Piccolo: In-network compute for 5G services. An EC-Celtic project, funded by the German BMWi, to explore in-network computing architectures for service (de)composition and function placement inside (mobile) networks. The idea of in-network computing augments "traditional" edge and cloud computing concepts by allowing more flexible placement of support functions and services across different areas of the network, ultimately also across providers. The objective is joint optimization of computing, networking, and storage resources.
IVNRI: In-Vehicular Network Research Infrastructure. An industry-funded project developing a freely configurable testbed for exploring network architectures and their capabilities for in-vehicular networks. The project encompasses aspects ranging different link, network, transport, and application layer designs and protocols. We devise highly automated infrastruture and collect and use synthetic as well as real world data sets to evaluate the variety of different (in-vehicle) applications and their interaction/co-existence.
ViM: Virtual Mobility World. A state-funded project in which major industry players, TUM and two other Bavarian universities join forces to devise innovative methods to research, analyze, develop and secure new mobility technologies. ViM aims to build a platform prototype for research and for the development of innovative business models that can be used to test novel mobility services. The goal is the development of a data and software framework that enables the introduction and use of different digital and modular components based on their application context, and provides mobility data as the basis for research, services and applications. In particular, the platform allows the combination of real (historical, current traffic and context data) and simulated data to generate a realistic virtual world.
MO3: MOnitoring, MOdeling and forecasting MObility patterns. An interdisciplinary project within TUM jointly with the Chair of Transportation Systems Engineering on assessing and modeling micro- and mesoscopic mobility in urban areas. Our work will focus on designing, developing, and deploying measurement systems and query infrastructure as well as inference algorithms and models to observe and characterize mobility patterns and provide input for diverse mobility steering applications (such as recommender systems). Leveraging experience of the TSE chair, we will further behavioural mobility models, integrate (observed/inferred) demand onto a demand/supply modeling environment, and use measurements to calibrate integrated models.
Connected Mobility Living Lab. A state-funded research project in which major industry players and TUM join forces to prototype an open platform for mobility services. The aim is bringing together data and (B2B) service providers to offer a sustainable ecosystem of services based upon which a broad range of B2B and consumer services related to human and vehicular mobility can be easily developed and operated. Overall, the project covers a broad range of topics from business processes in support of such an ecosystem to security and privacy to protocol and system design and evaluation. We are involved with three subprojects: on privacy-preserving proximity services, on sensing on demand (sensing as a service) and on social and collaborative mobility services.
RIFE: architectuRe for an Internet For Everybody. A project funded by the EC Horizon 2020 program to provide affordable and sustainable access to the Internet by realizing an architecture for an Internet for everybody that enables access to information and services at economically sustainable price points unmatched by today's technologies while also catering to challenges, such as intermittent connectivity, posed by the varying environmental challenges that are imposed on those who want to connect. RIFE will devise a unifying network architecture, incorporating elements of delay-tolerant and information-centric networking, develop dissemination strategies to enable Internet access in diverse settings, and implement application-specific functions as necessary to support today's and future services.
SSICLOPS: Scalable and Secure Architecture for Cloud Operations. A project funded under the EC Horizon 2020 program to create and operate high-performance private cloud infrastructure that allows flexible scaling through federation with other private clouds without compromising their service level and security requirements. SSICLOPS federation will support the efficient integration of clouds, no matter if they are geographically co-located or distributed, belong to the same or different administrative entities or jurisdictions. We will devise efficient and secure transport protocols for both intra- and inter-cloud/data center communication and develop mechanisms for flexible job scheduling and migration supported by cloud performance monitoring and tuning functions. We will explore four use cases from in-memory data bases high-performance computing (high-energy physics) to cloud bursting to network function virtualization.
METRICS: Measurement for Europe: Training and Research for Internet Communications Science. An EC FP7 Marie Curie Initial Training Networking for 13 PhD students and one post-doctoral researcher on network measurements in the fixed and mobile Internet and within data centers. Research is complemented by summer schools on scientific writing and presentations, tools and methodology, and entrepreneurship. Aalto Comnet work will focus on 1) (mobile) network measurements and QoE prediction and 2) data analysis, trace-based modeling, and simulations of human behavior.
IoTSS: Internet of Things for Smart Systems: The focus of our project is the user context, in which way end users react and interact with the presence of an ecosystem consisting of smart devices dedicated to augment their reality and enrich their experience. Therefore, we create a platform composed of different devices able to tackle different research questions spanning across multiple fields, e.g Indoor navigation optimization, creation of mobile clouds on resource-constrained devices, proximity modeling based on multimodal data.
For recent research projects, please see my previous homepage at Aalto University.