• Central processing based
  model

• Fulfils the need for large
  amounts of data to be
  accessed more quickly,
  this demand is ever-
  growing due to cloud
  

  agility

• Accessed through

  internet

• Extending cloud to the edge of the network
  Decentralized computinany device with computing, storage,
  and network connectivity can be a fog node

• Fog computing shoves intelligence

• down to the local area network level of
  network architecture.

• Fog computing usually work with cloud and Edge  can work without cloud or fog.

• Edge is limited to smallr number of peripheral

  layers

• Edge computing pushes the intelligence, processing power and communication of an edge gateway or appliance directly into devices like programmable automation controllers

Merits 

• Easy to scale

• Low cost storage

• Based on Internet driven
  global network on robust TCP/IP protocol

• Real time data analysis
  Take quick actions
  Sensitive data remains inside the
  network

• Edge computing simplifies internal communication by means of physically
  

• PACs then use edge computing capabilities to determine what data
  should be stored locally or sent to the cloud for further analysis

• Latency/Response time

• Bandwidth cost

• Security
  

• Power consumption

• No offline-mode

• Sending raw data over
  internet to the cloud
  could have privacy,
  security and legal issues

• Fog computing relies on many

  links to move data from

  physical asset chain to digital layer and this is a potential point of failure.

• Less scalable than fog computing
  

• Interconnected through proprietary
  networks with custom

  security and
  little interoperability.
  

• No cloud-aware