VIoLET: A Large-scale Virtual Environment for Internet of Things

IoT deployments have been growing manifold, encompassing sensors, networks, edge, fog and cloud resources. Despite the intense interest from researchers and practitioners, most do not have access to large-scale IoT testbeds for validation. Simulation environments that allow analytical modeling are a poor substitute for evaluating software platforms or application workloads in realistic computing environments. Here, we propose VIoLET, a virtual environment for defining and launching large-scale IoT deployments within cloud VMs. It offers a declarative model to specify container-based compute resources that match the performance of the native edge, fog and cloud devices using Docker. These can be inter-connected by complex topologies on which private/public networks, and bandwidth and latency rules are enforced. Users can configure synthetic sensors for data generation on these devices as well. We validate VIoLET for deployments with > 400 devices and > 1500 device-cores, and show that the virtual IoT environment closely matches the expected compute and network performance at modest costs. This fills an important gap between IoT simulators and real deployments.Comment: To appear in the Proceedings of the 24TH International European Conference On Parallel and Distributed Computing (EURO-PAR), August 27-31, 2018, Turin, Italy, europar2018.org. Selected as a Distinguished Paper for presentation at the Plenary Session of the conferenc

Cloudlet-based just-in-time indexing of IoT video

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Flexible Resolution of Authorisation Conflicts in Distributed Systems

Flexible Resolution of Authorisation Conflicts in Distributed System

Context-aware and automatic configuration of mobile devices in cloud-enabled ubiquitous computing

This is the author's accepted manuscript. The final publication is available at Springer via http://dx.doi.org/10.1007/s00779-013-0698-3. Copyright @ Springer-Verlag London 2013.Context-sensitive (or aware) applications have, in recent years, moved from the realm of possibilities to that of ubiquity. One exciting research area that is still very much in the realm of possibilities is that of cloud computing, and in this paper, we present our work, which explores the overlap of these two research areas. Accordingly, this paper explores the notion of cross-source integration of cloud-based, context-aware information in ubiquitous computing through a developed prototypical solution. Moreover, the described solution incorporates remote and automatic configuration of Android smartphones and advances the research area of context-aware information by harvesting information from several sources to build a rich foundation on which algorithms for context-aware computation can be based. Evaluation results show the viability of integrating and tailoring contextual information to provide users with timely, relevant and adapted application behaviour and content

Privacy mediators:helping IoT cross the chasm

Unease over data privacy will retard consumer acceptance of IoT deployments. The primary source of discomfort is a lack of user control over raw data that is streamed directly from sensors to the cloud. This is a direct consequence of the over-centralization of today’s cloud-based IoT hub designs. We propose a solution that interposes a locally-controlled software component called a privacy mediator on every raw sensor stream. Each mediator is in the same administrative domain as the sensors whose data is being collected, and dynamically enforces the current privacy policies of the owners of the sensors or mobile users within the domain. This solution necessitates a logical point of presence for mediators within the administrative boundaries of each organization. Such points of presence are provided by cloudlets, which are small locally-administered data centers at the edge of the Internet that can support code mobility. The use of cloudlet-based mediators aligns well with natural personal and organizational boundaries of trust and responsibility

A pervasive approach to a real-time intelligent decision support system in intensive medicine

The decision on the most appropriate procedure to provide to the patients the best healthcare possible is a critical and complex task in Intensive Care Units (ICU). Clinical Decision Support Systems (CDSS) should deal with huge amounts of data and online monitoring, analyzing numerous parameters and providing outputs in a short real-time. Although the advances attained in this area of knowledge new challenges should be taken into account in future CDSS developments, principally in ICUs environments. The next generation of CDSS will be pervasive and ubiquitous providing the doctors with the appropriate services and information in order to support decisions regardless the time or the local where they are. Consequently new requirements arise namely the privacy of data and the security in data access. This paper will present a pervasive perspective of the decision making process in the context of INTCare system, an intelligent decision support system for intensive medicine. Three scenarios are explored using data mining models continuously assessed and optimized. Some preliminary results are depicted and discussed.Fundação para a Ciência e a Tecnologia (FCT

Magmatic origin and petrogenesis characterization of syenite rock from Pakkanadu alkaline complex, Southern Granulite Terrain, India: Implication on emplacement and petrogenetic history

The present study mainly focused on understanding the magmatic origin and petrogenesis characterization based on the Petrography, major, trace and Rare Earth Element (REE) signatures in the alkaline syenite from Pakkanadu alkaline carbonatite complex. The alkaline plutons from South Indian granulite terrain are intruded along with Archaean epidote-hornblende gneisses. The study area was carbonatite complexes of Tamil Nadu and is characterized by a group of rock associations Carbonatite-Syenite-Pyroxenite - Dunite. From Harker various patterns Pakkanadu alkaline complex syenite showed increasing trends of SiO2, Al2O3, Na2O + K2O opposite to decreasing order of CaO, Fe2O3, MgO, TiO2, P2O5 and MnO trend, suggest fractionation of clinopyroxene, hornblende, sphene, apatite and oxide minerals and feldspar that ruled the fractionation. The concentration of trace elements enriched in Large Ion lithophile elements  (LILE) (Ba, Sr, and Rb) elements and High Field Strength Elements (HFSEs) indicated that the dyke intrusion by differentiation of magma from a mantle source. Rare earth element (REE) distribution of Light rare earth element (LREE) enriched and High rare earth element (HREE) depleted pattern show strongly fractionated pattern with moderate Eu anomalies. Plots of tectonic discrimination diagrams of Pakkanadu samples fall in the field of syn-COLG field to the VAG syn- COLG field.     For the first time, this type of study was carried out in the study region in a detailed manner. The present study significantly exposed the petrography, petrogenesis and magmatic origin process in the Pakkanadu alkaline carbonatite complex.

AUTOMATED AGENT PROFICIENCY MEASUREMENT

A contact center routes an incoming customer contact by selecting an agent based on a number of factors. One of those factors is agent proficiency, which is typically configured as different skills and attributes that are associated to an agent. Currently, such skills and attributes are manually configured in contact center solutions and updated by an agent\u27s supervisors and management operatives based on their periodic assessment of an agent\u27s performance and skills. Techniques are presented herein that support an automated solution for the updating of the skills, attributes, and proficiencies that are associated with contact center agents. Under aspects of the presented techniques, agent particulars may be tuned continually, on an ongoing basis, based on the different types of data that is collected during contact center operations (including, for example, call handling metrics, customer survey results, etc.) and historical metrics. Such an automated approach obviates the need for contact center supervisors and administrators to constantly tinker with agent re-skilling during contact center operations and enables a contact center to automatically provide the optimal experience for customers, agents, and supervisors