Inspection games for selfish network environments

Current distributed information system consider only typical fault-tolerance techniques for re-liability issues. Selfish peers, which deviate from the collaborative protocol to increase personal benefit, may also harmfully affect the goals of networked architectures. Securing the collaborative protocol would be an option, however, this may not be always possible or wanted. Then, a post-hoc assessment, deployed by the system designer, could monitor the correct behaviour of the participants without affecting the actual system\u2019s functioning. Due to limited resources, a complete monitoring is not possible: typically monitoring is done by sampling by sampling so that misbehaviour in some case can go undetected. At the same time, a selfish peer\u2019s decision to violate also depends also on the monitoring rate of the inspecting parties. This forms an interdependent interaction landscape, which corresponds to a class of games known as Inspection Games. In this paper, we discuss the practicability of Inspection Games for networked architectures for system analysis and design. To this end, develop generalized Inspection Game versions up to m inspectors and n inspectees, starting from a simple two-player game; we further provide solutions (i.e. Nash equilibria) for all games. Afterwards, these games and solutions are adapted towards an application to networked architectures. This is done by extending them to the possibility of false negatives (the performed inspection on a player\u2019s behaviour does not detect a deviation from the protocol which has actually occurred, due to the intrinsic failability of the inspection technique)

A delay and cost balancing protocol for message routing in mobile delay tolerant networks

The increasing pervasiveness of mobile devices with networking capabilities has led to the emergence of Mobile Delay Tolerant Networks (MDTNs). The characteristics of MDTNs, which include frequent and long-term partitions, make message routing a major challenge in these networks. Most of the existing routing protocols either allocate an unlimited number of message copies or use a xed number of message copies to route a message towards its destination. While the first approach unnecessarily oods the network, the rigidity of the second approach makes it ine cient from the viewpoint of message replication. Hence, the question that we address in this paper is: "How to dynamically allocate message copies in order to strike a balance between the delay and cost of message delivery?". We present a novel adaptive multi-step routing protocol for MDTNs. In each routing step, our protocol reasons on the remaining time-tolive of the message in order to allocate the minimum number of copies necessary to achieve a given delivery probability. Experiment results demonstrate that our protocol has a higher delivery ratio and a lower delivery cost compared to the state-of-the-art Spray-and-Wait and Bubble protocols

Virtual prototyping of floating point units

International audienceVirtual prototyping is a key technology for design space exploration, design verification, code development and testing of new systems on chip. For processors, either general purpose, multi and manycore or GPUs, the availability of powerful floating point units has now become mandatory in a lot of markets. However, implementing a fast and accurate floating point unit virtual prototype is not easy, even if host and target processors are IEEE 754 compliant. The goal of this paper is not to propose a definitive solution to this problem, but to draw the attention of the virtual prototyping community to it. To that aim, we study two solutions that form a compromise between speed of virtual prototype execution and computation accuracy

RACOON++: A Semi-Automatic Framework for the Selfishness-aware Design of Cooperative Systems

Challenge in designing cooperative distributed systems is to develop feasible and cost-effective mechanisms to foster cooperation among selfish nodes, i.e., nodes that strategically deviate from the intended specification to increase their individual utility. Finding a satisfactory solution to this challenge may be complicated by the intrinsic characteristics of each system, as well as by the particular objectives set by the system designer. Our previous work addressed this challenge by proposing RACOON, a general and semi-automatic framework for designing selfishness-resilient cooperative systems. RACOON relies on classical game theory and a custom built simulator to predict the impact of a fixed set of selfish behaviours on the designer\u2019s objectives. In this paper, we present RACOON++, which extends the previous framework with a declarative model for defining the utility function and the static behaviour of selfish nodes, along with a new model for reasoning on the dynamic interactions of nodes, based on evolutionary game theory. We illustrate the benefits of using RACOON++ by designing three cooperative systems: a peer-to-peer live streaming system, a load balancing protocol, and an anonymous communication system. Extensive experimental results using the state-of-the-art PeerSim simulator verify that the systems designed using RACOON++ achieve both selfishness-resilience and high performance

