Research

SpatialServices

Introduction

Spatial services are a new generation of services. They exploits spatially distributed data, enable smart environments, or exploit Internet of Things (IoT) scenarios. This is a new category of decentralised services based on data propagation among mobile devices. These services are provided as the result of the collective interactions among multiple entities, involving processes and calculations. It takes place across several geographically distributed computational nodes. Moreover, research in the engineering of collective adaptive systems provides advances in the identification of bio-inspired self-organising mechanisms and their expression as design patterns. Fine-grained analysis of these mechanisms, when taken in isolation or combined with each other, and their sensitivity to parameters in relation with non-functional properties is still lacking. Dynamic composition of these mechanisms and providing reliable non-functional properties, through dynamic adaptation of parameters, is not yet considered in the literature. Spatial system services built on self-organising mechanisms are relevant in specific application contexts, particularly in open smart environment and for applications deployed over several nodes. Their performance de- pends on good calibration and some of them can be in competition for a specific application. The goal of this research project is to determine at run-time the most appropriate mechanism. Services should be well calibrated in dynamic situations to guarantee appropriate non-functional properties expressed as quality of service (QoS). It also intends to develop a model for on-the-fly creation of spatial services. These services are deployed over a geographic area and providing requested non-functional properties. In open smart environments, it is only at run-time that the need for a spatial user-service arises and it is through the collective interactions of existing spatial system services, sensors or other ”Things” that the requested user-service is provided.

Approach 

The goal of this research is to dynamically compose spatial services and determine, at run-time, the most reliable and pertinent composition. On-demand services have to dynamically provide the best combination of the available services to answer to a user's request. In open smart environments, it is only at run-time that the need for a spatial service arises and it is through the collective interactions of existing spatial services, sensors or application that the requested service is provided. On-the-fly service composition will study how spatial services dynamically select themselves to respond to a request by guaranteeing pertinence, reliability and non-functional property.

Applications

On-demand service composition is a tempting approach for an enormous list of applications. It relies on connected objects, deals with dynamic environments and doesn't need any complex or fixed infrastructure. 

  • Social distancing: in health crisis, such as the one provided by the Covid-19 pandemic in 2020, we can envisage a service provided collectively by objects residing in the urban furniture, sensing the number and density of people (inside shops, on-board a bus, in a street, etc.), and providing information on locations to avoid or on routes to take in order to avoid high density areas. An alternative consists in people's phone advertising their presence and collectively constructing information about density and places to avoid.

  • Energy sharing: this is a trendy topic that relies on trading, locally generated energy, with neighbours without passing by a provider. Leveraging our proposal, we can envisage various situations, of multiple scales: from electrical appliances inside a house coordinating the consumption of energy, to coordination of energy sharing among households involving negotiations and contracts. All this, in a dynamic manner, seamlessly integrating new households joining the system, or new electric appliances arriving or departing (including e-cars).

  • Smart city: it offers a large list and variety of connected objects. Heterogeneous robots, devices or urban furniture could collaborate together and ease the user's daily life. Similarly to our example of the personalised shortest illuminated path provided by light bulbs (or light streets), we can imagine waste baskets coordinating themselves the garbage trucks collection.

  • Emergency situation, disaster crisis: such situations can occur everywhere and all the time. On-demand service are built from an ad-hoc infrastructure; they rely on computer nodes disseminated in the environment by first responders. They are connected to specific objects (e.g. robots, doctors, etc.). These services help coordinate emergency teams actions, and more generally help satisfy users' needs when no predefined service or fixed infrastructure can help.

  • Robot / traffic steering: autonomous mobile robots, evolving in dynamic situations with road works or on construction sites, could dynamically request and receive information about obstacles or best routes to take. The obstacles being "objects" providing services advertising themselves as locations to avoid. Collective interactions among obstacles and passageway define the best route. This can be similarly provided to cars in order to ease traffic.

  • Autonomous robots: more generally, autonomous robots (mobile or not, industrial or not) provide and receive services in the environment in which they are situated. These robots can then participate to some spatial service (collectively transporting objects or building a product), and in the process learn the right action to take and adapt itself regarding their dynamic environment.

Papers

Partners

  • University of Applied science of Western Switzerland (HES-SO//Geneva)