The explosive increase of data traffic with the proliferation of devices leads to massive interconnections.rnAs a result, the difficulty of network management operations and configurations,rnservice provisioning, and heterogeneous networks due to continuous network deployments tornmeet the demand of ubiquitous connections evolved the network programmability concept as arnsolution.The SDN decoupling of the control plane from the data plane with logically centralizedrnand programmable network came with opportunities and also challenges such as scalability andrnreliability that addressed with Multiple controller systems to improve network performance.rnThe number of controllers needed for a given network topology and where it should be placedrnoptimally might vary with different use cases. For these varieties of use cases, different formulationsrnof mathematical models with different optimization models are addressed in manyrnresearch works. This thesis work focused on optimum controller placement for the WAN networkrntopology of Ethio telecom optimizing propagation latency and controller imbalance withrnConstraint of controller capacity and the metrics trade-off analysis.rnThe optimum controller placement to minimize controller number by the constraints of propagationrndelay, controller capacity, traffic estimates, and load balance. Performance evaluationrnbased on these parameters based optimization model of the heuristic approaches like SimulatedrnAnnealing and K-Medoid is performed. In this work, the trial and error way of determiningrncontroller number taking as the input parameter is replaced with determining it from controllerrncapacity and node weights (flow requests from nodes). Also introduced the concept of loadrnbalance based on Jainâ€™s fairness index to measure how load is fairly distributed.rnAt last, the impact of controller capacity assessment on parameters of the optimum placementrninvestigation showed controller capacity affects the placement metrics. As a result, K-Medoidrnshowed improvement of 32% to 90% in load balance taking the same latency as a reference andrn12.5% to 29% node to controller latency taking the same controller imbalance as a reference.rnFinally, optimum controller placement was identified and shown on google earth.