The internet of things has expanded rapidly over the past few years. These are small devices which are controlled and tracked by latest cost-effective chips of suitable size. The problem of building IoT has changed into the problem of managing the large quantity of data. The quantity of transistors per chip will turn double after every 18 months as per Moore’s law, which has enabled hardware developers to incorporate additional functionality in the same footprint. This helps in the creation of smaller phones, computers and many other ready-to-use electronic devices.
Businesses want their IoT systems to work on super-fast response times, while availing the efficiency and cost benefits of cloud as well. Keep reading to find out how these two technologies are bridged together by edge computing.
The organizational structure of edge computing and cloud computing is almost opposite. A large part of a network is efficiently used by cloud computing to store and process the data through a focused spot, which is basically a data center occupied by cloud pop. Due to the strong interconnectivity of nodes, it is easier to share data with one another through a network which is high-performance.
More organizations are interested in bringing their computation capacities nearer to the information collecting devices with the growth of IoT. Edge computing shifts central computational power away from the cloud and nearer to the devices of end users as devices on IoT systems are usually low on computational potentiality and power. Working with a large number of clients enables the processing to proceed much faster.
Bringing these two technologies together enables the cloud to manage usual computation tasks, whilst edge computing handles needs which are more client-specific. For instance, data aggregation can be depended on edge computing to collect data into an individual set and then it can be sent for further processing to the cloud.