=Paper=
{{Paper
|id=Vol-2900/WS2Paper2
|storemode=property
|title=Increasing Interoperability in the Web of Things Using Autonomous Agents(Position Paper)
|pdfUrl=https://ceur-ws.org/Vol-2900/WS2Paper2.pdf
|volume=Vol-2900
|authors=Edison Chung,Maxime Lefrançois,Olivier Boissier
|dblpUrl=https://dblp.org/rec/conf/iesa/ChungLB20
}}
==Increasing Interoperability in the Web of Things Using Autonomous Agents(Position Paper)==
https://ceur-ws.org/Vol-2900/WS2Paper2.pdf
Increasing interoperability in the Web of Things
using Autonomous Agents (Position Paper)
Edison Chunga , Maxime Lefrançoisa and Olivier Boissiera
a
Mines Saint-Etienne, Univ Lyon, Univ Jean Monnet, IOGS, CNRS, UMR 5516, LHC, Institut Henri Fayol, F - 42023
Saint-Etienne France
Abstract
The Web of Things (WoT) aims to enable interoperability across the Internet of Things (IoT) and appli-
cation domains. However, the number and heterogeneity of connected devices continues to grow. The
integration of multiple Things with different interaction methods requires human effort and interven-
tion, and is increasingly challenging as their heterogeneity grows. Some form of automation of this task,
for example by delegating new service compositions to autonomous agent, would require mechanisms
for uniform access and interaction among Things. In this position paper, we investigate how Semantic
Interoperability Solutions (SIS) can be combined with multi-agent systems (MAS), to allow agents to
autonomously interact with these WoT resources. We use as a starting point the work of the Web of
Things Working Group at W3C (World Wide Web Consortium). We identify and describe issues related
to i) the representation, ii) the discovery and selection of Things, and iii) the interaction between agents
and Things. We claim that these issues are the core tenets to ensure this integration using MAS, WoT
and SIS.
Keywords
Web of Things, interoperability, Multi-Agent Systems, Thing Description, Autonomous Agents
1. Introduction
While the number of devices, or Things, connected to the Internet of Things (IoT) grows every
day, the IoT suffers from a lack of interoperability across platforms [1]. In order to develop
technology-independent networked applications, platform independent APIs are needed, as
well as means for different platforms to discover how to interoperate with one another. The
Web of Things (WoT) [2] is being developed to address these issues and to be the information
space built upon the IoT where new services (physical and digital) are spawned, building an
environment with inter-connected objects participating to applications such as smart buildings,
intelligent transport, smart energy management, etc. Things in the WoT are physical or virtual
entities whose interaction affordances are described. They can be connected devices, but also
entities such as people, places, and abstract concepts (e.g. events) [3].
Things are heterogeneous in nature, with different ways to interact with them. Thus, cre-
ating and providing new services based on the composition of these Things proves to be a
Proceedings of the Workshops of I-ESA 2020, 17-11-2020, Tarbes, France
" edison.chung@emse.fr (E. Chung); maxime.lefrancois@emse.fr (M. Lefrançois); olivier.boissier@emse.fr (O.
Boissier)
~ https://www.maxime-lefrancois.info/ (M. Lefrançois)
0000-0002-5672-5508 (E. Chung); 0000-0001-9814-8991 (M. Lefrançois); 0000-0002-2956-0533 (O. Boissier)
© 2020 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
Workshop
Proceedings
http://ceur-ws.org
ISSN 1613-0073 CEUR Workshop Proceedings (CEUR-WS.org)
complex task for developers or mashup users. To reduce this complexity, we need to introduce
automatic composition and thus rely on mechanisms to ensure interoperability, and provide
uniform access to Things.
In this paper, we propose to combine Semantic Interoperability Solutions (SIS) and multi-
agent systems (MAS) to bring the required autonomy and interoperability on top of the WoT.
