13 research outputs found
Stability of Skorokhod problem is undecidable
Skorokhod problem arises in studying Reflected Brownian Motion (RBM) on an
non-negative orthant, specifically in the context of queueing networks in the
heavy traffic regime. One of the key problems is identifying conditions for
stability of a Skorokhod problem, defined as the property that trajectories are
attracted to the origin. The stability conditions are known in dimension up to
three, but not for general dimensions.
In this paper we explain the fundamental difficulties encountered in trying
to establish stability conditions for general dimensions. We prove that
stability of Skorokhod problem is an undecidable property when the starting
state is a part of the input. Namely, there does not exist an algorithm (a
constructive procedure) for identifying stable Skorokhod problem in general
dimensions
System design of stochastic models using robustness of temporal properties
Stochastic models such as Continuous-Time Markov Chains (CTMC) and Stochastic Hybrid Automata (SHA) are powerful formalisms to model and to reason about the dynamics of biological systems, due to their ability to capture the stochasticity inherent in biological processes. A classical question in formal modelling with clear relevance to biological modelling is the model checking problem, i.e. calculate the probability that a behaviour, expressed for instance in terms of a certain temporal logic formula, may occur in a given stochastic process. However, one may not only be interested in the notion of satisfiability, but also in the capacity of a system to maintain a particular emergent behaviour unaffected by the perturbations, caused e.g. from extrinsic noise, or by possible small changes in the model parameters. To address this issue, researchers from the verification community have recently proposed several notions of robustness for temporal logic providing suitable definitions of distance between a trajectory of a (deterministic) dynamical system and the boundaries of the set of trajectories satisfying the property of interest. The contributions of this paper are twofold. First, we extend the notion of robustness to stochastic systems, showing that this naturally leads to a distribution of robustness degrees. By discussing three examples, we show how to approximate the distribution of the robustness degree and the average robustness. Secondly, we show how to exploit this notion to address the system design problem, where the goal is to optimise some control parameters of a stochastic model in order to maximise robustness of the desired specifications
Hybrid Behaviour of Markov Population Models
We investigate the behaviour of population models written in Stochastic
Concurrent Constraint Programming (sCCP), a stochastic extension of Concurrent
Constraint Programming. In particular, we focus on models from which we can
define a semantics of sCCP both in terms of Continuous Time Markov Chains
(CTMC) and in terms of Stochastic Hybrid Systems, in which some populations are
approximated continuously, while others are kept discrete. We will prove the
correctness of the hybrid semantics from the point of view of the limiting
behaviour of a sequence of models for increasing population size. More
specifically, we prove that, under suitable regularity conditions, the sequence
of CTMC constructed from sCCP programs for increasing population size converges
to the hybrid system constructed by means of the hybrid semantics. We
investigate in particular what happens for sCCP models in which some
transitions are guarded by boolean predicates or in the presence of
instantaneous transitions
Computer Aided Verification
This open access two-volume set LNCS 11561 and 11562 constitutes the refereed proceedings of the 31st International Conference on Computer Aided Verification, CAV 2019, held in New York City, USA, in July 2019. The 52 full papers presented together with 13 tool papers and 2 case studies, were carefully reviewed and selected from 258 submissions. The papers were organized in the following topical sections: Part I: automata and timed systems; security and hyperproperties; synthesis; model checking; cyber-physical systems and machine learning; probabilistic systems, runtime techniques; dynamical, hybrid, and reactive systems; Part II: logics, decision procedures; and solvers; numerical programs; verification; distributed systems and networks; verification and invariants; and concurrency
Collaborating queues: large service network and a limit order book
E-thesis pagination differs from hardbound copy kept in the Manuscripts Department, Cambridge University Library.We analyse the steady-state behaviour of two different models with collaborating queues: that is, models in which "customers" can be served by many types of "servers", and "servers" can process many types of "customers".
The first example is a large-scale service system, such as a call centre. Collaboration
is the result of cross-trained staff attending to several different types of incoming calls. We first examine a load-balancing policy, which aims to keep servers in different pools equally busy. Although the policy behaves order-optimally over fixed time horizons, we show that the steady-state distribution may fail to be tight on the diffusion scale. That is, in a family of ever-larger networks whose arrival rates grow as O(r) (where r is a scaling parameter growing to infinity), the sequence of steady-state deviations from equilibrium scaled down by sqrt(r) is not tight. We then propose a different policy, for which we show that the sequence of invariant distributions is tight on the r^(1/2+epsilon) scale, for any epsilon > 0. For this policy we conjecture that tightness holds on the diffusion scale as well.
The second example models a limit order book, a pricing mechanism for a single-commodity market in which buyers (respectively sellers) are prepared to wait for the price to drop (respectively rise). We analyse the behaviour of a simplified model, in which the arrival events are independent of each other and the state of the limit order book. The system can be represented by a queueing model, with "customers" and "servers" corresponding to bids and asks; the roles of customers and servers are symmetric. We show that, with probability 1, the price interval breaks up into three regions. At small (respectively large) prices, only finitely many bid (respectively ask) orders ever get fulfilled, while in the middle region all orders eventually clear. We derive equations which define the boundaries between these regions, and solve them explicitly in the case of iid uniform arrivals to obtain numeric values of the thresholds. We derive a heuristic for the distribution of the highest bid (respectively lowest ask), and present simulation data confirming it.This work was supported by the US National Science Foundation Graduate Research Fellowship
A Markov Model of a Limit Order Book: Thresholds, Recurrence, and Trading Strategies
We analyze a tractable model of a limit order book on short time scales, where the dynamics are driven by stochastic fluctuations between supply and demand. We establish the existence of a limiting distribution for the highest bid, and for the lowest ask, where the limiting distributions are confined between two thresholds. We make extensive use of fluid limits to establish recurrence properties of the model. We use the model to analyze various high-frequency trading strategies, and comment on the Nash equilibria that emerge between high-frequency traders when a market in continuous time is replaced by frequent batch auctions.The second author’s research was partially supported by the National Science Foundation [Grant DMS-1204311] and NSF Graduate Research Fellowship
Tools and Algorithms for the Construction and Analysis of Systems
This open access book constitutes the proceedings of the 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2022, which was held during April 2-7, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022. The 46 full papers and 4 short papers presented in this volume were carefully reviewed and selected from 159 submissions. The proceedings also contain 16 tool papers of the affiliated competition SV-Comp and 1 paper consisting of the competition report. TACAS is a forum for researchers, developers, and users interested in rigorously based tools and algorithms for the construction and analysis of systems. The conference aims to bridge the gaps between different communities with this common interest and to support them in their quest to improve the utility, reliability, exibility, and efficiency of tools and algorithms for building computer-controlled systems