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In this work we introduce two novel deterministic annealing based clusteringalgorithms to address the problem of Edge Controller Placement (ECP) inwireless edge networks. These networks lie at the core of the fifth generation(5G) wireless systems and beyond. These algorithms, ECP-LL and ECP-LB, addressthe dominant leader-less and leader-based controller placement topologies andhave linear computational complexity in terms of network size, maximum numberof clusters and dimensionality of data. Each algorithm tries to placecontrollers close to edge node clusters and not far away from other controllersto maintain a reasonable balance between synchronization and delay costs. Whilethe ECP problem can be conveniently expressed as a multi-objective mixedinteger non-linear program (MINLP), our algorithms outperform state of artMINLP solver, BARON both in terms of accuracy and speed. Our proposedalgorithms have the competitive edge of avoiding poor local minima through aShannon entropy term in the clustering objective function. Most ECP algorithmsare highly susceptible to poor local minima and greatly depend oninitialization.

A Clustering Approach to Edge Controller Placement in Software Defined Networks with Cost Balancing