The Indian Institute of Technology (IIT) Jodhpur, Indian Institute of Information Technology (IIIT) Guwahati and the Indian Institute of Technology (IIT) Kharagpur have collaborated together to perform cutting-edge research in the area of Internet of Things (IoT). The researchers of the three institutes have developed architectures and algorithms to enhance the efficiencies of data collection and transmission associated with IoT devices and applications.
The research paper has been published in the journal, Future Generation Computer Systems, Elsevier, and is co-authored by Dr Suchetana Chakraborty, Assistant Professor, Department of Computer Science and Engineering, IIT Jodhpur, Dr Sandip Chakraborty, Associate Professor, Department of Computer Science and Engineering, IIT Kharagpur and Mr Anirban Das, Research Scholar, Department of Computer Science and Engineering, IIIT Guwahati.
Explaining the relevance of their research in today's world Dr Suchetana Chakraborty, Assistant Professor, Department of Computer Science and Engineering, IIT Jodhpur, said, “The Internet of Things (IoT) is considered the next Industrial Revolution because it is slowly changing our lives. We have already started connecting everyday objects to the internet via embedded devices; smart homes are already a reality and with advancements in Artificial Intelligence, IoT systems are enabling functional robots, and self-driving cars, among others.”
In IoT systems, data is transmitted between objects and systems through the internet. Such data transmission and management are currently packaged into disjoint ecosystems. For example, IoT systems that work within one operating system on devices cannot cross-talk with those devices managed by the other operating systems.
“There is growing interest in sharing IoT services among ecosystems,” said Dr Chakraborty, adding “such an architecture raises a fundamental question – how can multiple applications best utilize and control a single IoT setup?”
In modern IoT applications, data is communicated between the end device and a processing centre, which may be present in the cloud or the edge server (the area where a device or local network interfaces with the internet). The existing problem is that large volumes of data must be transmitted. Although data compression methods are used, they do not take into account the relevance of the data for the specific IoT application. Further, each ecosystem runs independently and is mounted on its own cloud/edge server, which leads to a wastage of resources.
“We sought to address the above two problems of resource wastage and data irrelevance through the development of novel algorithms,” explained the lead researcher. The team has developed an extreme edge-based data pre-processing framework, called CaDGen (Context-aware Data Generation), for efficient data management and forwarding in shared IoT infrastructure.
“We believe that such an approach can suit various smart environments in a connected living setup that minimizes the cost of data management while providing an effective service architecture for end-users,” concluded the researchers in their paper describing their research.