Probabilistic Event Dropping for Intermittently Connected Subscribers over Pub/Sub Systems

International audienceInternet of Things (IoT) aim to leverage data from multiple sensors, actuators and devices for improving peoples' daily life and safety. Multiple data sources must be integrated, analyzed from the corresponding application and notify interested stakeholders. To support the data exchange between data sources and stakeholders, the publish/subscribe (pub/sub) middleware is often employed. Pub/sub provides additional mechanisms such as reliable messaging, event dropping, prioritization, etc. The event dropping mechanism is often used to satisfy Quality of Service (QoS) requirements and ensure system stability. To enable event dropping, basic approaches apply finite buffers or data validity periods and more sophisticated ones are information-aware. In this paper, we introduce a pub/sub mechanism for probabilistic event dropping by considering the stakeholders' intermittent connectivity and QoS requirements. We model the pub/sub middleware as a network of queues which includes a novel ON/OFF queueing model that enables the definition of join probabilities. We validate our analytical model via simulation and compare our mechanism with existing ones. Experimental results can be used as insights for developing hybrid dropping mechanisms

Undifferentiated embryonal sarcoma of the liver mimicking acute appendicitis. Case report and review of the literature

BACKGROUND: Undifferentiated embryonal sarcoma (UES) of liver is a rare malignant neoplasm, which affects mostly the pediatric population accounting for 13% of pediatric hepatic malignancies, a few cases has been reported in adults. CASE PRESENTATION: We report a case of undifferentiated embryonal sarcoma of the liver in a 20-year-old Caucasian male. The patient was referred to us for further investigation after a laparotomy in a district hospital for spontaneous abdominal hemorrhage, which was due to a liver mass. After a through evaluation with computed tomography scan and magnetic resonance imaging of the liver and taking into consideration the previous history of the patient, it was decided to surgically explore the patient. Resection of I–IV and VIII hepatic lobe. Patient developed disseminated intravascular coagulation one day after the surgery and died the next day. CONCLUSION: It is a rare, highly malignant hepatic neoplasm, affecting almost exclusively the pediatric population. The prognosis is poor but recent evidence has shown that long-term survival is possible after complete surgical resection with or without postoperative chemotherapy

Simulation-based Queueing Models for Performance Analysis of IoT Applications

International audienceTo facilitate the development of Internet of Things (IoT) applications, numerous middleware protocols and APIs have been introduced. Such applications built atop reliable or unreliable protocols and they expose different characteristics. Additionally, with regard to the application context (e.g., emergency response operations), several Quality of Service (QoS) requirements must be satisfied. To study QoS in IoT applications, the provision of a generic performance analysis methodology is required. Queueing network models offer a simple modeling environment, which can be used to represent IoT interactions by combining multiple queueing model types for building queueing networks. The resulting networks can be used for performance analysis through analytical or simulation models. In this paper, we present several types of queueing models that represent different QoS settings of IoT interactions, such as intermittent mobile connectivity, message drop probabilities, message availability/validity and resource constrained devices. Using MobileJINQS, we simulate our models demonstrating the significant effect on response times and message success rates when varying QoS settings

Performance Modeling of the Middleware Overlay Infrastructure of Mobile Things

International audienceInternet of Things (IoT) applications consist of diverse Things (sensors and devices) in terms of hardware resources. Furthermore, such applications are characterized by the Things' mobility and multiple interaction types, such as synchronous, asynchronous, and streaming. Middleware IoT protocols consider the above limitations and support the development of effective applications by providing several Quality of Service features. These features aim to enable application developers to tune an application by switching different levels of response times and delivery success rates. However, the profusion of the developed IoT protocols and the intermittent connectivity of mobile Things, result to a non-trivial application tuning. In this paper, we model the performance of the middleware overlay infrastructure using Queueing Network Models. To represent the mobile Thing's connections/disconnections, we model and solve analytically an ON/OFF queueing center. We apply our approach to Streaming interactions with mobile peers. Finally, we validate our model using simulations. The deviations between the performance results foreseen by the analytical model and the ones provided by the simulator are shown to be less than 5%

