Laszlo Toka

Online Data Backup: A Peer-Assisted Approach

In this work we study the benefits of a peer- assisted approach to online backup applications, in which spare bandwidth and storage space of end- hosts complement that of an online storage service. Via simulations, we analyze the interplay between two key aspects of such applications: data placement and bandwidth allocation. Our analysis focuses on metrics such as the time required to complete a backup and a restore operation, as well as the storage costs. We show that, by using adequate bandwidth allocation policies in which storage space at a cloud provider can be used temporarily, hybrid systems can achieve performance comparable to traditional client-server architectures at a fraction of the costs. Moreover, we explore the impact of mechanisms to impose fairness and conclude that a peer-assisted approach does not discriminate peers in terms of performance, but associates a storage cost to peers contributing with little resources.

Managing a Peer-to-Peer Data Storage System in a Selfish Society

We compare two possible mechanisms to manage a peer-to-peer storage system, where participants can store data online on the disks of peers in order to increase data availability and accessibility. Due to the lack of incentives for peers to contribute to the service, we suggest that either each peers use of the service be limited to her contribution level (symmetric schemes), or that storage space be bought from and sold to peers by a system operator that seeks to maximize profit. Using a noncooperative game model to take into account user selfishness, we study those mechanisms with respect to the social welfare performance measure, and give necessary and sufficient conditions for one scheme to socially outperform the other.

On incentives in global wireless communities

The wireless community networking paradigm shows great promise in achieving a global status. However, both user participation and support from traditional Internet Service Providers (ISPs) play key roles in creating worldwide coverage; for this end a viable incentive system is essential. In this paper we study the economic interactions between users, ISPs and community providers. Our main contribution is threefold. First, we propose a model of the global wireless community concept as a Stackelberg game of two levels and construct the respective payoff functions of each player. Second, we show how both users and ISPs may fail to join the community in equilibrium. Third, we explore the parameter space of the mechanism designer and show how the technology diffusion process and expected payoffs can be controlled by adjusting roaming prices and revenue shares.

Data transfer scheduling for P2P storage

In Peer-to-Peer storage and backup applications, large amounts of data have to be transferred between nodes. In general, recipient of data transfers are not chosen randomly from the whole set of nodes in the Peer-to-Peer networks, but they are chosen according to peer selection rules imposing several criteria, such as resource contributions, position in DHTs, or trust between nodes. Imposing too stringent restrictions on the choice of nodes that are eligible to receive data can have a negative impact on the amount of time needed to complete data transfer, and scheduling choices influence this result as well. We formalize the problem of data transfer scheduling, and devise means for calculating (knowing a posteriori the availability patterns of nodes) optimal scheduling choices; we then propose and evaluate realistic scheduling policies, and evaluate their overheads in transfer times with respect to the optimal. We show that allowing even a small flexibility in choosing nodes after the peer selection step results in large improvements on time to complete transfers, and that even simple informed scheduling policies can significantly reduce transfer time overhead.

Analysis of user-driven peer selection in peer-to-peer backup and storage systems

In this paper we present a realistic model of peer-to-peer backup and storage systems in which users have the ability to selfishly select remote peers they want to exchange data with. In our work, peer characteristics (e.g., on-line availability, dedicated bandwidth) play an important role and are reflected in the model through a single parameter, termed profile. We show that selecting remote peers selfishly, based on their profiles, creates incentives for users to improve their contribution to the system. Our work is based on an extension to the Matching Theory that allows us to formulate a novel game, termed the stable exchange game, in which we shift the algorithmic nature of matching problems to a game theoretic framework. We propose a polynomial-time algorithm to compute (optimal) stable exchanges between peers and show, using an evolutionary game theoretic framework, that even semi-random peer selection strategies, that are easily implementable in practice, can be effective in providing incentives to users in order to improve their profiles.

Managing a peer-to-peer backup system: does imposed fairness socially outperform a revenue-driven monopoly?

We study a peer-to-peer backup system, where users offer some of their storage space to provide service for the others. The economic model for such a system is different from the ones applicable to peer-to-peer file sharing systems, since the storage capacity is a private good here. We study two mechanisms aimed at incentivizing users to offer some of their capacity: a price-based scheme (here a revenue-driven monopoly) and a more classical symmetric scheme (imposing users to contribute to the service at least as much as use it). We compare the outcomes of such mechanisms to the socially optimal situation that could be attained if users were not selfish, and show that depending on user heterogeneity, a revenue maximizing monopoly can be a worse or a better (in terms of social welfare) way to manage the system than a symmetric scheme.

General distributed economic framework for dynamic spectrum allocation

The emergence of novel radio techniques enables the application of advantageous revolutionary spectrum policies. An important body of research has appeared about possible frequency management schemes, but none of them proposes solutions that meet every related criteria. In this paper we present our work on dynamic spectrum allocation and pricing that offers a distributed mechanism design, well-suited to practical employment issues. Our model handles interference effects without any restricting assumptions, provides universal scalable and incentive-compatible allocation and pricing mechanisms. We provide both analytical and numerical evaluation of the proposed framework, and in either case we prove this latter to be a suitable approach to efficient and flexible spectrum utilization.

Redundancy management for P2P backup

We propose a redundancy management mechanism for peer-to-peer backup applications. Since, in a backup system, data is read over the network only during restore processes caused by data loss, redundancy management targets data durability rather than attempting to make each piece of information availabile at any time. Each peer determines, in an on-line manner, an amount of redundancy sufficient to counter the effects of peer deaths, while preserving acceptable data restore times. Our experiments, based on trace-driven simulations, indicate that our mechanism can reduce the redundancy by a factor between two and three with respect to redundancy policies aiming for data availability. These results imply an according increase in storage capacity and decrease in time to complete backups, at the expense of longer times required to restore data.We believe this is a very reasonable price to pay, given the nature of the application.

On Distributed Dynamic Spectrum Allocation for Sequential Arrivals

We study the potential of a dynamic spectrum management framework that enables sequential allocation of frequency bands for wireless service providers. We present our distributed system design on allocation and pricing with the goal of achieving efficient spectrum utilization, flexible allocations and incentive-compatibility, considering physical interference model among frequency licensees. Our work provides insights on the emerging optimization problems related to the allocation. We show the analytic results that give ideas for well-established heuristics to these problems. We evaluate the proposed framework and algorithms numerically, and we arrive at the conclusion, that even by the simple proposed heuristics the system performs well, thus it is a suitable approach to a flexible distributed dynamic allocation framework.

A dynamic exchange game

Our work aims to study a game based on an extended variant of the stable fixtures problem where multiple matches can be established between pairs of players, moreover preference orders are subject to alteration due to player strategies.