In this paper, we discuss optimal controller placement for Software Defined Networks (SDN) and propose a non-zero-sum game based distributed technique. Our proposed technique is a simple and low-complexity solution which runs in real-time. This can be implemented as an optimization engine at each SDN controller. The optimization engine at each controller computes a payoff function and compares its own payoff value with that of neighbors and takes appropriate decisions such that either new controllers should be added, or existing controllers should be deleted or offloading should be performed between controllers dynamically. We have conducted extensive simulations and verified the usability of the proposed scheme. We also propose a deployment framework which can be implemented using OpenFlow enabled platforms. Use of this technique not only can improve Quality of Services (QoS -minimum packet drops and delay) but also can save cost of deployment and operation.

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Indoor wireless communication using Wireless Fidelity (WiFi) is becoming a major need for the success of Internet of Things (IoT) and cloud robotics in both developed and developing countries. With different operating conditions, interference, obstacles and type of building materials used, it is difficult to predict the path loss components in an indoor environment, which are crucial for the network design. It has been observed that the indoor path loss models proposed for western countries cannot be directly used in Indian scenarios due to variations in building materials utilized, floor plans, etc. In this paper, we have proposed a non-deterministic statistical indoor path loss model-Tata Indoor Path Loss Model (T-IPLM) which can be used for the 2.4 -2.5 GHz, Industrial Scientific and Medical (ISM) band. To propose and validate, we have conducted several drive tests with different conditions such as busy office premise with obstacles, open office premise, corridor, canteen, and multistorey office locations, etc. We have also compared T-IPLM with popular path loss models such as ITU-R and Log-distance; T-IPLM matches closely with the drive test results as compared to other models. We believe that T-IPLM model can be used extensively to design accurate indoor communication networks required for regular WiFi communications and deployment and operations of IoT and cloud robotics.