Distributed Programming of Smart Systems with Event-Condition-Action Rules

In recent years, event-driven programming languages, e.g. those based on Event Condition Action (ECA) rules, have emerged as a promising paradigm for implementing smart systems, such as IoT devices. Still, actual implementations are bound to a centralized infrastructure, limiting scalability and security. In this work, we present attribute-based memory updates (AbU), a new interaction mechanism aiming to extend the ECA programming paradigm to distributed systems. It relies on attribute-based communication, that is similar to broadcast, but receivers are selected “on the fly” by means of predicates over their attributes. With AbU, smart devices can be easily programmed via ECA rules and, at the same time, they can be deployed to a distributed network. Hence, a centralized infrastructure is not needed anymore: the computation is moved on the edge, improving reliability, scalability, privacy and security

Behavioral equivalences for AbU: Verifying security and safety in distributed IoT systems

Attribute-based memory Updates ([Formula presented]in short) is an interaction mechanism recently introduced for adapting the Event-Condition-Action (ECA) programming paradigm to distributed reactive systems, such as autonomic and smart IoT device ensembles. In this model, an event (e.g., an input from a sensor, or a device state update) can trigger an ECA rule, whose execution can cause the state update of (possibly) many remote devices at once; the latter are selected “on the fly” by means of predicates over their state, without the need of a central coordinating entity. However, the combination of different [Formula presented]systems may yield unexpected interactions, e.g., when a new device is added to an existing secure system, potentially hindering the security of the whole ensemble of devices. This can be critical in the IoT, where smart devices are more and more pervasive in our daily life. In this paper, we consider the problem of ensuring security and safety requirements for [Formula presented]systems (and, in turn, for IoT devices). The first are a form of noninterference, as they correspond to avoid forbidden information flows (e.g., information flows violating confidentiality); while the second are a form of non-interaction, as they correspond to avoid unintended executions (e.g., leading to erroneous/unsafe states). In order to formally model these requirements, we introduce suitable behavioral equivalences for [Formula presented]. These equivalences are generalizations of hiding bisimilarity, i.e., a kind of weak bisimilarity where we can compare systems up to actions at different levels of security. Leveraging these behavioral equivalences, we propose (syntactic) sufficient conditions guaranteeing the requirements and, then, effective algorithms for statically verifying such conditions

Higher order corrections of the extended Chaplygin gas cosmology with varying GG and Λ\Lambda

In this paper, we study two different models of dark energy based on Chaplygin gas equation of state. The first model is the variable modified Chaplygin gas while the second one is the extended Chaplygin gas. Both models are considered in the framework of higher order $f(R)$ modified gravity. We also consider the case of time varying gravitational constant $G$ and $\Lambda$ for both models. We investigate some cosmological parameters such as the Hubble, the deceleration and the equation of state parameters. Then we showed that the model that we considered, extended Chaplygin gas with time-dependent $G$ and $\Lambda$, is consistent with the observational data. Finally we conclude with the discussion of cosmological perturbations of our model.Comment: Perturbation analysis added, typos corrected, references adde

The AbU Language: IoT Distributed Programming Made Easy

Event-driven programming based on Event-Condition-Action (ECA) rules allows users to define complex automation routines in a simple, declarative way; for this reason, in recent years ECA rules have been adopted by the majority of companies in the Internet of Things (IoT) industry as a promising paradigm for implementing ubiquitous and pervasive systems. Unfortunately, programming simplicity comes to a price: most implementations of ECA rules are bound to a strongly centralized communication infrastructure, that poses serious limitations on the application scenarios for the IoT, due to scalability, security and availability issues. To mitigate these issues, recent works introduced abstractions for communication and coordination of ensembles of IoT devices in a decentralized setting, effectively moving the computation towards the edge of the network without sacrificing the programming simplicity prerogative of ECA rules. In particular, Attribute-based memory Updates is a communication model transparently enhancing ECA rules-based systems with an interaction mechanism where communication is similar to broadcast but actual receivers are selected on the spot, by means of predicates (i.e., properties) over devices attributes. In this paper, we introduce AbU-dsl, a Domain Specific Language for the IoT that compiles on top of an implementation of Attribute-based memory Updates. In this way, AbU-dsl provides a practical development interface, based on ECA rules, to effectively program IoT devices in a fully decentralized setting, by exploiting a full-fledged attribute-based interaction model. Thus, programmers can specify interactions between devices in a declarative way, abstracting from details such as devices identity, number, or even their existence, without the need for a central controlling service

Bacterial growth dynamics and PKPD relationships of rifampicin and bedaquiline in BALB/c mice

Background and Purpose: Translational efforts in the evaluation of novel anti-tubercular drugs demand better integration of pharmacokinetic–pharmacodynamic data arising from preclinical protocols. However, parametric approaches that discriminate drug effect from the underlying bacterial growth dynamics have not been fully explored, making it difficult to translate and/or extrapolate preclinical findings to humans. This analysis aims to develop a drug-disease model that allows distinction between drug- and system-specific properties. Experimental Approach: Given their clinical relevance, rifampicin and bedaquiline were used as test compounds. A two-state model was used to describe bacterial growth dynamics. The approach assumes the existence of fast- and slow-growing bacterial populations. Drug effect on the growth dynamics of each subpopulation was characterised in terms of potency (EC50-F and EC50-S) and maximum killing rate. Key Results: The doubling time of the fast- and slow-growing population was estimated to be 25 h and 42 days, respectively. Rifampicin was more potent against the fast-growing (EC50-F = 4.8 mg·L−1), as compared with the slow-growing population (EC50-S = 60.2 mg·L−1). Bedaquiline showed higher potency than rifampicin (EC50-F = 0.19 mg·L−1; EC50-S = 3.04 mg·L−1). External validation procedures revealed an effect of infection route on the apparent potency of rifampicin. Conclusion and Implications: Model parameter estimates suggest that nearly maximum killing rate is achieved against fast-growing, but not against slow-growing populations at the tested doses. Evidence of differences in drug potency for each subpopulation may facilitate the translation of preclinical findings and improve the dose rationale for anti-tubercular drugs in humans