluated not only through theoretical/analytical performance estimation, but also through extensive simulations. We plan to carry out simulations both at a high-level, in order to understand general performance trends in very large (thousands of nodes) and heterogenous networks, and at a more refined level, in order to accurately estimate performances in medium sized networks (a few hundred of nodes). As a final outcome, the most significant algorithm/protocols and application scenarios will be packaged in a software tool (a "demonstrator") which will be made available to the research community.