Titled "New Digital Horizons: Connect, Create, Innovate", the second edition of the event is being jointly organised by Cellular Operators Association of India (COAI), the Department of Telecommunications (DoT) and other government departments. The aim behind IMC2018 is building ideas, sharing knowledge and best practices, forming lasting industry relationships, fostering commercial opportunities, showcasing game changing mobile technology and product trends, providing sectoral insights, industrial solutions, case studies and workshops. The biggest ICTevent in South Asia, comprising of conclave and exhibition will include ministerial and partner programs in Digital India, Smart City, emerging technologies, Make in India projects, skill harmonisation, business innovation and knowledge sharing etc. There will be a technology showcase offering a glimpse into virtual reality, connected cars, m-health, smart wearables, smart home, artificial intelligence, drones, robotics, smart energy, internet of things, block chain, bitcoin, Machine Vision, Cloud Computing Holography, among others. The three day event will cover a wide array of topics, including but not confined to emerging technologies to new digital ecosystems, m-education, digital marketing to e-health, 5G and retail.

The monitoring of large dynamic networks is a major chal- lenge for a wide range of application. The complexity stems from properties of the underlying graphs, in which slight local changes can lead to sizable variations of global prop- erties, e.g., under certain conditions, a single link cut that may be overlooked during monitoring can result in splitting the graph into two disconnected components. Moreover, it is often difficult to determine whether a change will propagate globally or remain local. Traditional graph theory measure such as the centrality or the assortativity of the graph are not satisfying to characterize global properties of the graph. In this paper, we tackle the problem of real-time monitoring of dynamic large scale graphs by developing a geometric approach that leverages notions of geometric curvature and recent development in graph embeddings using Ollivier-Ricci curvature [47]. We illustrate the use of our method by consid- ering the practical case of monitoring dynamic variations of global Internet using topology changes information provided by combining several BGP feeds. In particular, we use our method to detect major events and changes via the geometry of the embedding of the graph.