No, we're not talking about Superconducting Quantum Interference Devices [SQUID's], the ultra sensitive magnetometers used to measure subtle magnetic fields, based on superconducting loops containing Josephson junctions. We're talking about the cephalopods of the order Teuthida, short Squid, known to most people as seafood. Or we may know them from myths and legends or horror movies in which they star as monsters of the deep.
The squid is related to the octopus, cuttlefish and the nautilus. Cephalopods are among the oldest and most successful animals that have ever lived. They have survived hundreds of millions of years. They have no trace of a skeleton, neither internal nor external, but have a distinct head, a mantle, and arms. Squid have eight arms arranged in pairs and two - usually longer - tentacles. The squid are thought to be the most intelligent invertebrates and an important example of advanced cognitive evolution in animals. The existence of impressive spatial learning capacity, navigational abilities, and cooperative predatory techniques in cephalopods is widely acknowledged.
The Squid's intelligence is the result of a more evolved nervous system, which is fundamentally different from that of all other vertebrates, who only use ganglia for their nervous system. The squids nervous system is layered and consists of multiple 'tiers'. The first tier is the main controller, the Squids brain. It is found in the front of arthropods. This is a genetic adaption in order to allow the Squid to sense stimuli and react quicker. The second tier of the Squid's nervous system is a pair of nerve cords, giant axons, which may be up to one millimeter in length. These axons function like an intermediate brain, as they are at the connection point to the ganglia. The third tier is made of the masses of ganglia.
This brings us back to the question at the beginning, "What the heck have squids to do with IoT". Well, Squid's serve as a perfect example of a three-tier IoT architecture for the collection of sensor data, where huge numbers of small, low power, sensors relay collected data to nearby intermediate gateways. These gateways in turn, securely transmit the data to a centralised cloud service 'brain'.
In our current state of technology, you canít run everything centrally in the cloud. There are latency, mobility, geographic, bandwidth, reliability, security and privacy challenges to deal with. On the other hand, you can't run everything at the edge with intelligent sensor endpoints, due to energy, space, capacity, environmental, reliability, modularity, and security challenges.
The three-tier IoT architecture, often called "Fog Computing", bridges the continuum from cloud to things. It distributes compute, communication, control, storage and decision-making closer to where the data is originated, enabling faster processing time and lowering network costs. Fog is an extension of modern cloud-based computing architectures, where elements of the architecture can reside in multiple layers of a networkís topology. By adding layers of fog nodes or gateways, applications can be partitioned to run at the optimal network level.
In particular, this model of computing supports time-critical applications that require sub-millisecond reaction time. Autonomous vehicles, emergency responsiveness, drones and virtual reality are among the dozens of applications that require rapid latency.
We tell the story of a Squid, who is under threat in its environment by a lurking sperm whale. The sperm whale attacks the squid. We will show what happens next.