Multi-agent technologies introduce separation of concerns between autonomous decision en-
tities (agents) and active or passive entities (artifacts) [4]. This is done through uniform inter-
faces that agents can use to perceive and act on artifacts. Artifacts can be used to encapsulate
Things and act as proxies for agents to access the real world via the WoT.
Agents could autonomously and uniformly interact with Things, in other words, discover,
reason, access these Things, and build added value services from their composition. In order to
achieve this objective, several challenges have to be considered. This paper aims to state and
illustrate these challenges.
In section 2, we briefly describe related concepts, definitions and the state of the art in WoT,
SIS, and MAS. In section 3, we describe the problem and the related challenges to address the
autonomous interaction among things. Finally, in section 4, we conclude our work and discuss
perspectives.
2. Background
The WoT is the information space built upon the IoT. Its aim is to enable interoperability across
IoT Platforms and application domains [3]. It does so by providing i) IoT interfaces to allow IoT
devices and services to communicate with each other, and ii) standards to define and program
IoT behavior. Things, the central building block of the WoT, are abstractions of physical or
virtual entities [3] that need to be represented in IoT applications. A Thing may provide a
network-facing API for interaction (WoT Interface).
The WoT Thing Description (TD) specifies the semantics of these interactions. This seman-
tics is defined using an ontology: an explicit specification of a conceptualization [5]. TD is
a central building block in the W3C Web of Things (WoT) and can be considered as the en-
try point of a Thing. A TD comprises the description of the Interaction Affordances of the
Thing, general metadata such as communication and security mechanisms, and potentially
other domain specific metadata [3]. Three categories of Interaction Affordances are defined:
Properties, Actions, and Events [6]. Properties can be used for sensing and controlling param-
eters. Actions model invocation of physical processes, and abstract calls of existing platforms.
Events are used for the publish/subscribe model of communication where data are sent asyn-
chronously to the consumer.
A Multi-Agent System (MAS) is a loosely coupled network of agents that work together
to solve problems beyond the individual capabilities or knowledge of each agent [7]. The
characteristics of a MAS [8], are: i) locality and limited information and capabilities in each
agent, ii) no global view and system control, iii) data distribution and control decentralization,
iv) asynchronous computation.
In the context of MAS, we focus on the Multi-Agent Oriented Programming approach [4]
that makes a clear separation of concerns between agents and their environment.
An agent is a physical or software entity, situated in its environment. It is capable of flexible
autonomous action in order to meet its design objectives. Autonomy for an agent means that
it is able to decide on its actions without direct intervention from humans [8]. An agent
can sense the environment and perform actions to change it. The environment denotes the
conceptual space where agents execute and interact. Artifacts encapsulate any kind of resource
or tool (web service, sensor, actuator) that agents can use in the environment to achieve their
goals [9]. They provide uniform access through a set of observable properties, operations,
and signals. Agents can perceive artifacts’ properties and signals, and autonomously decide to
execute artifacts’ operations.
While MAS and IoT have both existed for a long time, few integration attempts have been
realized. One notable paradigm is the Internet of Agents (IoA) [10]. It uses agents to represent
and streamline interactions of Things. The Agent of Things (AoT) [11] and the Multiagent
Web [12] are two approaches that adopt this paradigm. In the AoT, each Thing embeds an
autonomous agent. The hardware and complexity requirements hamper the reusability and
scalability of this approach [11]. The Multiagent Web uses a multi-layer MAS to govern a
group of devices. This approach is scalable as it is built on top of the Web architecture [12].
3. Challenges
As we can see from the previous section, even if several bricks exist, there doesn’t exist yet
a solution to the problem which is considered in this paper: How can we allow agents to au-
tonomously and uniformly interact with Things in the Web of Things?
To better illustrate it, let us consider a scenario in which we want to optimize the power
consumption of a smart building, composed of several spaces in which devices (e.g. sensors,
thermostats, lights, fans, ...) are deployed. Our goal is to introduce autonomous agents to
control the devices and optimize the smart building energy consumption. Our first challenge is
to introduce the devices’ affordances to the agents, since we consider that the existing devices
in the building are, at the beginning, external entities to the agents’ environment. In other
words, we need a uniform representation for the devices in this environment. Our second
challenge is to let the agents autonomously discover and select the devices that will help them
to achieve their goals. Our third challenge is to allow the agents to operate devices, which
implies that agents interact with devices through their representation.
