With the growing number of sensors, devices, cell phones, and embedded chips in every conceivable machine and appliance, there’s been talk of the rise of the “Internet of things,” in which they are all discovering, communicating and exchanging messages with one another.
SOA provides architectural approach for ‘real-world’ services running on physical devices
Can the Internet of things learn a thing or two from enterprise systems? Perhaps service orientation can increase the functionality of networks of devices?
Dominique Guinard, Vlad Trifa, Stamatis Karnouskos, Patrik Spiess and Domnic Savio published an interesting look at the role SOA is playing in the interlacing and interaction of mobile and embedded devices in IEEE’s Computing Now journal.
As the authors observe:
“SOA approaches traditionally used to couple functionality of heavyweight corporate IT systems are becoming applicable to embedded real-world devices, i.e., objects of the physical world that feature embedded processing and communication. In such infrastructures, composed of large numbers of networked, resource-limited devices, the discovery of services and on-demand provisioning of missing functionality is a significant challenge.”
Guinard and company suggest that SOA provides an architectural approach that enables the deployment and management of “real-world” services running on physical devices. They suggest the use of Web service standards and Web-oriented patterns (REST) to make this happen, helping to integrate physical devices into existing enterprise information systems. “Web services on devices can be used to dynamically register devices and the service(s) they provide.”
There are many areas this could apply. Applying SOA principles to various smart components of logistics systems that rely on various independent components — containers, pallets, and vehicles could help coordinate operations. A production floor may have embedded sensors with equipment that talk to each other.
Guinard and company provide some strategies that can make service orientation happen, including the use of queries to search service metadata that has been gathered by the network discovery of devices. They report designing and evaluating automatic augmentation of the search queries, “with strategies that extend queries with related keywords found on knowledge repositories available on the network, e.g., third party Websites.” With this extension, the say, “we have shown that significantly more services can be identified without overloading devices with description data.”
