Italy

The delivery of cloud services - on the infrastructure, platform, and software level – relies on the management systems’ ability to meet the requirements of cloud providers and their users. Our research efforts, often under the term Cloud Control, has addressed the challenges of how to meet key requirements in terms of, e.g., availability, reliability, performance, and cost- and energy-efficiency since before the term cloud was coined, addressing compute clusters, cloud datacenters, federations of cloud datacenters, edge networks, and software defined infrastructures. Our approach to control the systems has been multidisciplinary, providing autonomous management systems based on distributed systems research complemented with expertise in control theory, mathematical statistics, discrete optimization, and machine learning. And for the problems that simply cannot be controlled, the approach includes anomaly detection and mitigation. This presentation will illustrate how the research area has developed over the past 15 years and includes examples of specific research efforts performed over these years, in essence providing a Swedish Smorgasboard of cloud control research.

CLOSER 2022

15 Years of Cloud Control

The internet of things (IoT) is a platform that allows a network of devices (sensors, smart meters, etc.) to communicate, analyse data and process information collaboratively in the service of individuals or organisations. The IoT network can generate large amounts of data in a variety of formats and using different protocols which can be stored and processed in the cloud. The conference looks to address the issues surrounding IoT devices, their interconnectedness and services they may offer, including efficient, effective and secure analysis of the data IoT produces using machine learning and other advanced techniques, models and tools, and issues of security, privacy and trust that will emerge as IoT technologies mature and become part of our everyday lives.

Big Data (BD) has core values of volume, velocity, variety and veracity. After collecting much data from IoT, BD can be jointly used with machine learning, AI, statistical and other advanced techniques, models and methods, which can create values for people and organizations adopting it, since forecasting, deep analysis and analytics can help identify weaknesses and make improvements based on different analysis.

Maintaining a high level of security and privacy for data in IoT are crucial and we welcome recommendations, solutions, demonstrations and best practices for all forms of security and privacy for IoT and BD.



IoTBDS 2022

The conference looks to address the issues surrounding IoT devices, their interconnectedness and services they may offer, including efficient, effective and secure analysis of the data IoT produces using machine learning and other advanced techniques, models and tools, and issues of security, privacy and trust that will emerge as IoT technologies mature and become part of our everyday lives.


keynote

The International Conference on Cloud Computing and Services Science (CLOSER), focuses on the highly important area of Cloud Computing, inspired by some latest advances that concern the infrastructure, operations, and available services through the global network. Further, the conference considers as essential the link to Services Science, acknowledging the service-orientation in most current IT-driven collaborations. The conference is nevertheless not about the union of these two (already broad) fields, but about Cloud Computing where we are also interested in how Services Science can provide theory, methods and techniques to design, analyze, manage, market and study various aspects of Cloud Computing.

The International Conference on Cloud Computing and Services Science (CLOSER), focuses on the highly important area of Cloud Computing, inspired by some latest advances that concern the infrastructure, operations, and available services through the global network. 

The rapid advancements in Information and Communication Technologies (ICTs) have beengreatly changing our society, with clear societal and economic benefits. Mobiletechnology, Cloud, Big Data, Internet of things, services and technologies that arebecoming more and more pervasive and conveniently accessible, towards to the realizationof a smart society. At the heart of this evolution is the ability to collect, analyze,process and share an ever-increasing amount of data, to extract knowledge for offeringpersonalized and advanced services. A major concern, and potential obstacle, towards thefull realization of such evolution is represented by security and privacy issues. I willillustrate some security and privacy issues arising in emerging scenarios, focusing on theproblem of managing data while guaranteeing protection of data stored or processed byexternal providers.

Data Security and Privacy in Emerging Scenarios

The development and testing of autonomous vehicles requires a massive edge-to-cloud-to-edge “data loop” that begins & ends with the test fleet. In order to meet customer sprint cycle KPIs and iterate across the data loop quickly & efficiently, Microsoft solved a series technical and logistical challenges at scale across an end to end workflow featuring sensor reprocessing, CI/CD & ML pipeline management, and both perception and post-perception closed loop simulation.The focus of this presentation will be a high-level description of the entire data loop with a focus on the unique challenges of sensor reprocessing (commonly called “re-sim” or “playback”) at a massive scale. Re-sim is simultaneously a logistical challenge, a safety challenge, and a budget challenge. The presentation will explain how Microsoft Azure:• Extracts petabytes of data (daily!) from both stationary & nomadic fleets dispersed globally• Filters, processes, & curates those petabytes of data• Accurately assesses & recreates the real-world performance of a device under test• … and do all of the above quickly and cheaplyThe presentation will conclude with a forward-looking overview of anticipated future challenges Microsoft will need to solve as the technology continues to evolve and customer KPIs grow more sophisticated.

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Data Security and Privacy in Emerging Scenarios

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