MiMove’s research has a strong focus on distributed systems, including mobile ones, and supporting middleware, with special interest in the aspects of system emergence and evolution, mobile and social crowd-sensing, as well as user-centric Internet measurement and analysis. Our research has a particular interest in the Internet of Things, given its still open research challenges and its always increasing social, economic and technological impact.
The resulting ubiquitous systems have a number of unique – individually or in their combination – features, such as dynamicity due to volatile resources and user mobility, heterogeneity due to constituent resources developed and run independently, and context-dependence due to the highly changing characteristics of the execution environment, whether technical, physical or social. This raises the challenge of enabling such systems to emerge dynamically out of the composition of networked components or whole autonomous systems while meeting target functional and non-functional goals.
Relevant systems in particular rely on the physical but also social sensing and actuation capabilities of mobile devices and their users, as for instance leveraged in the context of smart spaces/cities. More specifically, the massive adoption of smart phones and other user-controlled mobile devices allows for social sensing/crowdsensing, where the user gets involved – passively or proactively – in the sensing of the environment. However, the diversity in quality and numbers of the contributed observations challenge the resource-efficient and accurate analysis of physical phenomena, while still guaranteeing privacy to the contributing users who disclose sensitive information like location.
Distributed systems with the above specifics further push certain problems related to the Internet and user experience to their extreme. The complexity of most Internet applications challenges even networking experts to fully diagnose and fix performance problems and anomalous network behavior, let alone most Internet users. Moreover, Quality of Experience (QoE), “the overall acceptability of an application or service as perceived subjectively by the end user” is the gold-standard to measure the performance of online services. Ideally, the detection of performance disruptions should capture when QoE degrades, not simply instances when lower-level Quality of Service (QoS) metrics degrade.
The above challenging context raises key research questions:
- 1. How to deal with heterogeneity and dynamicity, which create runtime uncertainty, when developing and running emergent distributed systems in the open and constantly evolving Internet and IoT environment?
- 2. How to raise human-centric social sensing/crowdsensing to a reliable and trustworthy means of capturing world phenomena?
- 3. How to enable automated diagnosis and optimization of networks and systems in the Internet and IoT environment for improving the QoE of their users?
The research questions identified above call for radically new ways in conceiving, developing and running distributed systems, including mobile ones. In response to this challenge, MiMove’s research aims at enabling next-generation distributed systems that are the focus of the following research themes:
Emergent system composition and adaptation
Mobile and social crowdsensing
User-centric Internet measurement and data analysis
We implement the outcomes of the three identified research themes as middleware-level functionalities giving rise to software architectures as well as tools for distributed systems and enabling practical application and assessment of our research.