Abstract Novel utility computing paradigms rely upon the deployment of multi-service applications to pervasive and highly distributed cloud-edge infrastructure resources. Deciding onto which computational nodes to place services in cloud-edge networks, as per their functional and non-functional constraints, can be formulated as a combinatorial optimisation problem. Most existing solutions in this space are not able to deal with unsatisfiable problem instances, nor preferences, i.e., requirements that DevOps may agree to relax to obtain a solution. In this article, we exploit Answer Set Programming optimisation capabilities to tackle this problem. Experimental results in simulated settings show that our approach is effective on lifelike networks and applications.

Abstract The volume at hand presents the Special Issue on “Distributed Complex Systems: Governance, Engineering, and Maintenance”. The Special Issue has been originally conceived within the context of the 2nd International Workshop on Governing Adaptive and Unplanned Systems of Systems (GAUSS 2020), one of the co‐located events of the 31st International Symposium on Software Reliability Engineering (ISSRE 2020). The authors of the best papers at GAUSS 2020 have been invited to submit an extended version of their previous work. In addition, the editors opened the submission also to all the other researches working on technical and managerial solution for governing Distributed Complex Systems. Ultimate objective of the editors with this Special Issue is to promote discussions focusing on anticipating, mitigating, or reacting to scenarios that were unplanned or under‐specified at design time.

Studies on public transportation in Europe suggest that European inhabitants use buses in ca. 56% of all public transport travels. One of the critical factors affecting such a percentage and more, in general, the demand for public transport services, with an increasing reluctance to use them, is their quality. End-users can perceive quality from various perspectives, including the availability of information, i.e., the access to details about the transit and the provided services. The approach proposed in this paper, using innovative methodologies resorting on data mining and machine learning techniques, aims to make available the unavailable data about public transport. In particular, by mining GPS traces, we manage to reconstruct the complete transit graph of public transport. The approach has been successfully validated on a real dataset collected from the local bus system of the city of L'Aquila (Italy). The experimental results demonstrate that the proposed approach and implemented framework are both effective and efficient, thus being ready for deployment.

BACKGROUND: Hepatocellular carcinoma (HCC) is an aggressive epithelial tumor which shows very poor prognosis and high rate of recurrence, representing an urgent problem for public healthcare. MicroRNAs (miRNAs/miRs) are a class of small, non-coding RNAs that attract great attention because of their role in regulation of processes such as cellular growth, proliferation, apoptosis. Because of the thousands of potential interactions between a single miR and target mRNAs, bioinformatics prediction tools are very useful to facilitate the task for individuating and selecting putative target genes. In this study, we present a chemically-induced HCC mouse model to identify differential expression of miRNAs during the progression of the hepatic injury up to HCC onset. In addition, we describe an established bioinformatics approach to highlight putative target genes and protein interaction networks where they are involved. RESULTS: We describe four miRs (miR-125a-5p, miR-27a, miR-182, miR-193b) which showed to be differentially expressed in the chemically-induced HCC mouse model. The miRs were subjected to four of the most used predictions tools and 15 predicted target genes were identified. The expression of one (ANK3) among the 15 predicted targets was further validated by immunoblotting. Then, enrichment annotation analysis was performed revealing significant clusters, including some playing a role in ion transporter activity, regulation of receptor protein serine/threonine kinase signaling pathway, protein import into nucleus, regulation of intracellular protein transport, regulation of cell adhesion, growth factor binding, and regulation of TGF-beta/SMAD signaling pathway. A network construction was created and links between the selected miRs, the predicted targets as well as the possible interactions among them and other proteins were built up. CONCLUSIONS: In this study, we combined miRNA expression analysis, obtained by an in vivo HCC mouse model, with a bioinformatics-based workflow. New genes, pathways and protein interactions, putatively involved in HCC initiation and progression, were identified and explored.

Wireless Sensor Networks are becoming one of the most successful choices for the development and deployment of applications in a range of scenarios, from intelligent homes to environment monitoring. Nowadays, there is a growing demand for programming large-scale wireless sensor networks. New programming paradigms should ease the task of building WSN applications that adapt at run-time to changes in the context, in the available resources, and also in user requirements. In this paper we describe PROTEUS, a platform to manage adaptation and reconfiguration, with the aim of supporting the development of WSN applications. After introducing PROTEUS, we show how it can be used to program a dynamic clustering algorithm, where clusters are created and destroyed at runtime, and nodes need to adapt and reconfigure accordingly. We provide a prototype implementation using TinyOS. Some remarks on the work are also presented.

Peer-to-peer (P2P) systems are widely used for sharing digital items without structured metadata and in absence of any kind of digital rights management applied to the distributed contents. In this paper we propose the implementation of a prototype application that makes use of a structured P2P system enabling the indexing of complex metadata, used to express digital rights. In this way the media contents are exchanged and played according to the expressed grants. The creation and the consumption of the shared contents can be performed through any MPEG-21 REL compliant software and the application allows indexing and search for both governed and ungoverned contents. The information about the license can be included in the queries and the P2P network can be used to share governed contents (both free and with fee) in a legitimate way. In particular the proposed approach represents a suitable solution for indexing and querying rights complex structures on DHT based networks.

TCP is a reliable transport protocol that performs well in fixed networks where congestion is the primary cause of packet loss. However, TCP's packet recovery schemes lead to non-optimized data flow resuming after handover procedures in wireless LAN environments. The Bluetooth system is a low cost, short range wireless technology that can be used to provide network access; the handover procedure among Bluetooth access points is relatively slow compared to other standards because Bluetooth was born as a cable replacement with no mobility support. In this document TCP performance over the Bluetooth system is analyzed with particular attention to its behavior during the handover procedure that has been developed in our laboratories. TCP measurements, collected on a real-time prototype, show that packet losses during Bluetooth handovers result in TCP stream interruption that can last for more than two seconds even though layer two handover time is about 350 ms.