An Adaptive Nature-inspired Fog Archit...

During the last decade, Cloud computing has efficiently exploited the economyof scale by providing low cost computational and storage resources over theInternet, eventually leading to consolidation of computing resources into largedata centers. However, the nascent of the highly decentralized Internet ofThings (IoT) technologies that cannot effectively utilize the centralized Cloudinfrastructures pushes computing towards resource dispersion. Fog computingextends the Cloud paradigm by enabling dispersion of the computational andstorage resources at the edge of the network in a close proximity to where thedata is generated. In its essence, Fog computing facilitates the operation ofthe limited compute, storage and networking resources physically located closeto the edge devices. However, the shared complexity of the Fog and theinfluence of the recent IoT trends moving towards deploying and interconnectingextremely large sets of pervasive devices and sensors, requires exploration ofadaptive Fog architectural approaches capable of adapting and scaling inresponse to the unpredictable load patterns of the distributed IoTapplications. In this paper we introduce a promising new nature-inspired Fogarchitecture, named SmartFog, capable of providing low decision making latencyand adaptive resource management. By utilizing novel algorithms and techniquesfrom the fields of multi-criteria decision making, graph theory and machinelearning we model the Fog as a distributed intelligent processing system,therefore emulating the function of the human brain.