Publications

Abstract : Internet of Things (IoTs) is gaining increasing significance due to real-time communication and decision making capabilties of sensors integrated into everyday objects. IoTs are power and bandwidth-constrained with applications in smarthome, healthcare, transportation and industrial domains. Routing bears significant importance in IoTs where sensors acting as hosts deliver data to the gateways which in turn impacts power consumption. Thus there exists a need for modeling and analysis of routing in IoT networks towards predicting power consumption. In this work, we develop an analytical model of a naive flooding based routing protocol using Markov chains. In particular, we derive steady state transition probabilities of transmit and receive states using protocol execution traces and further utilize them towards predicting power consumption. Our approach to modeling is generic in that it can be applied to routing protocols across domains. Evaluation of the model shows that the predicted values for power consumption lie closer to the actual observations obtained using ns-2 simulation thus resulting in minimal mean square errors.