Model Checking Probabilistic Pushdown Automata

We consider the model checking problem for probabilistic pushdown automata (pPDA) and properties expressible in various probabilistic logics. We start with properties that can be formulated as instances of a generalized random walk problem. We prove that both qualitative and quantitative model checking for this class of properties and pPDA is decidable. Then we show that model checking for the qualitative fragment of the logic PCTL and pPDA is also decidable. Moreover, we develop an error-tolerant model checking algorithm for PCTL and the subclass of stateless pPDA. Finally, we consider the class of omega-regular properties and show that both qualitative and quantitative model checking for pPDA is decidable

Information Asymmetry Models in the Internet Connectivity Market

This paper discusses the structure of the Internet connectivity market by focusing on the business relations of stakeholders involved in network services provision. We believe that the role of information asymmetry is critical when considering interconnection agreements, and should be taken into account in the structure of the contract. Information asymmetry due to incomplete information concerning important operating parameters such as network load, capacity, cost, gives rise to adverse selection during negotiation and contract preparation. The current at structure of interconnection agreements does not address such information asymmetries. In many cases, the dfficulty of observing the actual effort allocated by the contracted network for providing quality of service, and in particular, the absence of appropriate incentives in the contract, allows for the possibility of opportunistic behaviour in the form of moral hazard. We formulate two simple analytical models which demonstrate the effects of moral hazard in the market for network transport services. The first deals with the case where the network is contracted for short duration transport where the customer can not use the statistical information obtained during the life time of the service to determine with certainty the actual effort allocated by the network. The second model deals with transit contracts of longer duration, where the actual cost for provisioning the service at various quality levels is only statistically known at the time the contract is set up. Although these models are too simple for capturing the complexity of interconnection agreements between ISPs, they demonstrate the bad effects of information asymmetry and motivate the importance of incentive contracts for improving efficiency.interconnection moral hazard incentives

Efficient computation of exact solutions for quantitative model checking

Quantitative model checkers for Markov Decision Processes typically use finite-precision arithmetic. If all the coefficients in the process are rational numbers, then the model checking results are rational, and so they can be computed exactly. However, exact techniques are generally too expensive or limited in scalability. In this paper we propose a method for obtaining exact results starting from an approximated solution in finite-precision arithmetic. The input of the method is a description of a scheduler, which can be obtained by a model checker using finite precision. Given a scheduler, we show how to obtain a corresponding basis in a linear-programming problem, in such a way that the basis is optimal whenever the scheduler attains the worst-case probability. This correspondence is already known for discounted MDPs, we show how to apply it in the undiscounted case provided that some preprocessing is done. Using the correspondence, the linear-programming problem can be solved in exact arithmetic starting from the basis obtained. As a consequence, the method finds the worst-case probability even if the scheduler provided by the model checker was not optimal. In our experiments, the calculation of exact solutions from a candidate scheduler is significantly faster than the calculation using the simplex method under exact arithmetic starting from a default basis.Comment: In Proceedings QAPL 2012, arXiv:1207.055

Decision Problems for Nash Equilibria in Stochastic Games

We analyse the computational complexity of finding Nash equilibria in stochastic multiplayer games with $\omega$-regular objectives. While the existence of an equilibrium whose payoff falls into a certain interval may be undecidable, we single out several decidable restrictions of the problem. First, restricting the search space to stationary, or pure stationary, equilibria results in problems that are typically contained in PSPACE and NP, respectively. Second, we show that the existence of an equilibrium with a binary payoff (i.e. an equilibrium where each player either wins or loses with probability 1) is decidable. We also establish that the existence of a Nash equilibrium with a certain binary payoff entails the existence of an equilibrium with the same payoff in pure, finite-state strategies.Comment: 22 pages, revised versio

Memory Efficient Algorithms for the Verification of Temporal Properties

peer reviewedaudience: researcherThis paper addresses the problem of designing memory-efficient algorithms for the verification of temporal properties of finite-state programs. Both the programs and their desired temporal properties are modeled as automata on infinite words (Büchi automata). Verification is then reduced to checking the emptiness of the automaton resulting from the product of the program and the property. This problem is usually solved by computing the strongly connected components of the graph representing the product automaton. Here, we present algorithms which solve the emptiness problem without explicitly constructing the strongly connected components of the product graph. By allowing the algorithms to err with some probability, we can implement them with a randomly accessed memory of size O(n) bits, where n is the number of states of the graph, instead of O(n log n) bits that the presently known algorithms require