Abstract
Modern-day real-time IoT devices used in domains like automated surveillance, healthcare, augmented/virtual reality, automation and control etc are generating a huge amount of data and are very delay sensitive as well. Due to this, they are becoming bandwidth hungry and require an uninterrupted connectivity/communication channel as well. This gave birth to the use of small cells (micro, pico, femto) on the edge of the network to accommodate a large number of IoT devices. On the other hand, delay sensitivity of real-time IoT applications are forcing the adoption of Edge Computing rather than using a far Cloud. Edge Computing does process the sensed data near to its origin to meet the strict delay requirements. This chapter addresses these two issues and is trying to optimize Edge Computing and Edge Communication network using Integer Linear Programming (ILP). The ILP problem is formulated for optimal computation and communications are original and novel. Using ILP, an optimal way to utilize Edge Computing resources is proposed to meet the demand optimally. Similarly, it solves the issue of optimal and dynamic channel allocation (DCA) in small cells. DCA problem is also formulated as a novel ILP problem and solved.
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