Many-player inspection games in networked environments

In communication architectures, nodes are expected to spend their own resources so as to relay other nodes' messages or perform other services for the common good. However any selfish node, if given the opportunity, would typically prefer \u2014 to spare its own resources \u2014 to avoid serving the other nodes. This creates a potential problem to any collaborative protocol. A possible approach towards this issue consists in performing audits on the actions of the individual nodes, and applying some form of sanction to those whose misbehaviour has been detected during an inspection. However typically, auditing is costly and due to limited resources it can be carried on only on a sampling basis. It is clear that the rate of inspection has to be adapted to the rate of misbehavior, so as to strike a balance, from the point of view of the inspector, between the audit costs and the avoided damage to the system. Since the misbehaviour rate of rational agents is not predefined or fixed, but in turn depends from inspection rate, the overall behavior of the system made by inspectors and inspectees fits into a typical interdependent interaction landscape and can be modeled using Game Theory. The above described audit situation corresponds to a class of games known as Inspection Games. In this paper, we model several versions of Inspection Games (IGs), up to the most general case involving m inspectors and n inspectees. We resolve each game by computing the strategy that rational players would follow. Moreover, we also extend the IG model by taking into account the possibility of undetected violations, i.e. false negatives in the inspections

Managing a pool of rules for credit card fraud detection by a Game Theory based approach

In the automatic credit card transaction classification there are two phases: in the Real-Time (RT) phase the system decides quickly, based on the bare transaction information, whether to authorize the transaction; in the subsequent Near-Real-Time (NRT) phase, the system enacts a slower ex-post evaluation, based on a larger information context. The classification rules in the NRT phase trigger alerts on suspicious transactions, which are transferred to human investigators for final assessment. The management criteria used to select the rules, to be kept operational in the NRT pool, are traditionally based mostly on the performance of individual rules, considered in isolation; this approach disregards the non-additivity of the rules (aggregating rules with high individual precision does not necessarily make a high-precision pool). In this work, we propose to apply, to the rule selection for the NRT phase, an approach which assigns a normalized score to the individual rule, quantifying the rule influence on the overall performance of the pool. As a score we propose to use a power-index developed within Coalitional Game Theory, the Shapley Value (SV), summarizing the performance in collaboration. Such score has two main applications: (1) it can be used, within the periodic rule assessment process, to support the decision of whether to keep or drop the rule from the pool; (2) it can be used to select the top-ranked rules, so as to work with a more compact ruleset. Using real-world credit card fraud data containing approximately 300 rules and 10^5 transactions records, we show that: (1) this score fares better \u2013 in granting the performance of the pool \u2013 than the one assessing the rules in isolation; (2) that the same performance of the whole pool can be achieved keeping only one-tenth of the rules \u2013 the top-k SV-ranked rules. We observe that the latter application can be reframed in terms of Feature Selection (FS) task for a classifier: we show that our approach is comparable w.r.t benchmark FS algorithms, but argue that it presents an advantage for the management, consisting in the assignment of a normalized score to the individual rule. This is not the case for most FS algorithms, which only focus on yielding a high-performance feature-set solution

A framework for the design configuration of accountable selfish-resilient peer-to-peer systems

A challenge in designing a peer-To-peer (P2P) system is to ensure that the system is able to tolerate selfish nodes that strategically deviate from their specification whenever doing so is convenient. In this paper, we propose RACOON, a framework for the design of P2P systems that are resilient to selfish behaviours. While most existing solutions target specific systems or types of selfishness, RACOON proposes a generic and semi-Automatic approach that achieves robust and reusable results. Also, RACOON supports the system designer in the performance-oriented tuning of the system, by proposing a novel approach that combines Game Theory and simulations. We illustrate the benefits of using RACOON by designing two P2P systems: A live streaming and an anonymous communication system. In simulations and a real deployment of the two applications on a testbed comprising 100 nodes, the systems designed using RACOON achieve both resilience to selfish nodes and high performance