Dynamically evolving networks get humongous in no time. Usually, sampling techniques are used to create representative specimens of such large scale socio-centric temporal networks. Likewise, the size of ego networks gets larger over a period of evolution. Which is why, there is a need to sample ego-centric networks while maintaining the importance and efficiency of the ego. In this paper, we present a novel method to sample ego networks as they evolve, while maintaining the freshness of the ego network, with the latest ties and most stronger relationships from past, based on an attenuation factor. We made use of an exhaustive list of node level and graph level metrics to evaluate and compare the samples with the original network. Our experiments show that the proposed method maintains most active and recent nodes. It also preserves the strength of ties between them. We find that our method decreases the redundancy while maintaining the efficiency of network. We also analysed the evolution of an ego network over a period of 31 days.