Geometric documentation of the Tunnel Dome of Road construction with Geodetic Methods

119 σ.Η παρούσα διπλωματική εργασία έχει σαν κύριο στόχο τη γεωμετρική τεκμηρίωση του μεταλλότυπου θόλου της σύραγγας Τ1 στην περιοχή των Τεμπών.The present dissertation aims at the geometric dicumentation of the metal formwork of the T1 tunnel done in the Tempi area.Ιωάννης Α. Γεωργαντά

Probabilistic Event Dropping for Intermittently Connected Subscribers over Pub/Sub Systems

International audienceInternet of Things (IoT) aim to leverage data from multiple sensors, actuators and devices for improving peoples' daily life and safety. Multiple data sources must be integrated, analyzed from the corresponding application and notify interested stakeholders. To support the data exchange between data sources and stakeholders, the publish/subscribe (pub/sub) middleware is often employed. Pub/sub provides additional mechanisms such as reliable messaging, event dropping, prioritization, etc. The event dropping mechanism is often used to satisfy Quality of Service (QoS) requirements and ensure system stability. To enable event dropping, basic approaches apply finite buffers or data validity periods and more sophisticated ones are information-aware. In this paper, we introduce a pub/sub mechanism for probabilistic event dropping by considering the stakeholders' intermittent connectivity and QoS requirements. We model the pub/sub middleware as a network of queues which includes a novel ON/OFF queueing model that enables the definition of join probabilities. We validate our analytical model via simulation and compare our mechanism with existing ones. Experimental results can be used as insights for developing hybrid dropping mechanisms

Simulation-based Queueing Models for Performance Analysis of IoT Applications

International audienceTo facilitate the development of Internet of Things (IoT) applications, numerous middleware protocols and APIs have been introduced. Such applications built atop reliable or unreliable protocols and they expose different characteristics. Additionally, with regard to the application context (e.g., emergency response operations), several Quality of Service (QoS) requirements must be satisfied. To study QoS in IoT applications, the provision of a generic performance analysis methodology is required. Queueing network models offer a simple modeling environment, which can be used to represent IoT interactions by combining multiple queueing model types for building queueing networks. The resulting networks can be used for performance analysis through analytical or simulation models. In this paper, we present several types of queueing models that represent different QoS settings of IoT interactions, such as intermittent mobile connectivity, message drop probabilities, message availability/validity and resource constrained devices. Using MobileJINQS, we simulate our models demonstrating the significant effect on response times and message success rates when varying QoS settings

Performance analysis of Internet of Things interactions via simulation-based queueing models

International audienceNumerous middleware application programming interfaces (APIs) and protocols were introduced in the literature in order to facilitate the application development of the Internet of Things (IoT). Such applications are built on reliable or even unreliable protocols that may implement different quality-of-service (QoS) delivery modes. The exploitation of these protocols, APIs and QoS modes, can satisfy QoS requirements in critical IoT applications (e.g., emergency response operations). To study QoS in IoT applications, it is essential to leverage a performance analysis methodology. Queueing-network models offer a modeling and analysis framework that can be adopted for the IoT interactions of QoS representation through either analytical or simulation models. In this paper, various types of queueing models are presented that can be used for the representation of various QoS settings of IoT interactions. In particular, we propose queueing models to represent message-drop probabilities, intermittent mobile connectivity, message availability or validity, the prioritization of important information, and the processing or transmission of messages. Our simulation models demonstrate the significant effect on delivery success rates and response times when QoS settings are varied

The impact of socio-demographic features on anxiety and depression amongst navy veterans after retirement: a cross-sectional study

The article was funded by the “CUT Open Access Author Fund”Retirement from work may trigger various changes in everyday life that affect mental health. The current cross-sectional study, conducted with 231 veterans, examines the relationship between socio-demographic features and both anxiety and depression in navy veterans after retirement. Spielberg's State-Trait Anxiety Inventory (STAI) was used for anxiety assessment, and the Beck Depression Inventory (BDI) was used for depression assessment. The analysis was performed with the Statistical Package for Social Sciences (SPSS), version 20.0