Constraint Programming as a Means to Manage Configurations in Self-Adaptive Systems

International audienceIn recent years, new software architectures have been developed in which components can be bound and unbound dynamically as the context demands. This capacity to dynamically adapt the software's structure, behaviour and quality of service should make resilience easier to achieve by allowing systems to respond more flexibly to changing environmental contexts. However, because the decision of how to react to a new context is devolved to a run-time decision-making element that senses the context and selects an appropriate component configuration, a new approach to how software is specified is needed. A self-adaptive system that uses architectural adaptation may be conceptualized as a dynamic SPL. In this paper we argue that the problem of specifying a DSPL can be reduced to a constraint satisfaction problem. We combine goal modeling techniques with constraint programming to provide the analyst with a means to identify the system variants best suited to the various environmental contexts that a system might encounter at runtime. We illustrate our approach using the example of a self-adaptive wireless sensor network

Healthy reviews!- Online physician ratings reduce healthcare interruptions

We show that review platforms reduce healthcare interruptions for patients looking for a new physician. We employ a difference-in-differences strategy using physician retirements as a “disruptive shock” that forces patients to find a new physician. We combine insurance claims data with web-scraped physician reviews and highlight a substantial care-gap resulting from a physician’s retirement. We then show that online physician reviews reduce this gap and help patients find a new physician faster. Our results are robust to including a variety of controls and various instruments for the availability of physician reviews, but are not found for patients of nonretiring physicians. By reducing interruptions in care, reviews can improve clinical outcomes and lower costs

Hitch Hiker 2.0: a binding model with flexible data aggregation for the Internet-of-Things

Wireless communication plays a critical role in determining the lifetime of Internet-of-Things (IoT) systems. Data aggregation approaches have been widely used to enhance the performance of IoT applications. Such approaches reduce the number of packets that are transmitted by combining multiple packets into one transmission unit, thereby minimising energy consumption, collisions and congestion. However, current data aggregation schemes restrict developers to a specific network structure or cannot handle multi-hop data aggregation. In this paper, we propose Hitch Hiker 2.0, a component binding model that provides support for multi-hop data aggregation. Hitch Hiker uses component meta-data to discover remote component bindings and to construct a multi-hop overlay network within the free payload space of existing traffic flows. Hitch Hiker 2.0 provides end-to-end routing of low-priority traffic while using only a small fraction of the energy of standard communication. This paper extends upon our previous work by incorporating new mechanisms for decentralised route discovery and providing additional application case studies and evaluation. We have developed a prototype implementation of Hitch Hiker for the LooCI component model. Our evaluation shows that Hitch Hiker consumes minimal resources and that using Hitch Hiker to deliver low-priority traffic reduces energy consumption by up to 32 %

URLink: Using Names As Sole Internet Addresses to Tackle Scanning Attacks in IoT

peer reviewedThe Internet adopts a layered architecture where IP addresses are used to identify endpoints and port numbers serves as application multiplexers over a single host. Nowadays, names are usually used to expose a service to public access. However, even with the current DNS architecture, nodes must still know what the running host’s IP address and service’s port number are to access the service. In fact, any node can directly contact a publicly available node, sometimes for other purposes than accessing its public services. This is specially a challenge in IoT as highlighted by numerous high-profile DDoS attacks which leverage Internet scanning to find vulnerable IoT nodes. Defending against this is often a challenge for service operators. This paper questions this current architecture and calls for an alternative called URLink, where names are used as the sole identifier and access door towards a service. Through a new network abstraction called URLSocket, clients are no longer aware of the public service’s IP address and port number. We argue that such an approach is beneficial for IoT networks, as it can be used to address various security and privacy issues in these network. While such an architecture calls for changes in the client application stacks, existing applications (e.g. those running on an IoT node) can still leverage the proposed system in the current Internet

Prior human polyomavirus and papillomavirus infection and incident lung cancer: a nested case–control study

Purpose—To test whether infection with select human polyomaviruses (HPyV) and human papillomaviruses (HPV) is associated with incident lung cancer. Methods—We performed a nested case-control study, testing serum from the Carotene and Retinol Efficacy Trial CARET), conducted 1985–2005, for antibodies to Merkel cell (MCV), KI (KIV), and WU (WUV) HPyVs as well as to six high-risk and two low-risk HPV types. Incident lung cancer cases (n=200) were frequency-matched with controls (n=200) on age, enrollment and blood draw dates, intervention arm assignment, and the number of serum freeze / thaw cycles. Sera were tested using multiplex liquid bead microarray antibody assays. We used logistic regression to assess the association between HPyV and HPV antibodies and lung cancer. Results—There was no evidence of a positive association between levels of MCV, KIV, or WUV antibodies and incident lung cancer (P-corrected>0.10 for all trend tests; odds ratio (OR) range 0.72 to 1.09, P-corrected>0.10 for all). There was also no evidence for a positive association between HPV 16 or 18 infection and incident lung cancer (P-corrected≥0.10 for all trend tests; OR range 0.25 to 2.54, P>0.05 for all OR>1), but the number of persons with serologic evidence of these infections was small. Conclusions—Prior infection with any of several types of HPyV or HPV was not associated with subsequent diagnosis of lung cancer. Infection with these viruses likely does not influence a person’s risk of lung cancer in Western smoking populations

ConvDTW-ACS: Audio Segmentation for Track Type Detection During Car Manufacturing

This paper proposes a method for Acoustic Constrained Segmentation (ACS) in audio recordings of vehicles driven through a production test track, delimiting the boundaries of surface types in the track. ACS is a variant of classical acoustic segmentation where the sequence of labels is known, contiguous and invariable, which is especially useful in this work as the test track has a standard configuration of surface types. The proposed ConvDTW-ACS method utilizes a Convolutional Neural Network for classifying overlapping image chunks extracted from the full audio spectrogram. Then, our custom Dynamic Time Warping algorithm aligns the sequence of predicted probabilities to the sequence of surface types in the track, from which timestamps of the surface type boundaries can be extracted. The method was evaluated on a real-world dataset collected from the Ford Manufacturing Plant in Valencia (Spain), achieving a mean error of 166 milliseconds when delimiting, within the audio, the boundaries of the surfaces in the track. The results demonstrate the effectiveness of the proposed method in accurately segmenting different surface types, which could enable the development of more specialized AI systems to improve the quality inspection process.Comment: 12 pages, 2 figure

An Ontological Architecture for Principled and Automated System of Systems Composition

A distributed system's functionality must continuously evolve, especially when environmental context changes. Such required evolution imposes unbearable complexity on system development. An alternative is to make systems able to self-adapt by opportunistically composing at runtime to generate systems of systems (SoSs) that offer value-added functionality. The success of such an approach calls for abstracting the heterogeneity of systems and enabling the programmatic construction of SoSs with minimal developer intervention. We propose a general ontology-based approach to describe distributed systems, seeking to achieve abstraction and enable runtime reasoning between systems. We also propose an architecture for systems that utilize such ontologies to enable systems to discover and `understand' each other, and potentially compose, all at runtime. We detail features of the ontology and the architecture through two contrasting case studies. We also quantitatively evaluate the scalability and validity of our approach through experiments and simulations. Our approach enables system developers to focus on high-level SoS composition without being tied down with the specific deployment-specific implementation details