This scenario introduces the following functional issues that need to be addressed to inte-
grate MAS with WoT: i) representation of Things, ii) discovery and selection of Things, and iii)
interaction with Things. Each issue is separately described below.
3.1. How can we represent Things in the agents’ environment?
Each Thing has its own properties, events, and actions; described by its TD, which may poten-
tially include additional metadata based on other ontologies.
Consider we have two Things: the thermostat, and the room it’s in. The thermostat Thing
is a connected device. It should thus expose to the agent i) its current temperature property, ii)
an event temperature reached when some temperature is reached and iii) a change temperature
action. The room Thing is not a connected device, so it will only expose the following properties
room name and floor number for instance.
The representation of Things has two objectives: i) to provide information to the agents
about the Thing, and ii) to provide a way for the agents to interact with it; access to its prop-
erties and events and using its actions. The representation should be self-sufficient; the agent
does not require any other representation to fully interact with the Thing. Furthermore, a
uniform representation can mask the heterogeneity between Things.
Related to representation, several works have proposed using artifacts to offer agents an
access to external resources such as ontologies [13] and algorithms [14]. Simply encapsulating
external resources in artifacts is not enough. A standardized way to describe them is necessary
so that agents can reason on their usage interface. Semantic descriptions, such as OWL [15]
for ontologies and the TD [6] for Things, may prove useful in this regard. The adoption of TD
has not been widespread, since it is a relatively new concept.
A good approach would be to model Things as artifacts, so that agents can easily interact
with them. This approach requires aligning the concept and description of artifacts in agents’
environment with the Thing Description. An artifact provides a set of properties, a set of
signals and a set of operations [4]. Two Things may not have a similar TD. All TDs share the
same general structure. A similar comment applies also to artifacts. Thus, aligning the TD
structure to the structure of a generic artifact becomes the most important task to achieve.
3.2. How can agents discover and select Things to achieve their goals?
Asking developers to prepare a list of TDs for the agents will become impractical as the num-
ber of Things increases. This list provides a degree of uniformity, but we believe that agent
autonomy for discovery of Things is reduced. The agent must be autonomous in its searching
and discovering Things. It should be able to choose Things to interact with, according to their
owns goals without human intervention.
Automated Thing discovery in the WoT has been investigated in several proposals. For in-
stance, Dynamix [14] enables conventional Web apps to discover and control Universal Plug-
and-Play (UPnP) and AirPlay devices uniformly. In [16], a middleware discovers Bluetooth
and UPnP devices, wraps them with a semantic service description, and shows the available
services through a software client. Semantic services, such as Uberdust [17], SPITFIRE [18],
and DiscoWoT [19], have as main objective to facilitate the discovery, selection, and utiliza-
tion of Web-enabled devices. However, applications built on top of these platforms are not
interoperable as they do not use a common ontology to describe Things.
Let us notice that in the multi-agent domain, several attempts have been realized. For in-
stance, in [20], artifacts are implemented as part of an e-learning system. They provide search
and retrieval capabilities to agents for i) modeling learner information using a learner model
ontology, and ii) retrieving resources from learning object repositories.
A possible approach for this challenge would be to allow the agent itself to handle the dis-
covery of Things. The agent can manage its own list of Things. The agent can select the Things
from this list which will help achieve its goal. This would also allow for a network of agents to
be able to share information about the Things. This could be achieved, for example, by using
peer-to-peer communication enabled by JADE [21].
Another approach would be to create or adapt a repository to store TDs [22]. When intro-
ducing a new agent, it only needs to know that there is a repository and that it can use queries
to obtain a list of Things. The agent can send a query for specific interaction affordances, de-
vices, metadata, etc., in order to select Things. It is important to note that the repository would
require its own representation in the agent’s environment. This could be done through either
an agent or an artifact. It must be capable of automated discovery of Things.
