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Complex business processes can be realised by composing web services already available on the web. Choreography of web services describes how its constituent services have to interact with other to achieve business goals. In order to make a choreographed web service resilient to transient faults, we investigate in this paper the idea of applying checkpoints to web services. We do this in two steps: firstly, we identify patterns in which choreographed web services interact with each other and propose complexity metrics for these interaction patterns. Next, we propose pattern based checkpointing policy that identifies checkpointing locations in the given choreography. We also provide formal specification to the proposed patterns. We demonstrate the usability of our approach through the development of a tool that automatically inserts checkpointing locations in the given choreography specification.

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With the advent and widespread use of web services, complex business processes are being built by discovering and composing services already available over the Internet. Such composite web services operate over the Internet where reliability and speed cannot be guaranteed, hence providing fault handling mechanism to composite web services is of primary importance. Several fault handling and recovery techniques have been proposed in literature in the context of web services. Backward recovery using checkpointing is a general recovery scheme that can be used to make web services resilient to faults. Checkpointing strategies proposed in distributed systems are not directly applicable to web services due to the differences in the two paradigms. Few papers have been published discussing the need and techniques for checkpointing web services. In this paper we present a survey on various distributed and web service checkpointing techniques discussing their applicability, strengths and weaknesses. We give a brief introduction to our approach of checkpointing web services which identifies checkpointing locations, without user intervention, using complexity of interactions and services offered.

The Internet of Things (IoT) has received a lot of interest from researchers recently. IoT is seen as a component of the Internet of Things, which will include billions of intelligent, talkative "things" in the coming decades. IoT is a diverse, multi-layer, wide-area network composed of a number of network links. The detection of services and on-demand supply are difficult in such networks, which are comprised of a variety of resource-limited devices. The growth of service computing-related fields will be aided by the development of new IoT services. Therefore, Cloud service composition provides significant services by integrating the single services. Because of the fast spread of cloud services and their different Quality of Service (QoS), identifying necessary tasks and putting together a service model that includes specific performance assurances has become a major technological problem that has caused widespread concern. Various strategies are used in the composition of services i.e., Clustering, Fuzzy, Deep Learning, Particle Swarm Optimization, Cuckoo Search Algorithm and so on. Researchers have made significant efforts in this field, and computational intelligence approaches are thought to be useful in tackling such challenges. Even though, no systematic research on this topic has been done with specific attention to computational intelligence. Therefore, this publication provides a thorough overview of QoS-aware web service composition, with QoS models and approaches to finding future aspects.