Section: Overall Objectives

Overall Objectives

Given the prevalence of global networking and computing infrastructures (such as the Internet and the Cloud), mobile networking environments, powerful hand-held user devices, and physical-world sensing and actuation devices, the possibilities of new mobile distributed systems have reached unprecedented levels. Such systems are dynamically composed of networked resources in the environment, which may span from the immediate neighborhood of the users – as advocated by pervasive computing – up to the entire globe – as envisioned by the Future Internet and one of its major constituents, the Internet of Things. Hence, we can now talk about truly ubiquitous computing.

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. The latter two aspects are particularly manifested through the physical but also social sensing and actuation capabilities of mobile devices and their users. More specifically, leveraging the massive adoption of smart phones and other user-controlled mobile devices, besides physical sensing – where a device's sensor passively reports the sensed phenomena – social sensing/crowd sensing comes into play, where the user is aware of and indeed aids in the sensing of the environment. In addition, mobile distributed systems are most often characterized by the absence of any centralized control. This results in peer interaction between system entities, ad hoc or opportunistic relations between them, and relations reflecting the social behavior of the systems' users. The above features span the application, middleware and higher network layers of such systems in a cross-layer fashion.

This challenging environment is characterized by high complexity raising key research questions:

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  How to deal with the extreme uncertainty, when developing and running mobile distributed systems, resulting from the openness and constant evolution of their execution environment?

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  How to manage the ultra large scale and dynamicity resulting from millions or even billions of mobile devices that interact with the physical environment through sensing and actuation?

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  How to leverage the social aspects arising out of billions of users carrying personal devices in order to enable powerful, critical-mass social sensing and actuation?

The research questions identified above call for radically new ways in conceiving, developing and running mobile distributed systems. In response to this challenge, MiMove's research aims at enabling next-generation mobile distributed systems that are the focus of the following research topics:

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  Emergent mobile distributed systems. Uncertainty in the execution environment calls for designing mobile distributed systems that are able to run in a beforehand unknown, ever-changing context. Nevertheless, the complexity of such change cannot be tackled at system design-time. Emergent mobile distributed systems are systems which, due to their automated, dynamic, environment-dependent composition and execution, emerge in a possibly non-anticipated way and manifest emergent properties, i.e., both systems and their properties take their complete form only at runtime and may evolve afterwards. This contrasts with the typical software engineering process, where a system is finalized during its design phase  [37] , [42] . MiMove's research focuses on enabling the emergence of mobile distributed systems while assuring that their required properties are met. This objective builds upon pioneering research effort in the area of emergent middleware initiated by members of the team and collaborators  [41] .

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  Large scale mobile sensing and actuation. The extremely large scale and dynamicity expected in future mobile sensing and actuation systems lead to the clear need for algorithms and protocols for addressing the resulting challenges. More specifically, since connected devices will have the capability to sense physical phenomena, perform computations to arrive at decisions based on the sensed data, and drive actuation to change the environment, enabling proper coordination among them will be key to unlocking their true potential. Although similar challenges have been addressed in the domain of networked sensing and mobile robotics, including by members of the team  [80] , [68] , the specific challenges arising from the extremely large scale of mobile devices – a great number of which will be attached to people, with uncontrolled mobility behavior – are expected to require a significant rethink in this domain  [78] . MiMove's research investigates techniques for efficient coordination of future mobile sensing and actuation systems with a special focus on their dependability.

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  Mobile social crowd sensing. While mobile social sensing opens up the ability of sensing phenomena that may be costly or impossible to sense using embedded sensors (e.g., subjective crowdedness causing discomfort or joyfulness, as in a bus or in a concert) and leading to a feeling of being more socially involved for the citizens, there are unique consequent challenges. Specifically, MiMove's research focuses on the problems involved in the combination of the physically sensed data, which are quantitative and objective, with the mostly qualitative and subjective data arising from social sensing. Enabling the latter calls for introducing mechanisms for incentivising user participation and ensuring the privacy of user data, as well as running empirical studies for understanding the complex social behaviors involved. These objectives build upon previous research work by members of the team on mobile social ecosystems and privacy  [94] , [58] , [91] , as well as a number of efforts and collaborations in the domain of smart cities and transport that have resulted in novel mobile applications enabling empirical studies of social sensing systems  [45] , [72] , [73] .

Outcomes of the three identified research topics are implemented as middleware-level functionalities giving rise to software architectures for mobile distributed systems and enabling practical application and assessment of our research. Furthermore, although our research results can be exploited in numerous application domains, we focus in particular on the domain of smart cities, which is an area of rapidly growing social, economic and technological interest.