3.3. How can agents interact with Things?
Agents should be able to discover and interact with Things uniformly all throughout the WoT.
State-of-the-art approaches about IoA ( [11], [12]) rely on agents as mediators between Things
and other agents. Interactions between agents are more complex than interactions between
agents and resources [23].
As mentioned in section 3.1, we can encapsulate different Things using the same generic
artifact. This would allow any agent to easily discover and interact with any instantiated Thing
based on this artifact. The agent should be able to retrieve properties of a Thing as if they
were the artifact’s properties. The agent should call the actions and events as if they were
the artifact’s operations. Consider the example of a room with a thermostat and a heating
system. An agent reads the property corresponding to the room’s current temperature. The
agent calls the action of the heating system which regulate the temperature of the room. When
the desired temperature is reached, the thermostat sends a notification event in order to tell
the agent that the action is complete. The agent may obtain information about the room by
reading properties such as the room number and corresponding floor. Since relations between
Things can be expressed in their TD using Links, the agent should also be able to know that
the thermostat is in this specific room.
4. Conclusion
In this paper, we provided an overview of challenges that need to be addressed in order to
allow autonomous agents to interact with Things in the WoT. We analyzed issues for each of
these challenges. We also presented a general overview of the state of the art for the integra-
tion between MAS and the WoT, and provided some examples of semantic services for Thing
discovery in the WoT.
We discussed the potential use of artifact encapsulation to solve the challenge of represen-
tation of Things in the agents’ environment, as well as the issue of interaction between agents
and Things. The practical implementation of this concept will be done in future work. We
discussed possible approaches for autonomous discovery and selection of Things by agents.
Issues that were not discussed in this paper, such as the management of Things by agents,
could be considered for future work.
Acknowledgments
This work was partially funded by ENGIE Lab CRIGEN. We thank Lynda TEMAL and Sarra
BEN-ABBES whose comments/suggestions helped improve and clarify this manuscript.
References
[1] M. Noura, M. Atiquzzaman, M. Gaedke, Interoperability in internet of things
infrastructure: Classification, challenges, and future work, 2018. doi:10.1007/
978-3-030-00410-1\_2.
[2] W3C, W3C Web of Things at W3C, 2020. URL: https://www.w3.org/WoT/.
[3] M. Kovatsch, R. Matsukura, M. Lagally, T. Kawaguchi, K. Toumura, K. Kajimoto, Web of
Things (WoT) Architecture, W3C Working Draft, W3C, 2019.
[4] O. Boissier, R. H. Bordini, J. Hübner, A. Ricci, Dimensions in programming
multi-agent systems, The Knowledge Engineering Review 34 (2019). doi:10.1017/
S026988891800005X.
[5] T. R. Gruber, A translation approach to portable ontology specifications, Knowledge
Acquisition 5 (1993) 199–220. doi:10.1006/knac.1993.1008.
[6] S. Kaebisch, T. Kamiya, M. McCool, V. Charpenay, M. Kovatsch, Web of Things (WoT)
Thing Description, W3C Working Draft, W3C, 2018.
[7] E. H. Durfee, V. R. Lesser, Distributed Artificial Intelligence (Vol. 2), Morgan Kaufmann
Publishers Inc., San Francisco, CA, USA, 1989, pp. 229–243.
[8] N. R. Jennings, K. Sycara, M. Wooldridge, A Roadmap of Agent Research and De-
velopment, Autonomous Agents and Multi-Agent Systems 1 (1998) 7–38. URL: https:
//doi.org/10.1023/A:1010090405266. doi:10.1023/A:1010090405266.
[9] A. Omicini, A. Ricci, M. Viroli, Artifacts in the A&A Meta-model for Multi-agent Systems,
Autonomous Agents and Multi-Agent Systems 17 (2008) 432–456. URL: http://dx.doi.org/
10.1007/s10458-008-9053-x. doi:10.1007/s10458-008-9053-x.
