Hybrid performance modelling of opportunistic networks

We demonstrate the modelling of opportunistic networks using the process algebra stochastic HYPE. Network traffic is modelled as continuous flows, contact between nodes in the network is modelled stochastically, and instantaneous decisions are modelled as discrete events. Our model describes a network of stationary video sensors with a mobile ferry which collects data from the sensors and delivers it to the base station. We consider different mobility models and different buffer sizes for the ferries. This case study illustrates the flexibility and expressive power of stochastic HYPE. We also discuss the software that enables us to describe stochastic HYPE models and simulate them.Comment: In Proceedings QAPL 2012, arXiv:1207.055

An efficient hybrid model and dynamic performance analysis for multihop wireless networks

Multihop wireless networks can be subjected to nonstationary phenomena due to a dynamic network topology and time varying traffic. However, the simulation techniques used to study multihop wireless networks focus on the steady-state performance even though transient or nonstationary periods will often occur. Moreover, the majority of the simulators suffer from poor scalability. In this paper, we develop an efficient performance modeling technique for analyzing the time varying queueing behavior of multihop wireless networks. The one-hop packet transmission (service) time is assumed to be deterministic, which could be achieved by contention-free transmission, or approximated in sparse or lightly loaded multihop wireless networks. Our model is a hybrid of time varying adjacency matrix and fluid flow based differential equations, which represent dynamic topology changes and nonstationary network queues, respectively. Numerical experiments show that the hybrid fluid based model can provide reasonably accurate results much more efficiently than standard simulators. Also an example application of the modeling technique is given showing the nonstationary network performance as a function of node mobility, traffic load and wireless link quality. © 2013 IEEE

Fluctuating hydrodynamic modelling of fluids at the nanoscale

A good representation of mesoscopic fluids is required to combine with molecular simulations at larger length and time scales (De Fabritiis {\it et. al}, Phys. Rev. Lett. 97, 134501 (2006)). However, accurate computational models of the hydrodynamics of nanoscale molecular assemblies are lacking, at least in part because of the stochastic character of the underlying fluctuating hydrodynamic equations. Here we derive a finite volume discretization of the compressible isothermal fluctuating hydrodynamic equations over a regular grid in the Eulerian reference system. We apply it to fluids such as argon at arbitrary densities and water under ambient conditions. To that end, molecular dynamics simulations are used to derive the required fluid properties. The equilibrium state of the model is shown to be thermodynamically consistent and correctly reproduces linear hydrodynamics including relaxation of sound and shear modes. We also consider non-equilibrium states involving diffusion and convection in cavities with no-slip boundary conditions

Collaborative Verification-Driven Engineering of Hybrid Systems

Hybrid systems with both discrete and continuous dynamics are an important model for real-world cyber-physical systems. The key challenge is to ensure their correct functioning w.r.t. safety requirements. Promising techniques to ensure safety seem to be model-driven engineering to develop hybrid systems in a well-defined and traceable manner, and formal verification to prove their correctness. Their combination forms the vision of verification-driven engineering. Often, hybrid systems are rather complex in that they require expertise from many domains (e.g., robotics, control systems, computer science, software engineering, and mechanical engineering). Moreover, despite the remarkable progress in automating formal verification of hybrid systems, the construction of proofs of complex systems often requires nontrivial human guidance, since hybrid systems verification tools solve undecidable problems. It is, thus, not uncommon for development and verification teams to consist of many players with diverse expertise. This paper introduces a verification-driven engineering toolset that extends our previous work on hybrid and arithmetic verification with tools for (i) graphical (UML) and textual modeling of hybrid systems, (ii) exchanging and comparing models and proofs, and (iii) managing verification tasks. This toolset makes it easier to tackle large-scale verification tasks

Eradication-resolution dynamics with stochastic flare-ups

In infectious disease as well as in cancer, the ultimate outcome of the curative response, mediated by the body itself or through drug treatment, is either successful eradication or a resurgence of the disease (“flare-up” or “relapse”), depending on random fluctuations that dominate the dynamics of the system when the number of diseased cells has become very low. The presence of a low-numbers bottle-neck in the dynamics, which is unavoidable if eradication is to take place at all, renders at least one phase of the dynamics essentially stochastic. However, the eradicating agents (e.g. immune cells, drug molecules) generally remain at high numbers during the critical bottle-neck phase, sufficiently so to warrant a deterministic treatment. This leads us to consider a hybrid stochastic-deterministic approach where the infected cells are treated stochastically whereas the eradicating agents are treated deterministically. Exploiting the fact that the number of eradicating agents typically decreases monotonically during the resolution phase of the response, we derive a set of coupled first-order differential equations that describe the probability of ultimate eradication as a function of the system's state, and we consider a number of biomedical applications

A time dependent performance model for multihop wireless networks with CBR traffic

In this paper, we develop a performance modeling technique for analyzing the time varying network layer queueing behavior of multihop wireless networks with constant bit rate traffic. Our approach is a hybrid of fluid flow queueing modeling and a time varying connectivity matrix. Network queues are modeled using fluid-flow based differential equation models which are solved using numerical methods, while node mobility is modeled using deterministic or stochastic modeling of adjacency matrix elements. Numerical and simulation experiments show that the new approach can provide reasonably accurate results with significant improvements in the computation time compared to standard simulation tools. © 2010 IEEE