Towards an Efficient Service Provisioning in Cloud of Things (CoT)

The Cloud offers virtually unlimited resources and the ability to scale up or down applications as needed on the fly. Hence, the Cloud emerged as a suitable solution for large-scale IoT applications to cope with the rapidly increasing devices and data volume. Furthermore, IoT broadened the scope of the Cloud to the real world and enabled new service models such as the Sensing as a Service model. The convergence of both technologies stimulated innovations in both fields, we refer to this convergence as the Cloud of Things. The Cloud of Things enables users to request a complex IoT service (IoT application composed of several interconnected micro services) and deploy it seamlessly. However, deploying a complex IoT service in the Cloud of Things infrastructure is a difficult process due to the different types of physical nodes (Cloud data centers, IoT devices, gateways, etc.) and multiple architectures to collect and process data. Furthermore, network usage largely depends on the placement of different services across the network. In this paper, we present an efficient provisioning model of IoT services formulated as a Mixed Integer Problem. The objective is to minimize the cost of the deployment of IoT services in Cloud of Things infrastructure, through optimizing resources usage across physical nodes and bandwidth consumption over the network.

[1]  Prem Prakash Jayaraman,et al.  OpenIoT: Open Source Internet-of-Things in the Cloud , 2014, OpenIoT@SoftCOM.

[2]  Sudip Misra,et al.  Optimal composition of a virtual sensor for efficient virtualization within sensor-cloud , 2015, 2015 IEEE International Conference on Communications (ICC).

[3]  Karl Aberer,et al.  XGSN: An Open-source Semantic Sensing Middleware for the Web of Things , 2014, TC/SSN@ISWC.

[4]  Abdelsalam Helal,et al.  An Optimization Framework for Cloud-Sensor Systems , 2014, 2014 IEEE 6th International Conference on Cloud Computing Technology and Science.

[5]  Dave Evans,et al.  How the Next Evolution of the Internet Is Changing Everything , 2011 .

[6]  David Lillethun,et al.  Mobile fog: a programming model for large-scale applications on the internet of things , 2013, MCC '13.

[7]  Jian Tang,et al.  Sensing as a Service: Challenges, Solutions and Future Directions , 2013, IEEE Sensors Journal.

[8]  George Suciu,et al.  Big Data, Internet of Things and Cloud Convergence – An Architecture for Secure E-Health Applications , 2015, Journal of Medical Systems.

[9]  Sudip Misra,et al.  Assessment of the Suitability of Fog Computing in the Context of Internet of Things , 2018, IEEE Transactions on Cloud Computing.

[10]  Antonio Pescapè,et al.  Integration of Cloud computing and Internet of Things: A survey , 2016, Future Gener. Comput. Syst..

[11]  Maria Fazio,et al.  A Heterogeneous Approach for Developing Applications with FIWARE GEs , 2015, ESOCC.

[12]  Athanasios V. Vasilakos,et al.  Multiobjective Communication Optimization for Cloud-Integrated Body Sensor Networks , 2014, 2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing.

[13]  Imran Khan,et al.  Wireless sensor network virtualization: A survey , 2015, IEEE Communications Surveys & Tutorials.