[10] P. Pico-Valencia, J. Holgado-Terriza, D. Herrera-Sánchez, J. Sampietro, Towards the In-
ternet of Agents: An Analysis of the Internet of Things from the Intelligence and Au-
tonomy Perspective, Ingeniería e Investigación 38 (2018) 121–129. doi:10.15446/ing.
investig.v38n1.65638.
[11] A. M. Mzahm, M. S. Ahmad, A. Y. C. Tang, Agents of Things (AoT): An intelligent op-
erational concept of the Internet of Things (IoT), in: 2013 13th International Conference
on Intellient Systems Design and Applications, 2013, pp. 159–164. doi:10.1109/ISDA.
2013.6920728.
[12] P. Leong, L. Lu, Multiagent Web for the Internet of Things, in: 2014 International Confer-
ence on Information Science Applications (ICISA), 2014, pp. 1–4. doi:10.1109/ICISA.
2014.6847432.
[13] A. Freitas, A. R. Panisson, L. Hilgert, F. Meneguzzi, R. Vieira, R. H. Bordini, Integrating on-
tologies with multi-agent systems through CArtAgO artifacts, in: 2015 IEEE/WIC/ACM
International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT),
volume 2, IEEE, 2015, pp. 143–150.
[14] D. Carlson, B. Altakrouri, A. Schrader, An Ad-Hoc Smart Gateway Platform for the Web
of Things, in: 2013 IEEE International Conference on Green Computing and Communica-
tions and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, 2013,
pp. 619–625. doi:10.1109/GreenCom-iThings-CPSCom.2013.115.
[15] OWL 2 Web Ontology Language Document Overview (Second Edition), Technical Report,
W3C, 2012. Http://www.w3.org/TR/2012/REC-owl2-overview-20121211/.
[16] Z. Song, A. A. Cardenas, R. Masuoka, Semantic middleware for the Internet of Things, in:
2010 Internet of Things (IOT), 2010, pp. 1–8. doi:10.1109/IOT.2010.5678448.
[17] A. Orestis, A. Dimitrios, C. Ioannis, Towards integrating IoT devices with the Web, in:
Proceedings of 2012 IEEE 17th International Conference on Emerging Technologies Fac-
tory Automation (ETFA 2012), 2012, pp. 1–4. doi:10.1109/ETFA.2012.6489729.
[18] D. Pfisterer, K. Romer, D. Bimschas, O. Kleine, R. Mietz, C. Truong, H. Hasemann,
A. Kröller, M. Pagel, M. Hauswirth, M. Karnstedt, M. Leggieri, A. Passant, R. Richard-
son, SPITFIRE: toward a semantic web of things, IEEE Communications Magazine 49
(2011) 40–48. doi:10.1109/MCOM.2011.6069708.
[19] S. Mayer, D. Guinard, An Extensible Discovery Service for Smart Things, in: Proceedings
of the Second International Workshop on Web of Things, WoT ’11, ACM, New York, NY,
USA, 2011, pp. 7:1–7:6. URL: http://doi.acm.org/10.1145/1993966.1993976. doi:10.1145/
1993966.1993976, event-place: San Francisco, California, USA.
[20] B. Ciloglugil, M. M. Inceoglu, An Adaptive E-Learning Environment Architecture Based
on Agents and Artifacts Metamodel, in: 2018 IEEE 18th International Conference on
Advanced Learning Technologies (ICALT), 2018, pp. 72–74. doi:10.1109/ICALT.2018.
00024.
[21] JADE Team, Java Agent DEvelopment Framework, 2017. URL: https://jade.tilab.com/.
[22] E. Chung, M. Lefrançois, O. Boissier, Bringing connected objects to autonomous agents
operating on the web (2019).
[23] D. L. Acay, G. Tidhar, L. Sonenberg, Extending agent capabilities: tools vs. agents, in:
2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent
Technology, volume 2, IEEE, 2008, pp. 259–265.