Autonomic Management of Cloud Neighbourhoods through Pulse Monitoring

Abstract-This paper reports on autonomic computing research, including the development of a self-* proof of concept, for a cloud based environment. It monitors administrative boundaries from within an autonomic manager, with each manager operating in a peer-to-peer mode and utilizing a pulse monitor. The prototype was developed in Java utilizing SNMP to demonstrate the manager's self-situation and environment-awareness of the current state of the whole neighborhood and proves the feasibility of communicating the health of the neighborhood to peer managers using an XML pulse concept. Each manager houses the functionality to enact changes to their neighborhood using SNMP based rules. This enables the capability to provide self-healing, self-configuring, self-optimizing and self-protection to network neighborhoods within cloud computing

On Autonomic HPC Clouds

Proceedings of: Second International Workshop on Sustainable Ultrascale Computing Systems (NESUS 2015). Krakow (Poland), September 10-11, 2015.The long tail of science using HPC facilities is looking nowadays to instant available HPC Clouds as a viable alternative to the long waiting queues of supercomputing centers. While the name of HPC Cloud is suggesting a Cloud service, the current HPC-as-a-Service is mainly an offer of bar metal, better named cluster-on-demand. The elasticity and virtualization benefits of the Clouds are not exploited by HPC-as-a-Service. In this paper we discuss how the HPC Cloud offer can be improved from a particular point of view, of automation. After a reminder of the characteristics of the Autonomic Cloud, we project the requirements and expectations to what we name Autonomic HPC Clouds. Finally, we point towards the expected results of the latest research and development activities related to the topics that were identified.The work related to Autonomic HPC Clouds is supported by the European Commission under grant agreement H2020-6643946 (CloudLightning). The CLoudLightning project proposal was prepared by eight partner institutions, three of them as earlier partners in the COST Action IC1305 NESUS, benefiting from its inputs for the proposal. The section related to Autonomic Clouds is supported by the Romanian UEFISCDI under grant agreement PN-II-ID-PCE-2011- 3-0260 (AMICAS)

System to Recommend the Best Place to Live Based on Wellness State of the User Employing the Heart Rate Variability

[EN] The conditions of the environment where a person lives have a great impact on his wellness state. When buying a new house, it is important to select a place that aids in improving the wellness state of the buyer or, at least, keeps it at the same level. A deficient wellness state implies an increase of stress and the appearance of some effects associated with it. Heart rate variability (HRV) allows measuring the stress or wellness levels of a person by measuring the difference in time between heartbeats. A low HRV is related to high stress levels whereas a high HRV is associated with a high wellness state. In this paper, we present a system that measures the wellness and stress levels of home buyers by employing sensors that measure the HRV. Our system is able to process the data and recommend the best neighborhood to live in considering the wellness state of the buyer. Several tests were performed utilizing different locations. In order to determine the best neighborhood, we have developed an algorithm that assigns different values to the area in accordance with the HRV measures. Results show that the system is effective in providing the recommendation of the place that would allow the person to live with the highest wellness state.Lacuesta Gilabert, R.; García-García, L.; García-Magariño, I.; Lloret, J. (2017). System to Recommend the Best Place to Live Based on Wellness State of the User Employing the Heart Rate Variability. IEEE Access. 5:10594-10604. doi:10.1109/ACCESS.2017.2702107S1059410604

Social-Context Middleware for At-Risk Veterans

Many veterans undergo challenges when reintegrating into civilian society. These challenges include readapting to their communities and families. During the reintegration process veterans have difficulties finding employment, education or resources that aid veteran health. Research suggests that these challenges often result in veterans encountering serious mental illness. Post-Traumatic Stress Disorder (PTSD) is a common mental disease that veterans often develop. This disease impacts between 15-20% of veterans. PTSD increases the likelihood of veterans engaging in high risk behaviors which may consist of impulsivity, substance abuse, and angry outbursts. These behaviors raise the veterans’ risk of becoming violent and lashing out at others around them. In more recent studies the VA has started to define PTSD by its association to specific high risk behaviors rather than defining PTSD based on a combination of psychiatric symptoms. Some researchers have suggested that high risk behaviors -- extreme anger (i.e., rage or angry outbursts) is particularly problematic within the context of military PTSD. Comparatively little research has been done linking sensor based systems to identify these angry episodes in the daily lives of military veterans or others with similar issues. This thesis presents a middleware solution for systems that work to detect, and with additional work possibly prevent, angry outbursts (also described in psychological literature as “rage”) using physiological sensor data and context-aware technology. This paper will cover a range of topics from methods for collecting system requirements for a subject group to the development of a social-context aware middleware. In doing such, the goal is to present a system that can be constructed and used in an in lab environment to further the research of building real-world systems that predict crisis events, setting the state for early intervention methods based on this approach

A Survey on Virtualization of Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are gaining tremendous importance thanks to their broad range of commercial applications such as in smart home automation, health-care and industrial automation. In these applications multi-vendor and heterogeneous sensor nodes are deployed. Due to strict administrative control over the specific WSN domains, communication barriers, conflicting goals and the economic interests of different WSN sensor node vendors, it is difficult to introduce a large scale federated WSN. By allowing heterogeneous sensor nodes in WSNs to coexist on a shared physical sensor substrate, virtualization in sensor network may provide flexibility, cost effective solutions, promote diversity, ensure security and increase manageability. This paper surveys the novel approach of using the large scale federated WSN resources in a sensor virtualization environment. Our focus in this paper is to introduce a few design goals, the challenges and opportunities of research in the field of sensor network virtualization as well as to illustrate a current status of research in this field. This paper also presents a wide array of state-of-the art projects related to sensor network virtualization

Proceedings of the Second International Workshop on Sustainable Ultrascale Computing Systems (NESUS 2015) Krakow, Poland

Proceedings of: Second International Workshop on Sustainable Ultrascale Computing Systems (NESUS 2015). Krakow (Poland), September 10-11, 2015

Building the Hyperconnected Society- Internet of Things Research and Innovation Value Chains, Ecosystems and Markets

This book aims to provide a broad overview of various topics of Internet of Things (IoT), ranging from research, innovation and development priorities to enabling technologies, nanoelectronics, cyber-physical systems, architecture, interoperability and industrial applications. All this is happening in a global context, building towards intelligent, interconnected decision making as an essential driver for new growth and co-competition across a wider set of markets. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC – Internet of Things European Research Cluster from research to technological innovation, validation and deployment.The book builds on the ideas put forward by the European Research Cluster on the Internet of Things Strategic Research and Innovation Agenda, and presents global views and state of the art results on the challenges facing the research, innovation, development and deployment of IoT in future years. The concept of IoT could disrupt consumer and industrial product markets generating new revenues and serving as a growth driver for semiconductor, networking equipment, and service provider end-markets globally. This will create new application and product end-markets, change the value chain of companies that creates the IoT technology and deploy it in various end sectors, while impacting the business models of semiconductor, software, device, communication and service provider stakeholders. The proliferation of intelligent devices at the edge of the network with the introduction of embedded software and app-driven hardware into manufactured devices, and the ability, through embedded software/hardware developments, to monetize those device functions and features by offering novel solutions, could generate completely new types of revenue streams. Intelligent and IoT devices leverage software, software licensing, entitlement management, and Internet connectivity in ways that address many of the societal challenges that we will face in the next decade

The Impact of Digital Technologies on Public Health in Developed and Developing Countries

This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic