methodology to solve complex service
interactions via data-centric architectures, such as Hadoop. A significant
challenge is enabling the seamless
cooperation of multiple organizations
working on different platforms to satisfy consumers’ requirements.
This would deliver on the much-needed service composition. Barriers
to automated interorganizational service composition include disparities
in competency, trust, accountability,
functional and non-functional goals
(including security and privacy) at the
organizational level, and in interaction
protocols and representations at the
We identify four emerging research
challenges in service computing: Service design, service composition,
crowdsourcing-based reputation, and
the Internet of Things (Io T). First, we
introduce service design, which is
a fundamental but yet unsolved research problem in service computing.
Second, we elaborate on challenges
of service composition in the context
of large-scale Web and cloud service
systems, big data, and social networks. Next, crowdsourcing is a cost-effective means for IoT deployment,
through collecting sensing data from
pervasive sensing devices, for example, mobile phones.
14 We focus on
crowdsourcing as a key mechanism
for reputation computation. Lastly,
we discuss how service computing
helps realize the Io T vision and challenges (see Figure 2).
Challenges in service design. Ser-
vice design is about mapping a formal
understanding of the nature of ser-
vices and relationships thereof. This
is an important prerequisite to build-
ing sound service systems. Service
systems have so far been built without
an adequate rigorous foundation that
would enable reasoning about them.
The preferred approach has been to
rely on traditional software engineer-
ing approaches, which do not typically
take into account the fact that service
systems inherently bring together au-
tonomous parts. The Web potentially
provides a unique and uniform plat-
form to develop sound service sys-
tems. However, there has not been any
comprehensive theoretical framework
to define and analyze complex service
systems on the Web. As a result, only
development of cloud applications. As
already mentioned, service computing
can benefit from and contribute to new
directions inspired by the emergence
of mobile computing, cloud comput-
ing, big data, and social computing, as
exemplified in Figure 2. This manifesto
outlines the directions.
Since the emergence of the concept
of service computing, a number of
position and survey articles have been
7, 9, 16, 24 The present effort
differs from previous attempts in two
main ways. First, the driving factor in
this work is to decouple service computing from the technologies to implement service-oriented systems that
take full advantage of the promises
and expectations of service computing.
Second, this work emphasizes the contribution and in of service computing
on emerging trends in computing.
The structure of this manifesto
starts with analyzing the obstacles to
followed by examining the major challenges in emerging areas of service
computing. We then present a research
roadmap to address the identified
challenges and draw conclusions and
provide our assessments of the prospects for success.
Challenges in Service
According to our survey on the articles published in the aforementioned
journals and conferences (see the
table), current service computing research focuses mostly on seven problem areas: architecture, specification
languages, protocols, frameworks,
life cycle, quality of service, and the
establishment of trust and reputation
across the boundaries of autonomous
enterprises. The problems are especially apparent in the aforementioned
emerging service domains.
An often-overlooked strategic challenge in service computing is analyzing
why service computing has not reached
its full potential in the real world, and
what needs to be done to change that.
A barrier that hinders service computing research from being transformed
into an effective solution for industry
challenges has been the concomitant
lack of an easy methodology to transform complex data processing problems into routine services and an easy
their ability to work
in a competitive
where the key
is their quality.