Edge Caching in Fog-Based Sensor Networks through Deep Learning-Associated Quantum Computing Framework

Algorithm 1

Cache content management.

(i)	Function 1: cache synchronization and cooperation
(ii)	Input: time interval, set of user requests, work load on edge node and distance of UE from the edge node.
(iii)	Output: regional user set is obtained for particular time interval.
	cache_synchronization (t, S)
(1)	Information sharing R, d, at certain time quantum t
(2)	Return S for t
(3)
(4)	t = t + 1
(5)	repeat step 1.
	end
	Function 2: Update caching content in the edge
	Input: list of contents with extracted features.
	Output: prioritized caching content to be placed in F-AP.
	cache_update (L)
(1)	Selection of appropriate map size: x, y
(2)	Define color intensity of map nodes to depict classes for low, medium and high priority content.
(3)	Running the SOMs algorithm after initializing weights .
(4)	Mapping of , on L to get .
	end
	Function 3: serving a user request
	Input: regional user set, assigned edge node.
	Output: serving an incoming request
	Serve_UE_Phase (cache_synchronization( ),)
(1)	if (cache hit)
(2)	Serve
(3)	else
(4)	cache_update( )
(5)	Serve
	End