Software Defined Network-based Scalable Resource Discovery for Internet of Things

Geo-distributed and heterog eneous Internet of Things (IoT) devices can gener ate hug e amoun t of da ta. Inefficien t manag emen t of IoT-da ta promotes netw ork cong estion and increases computa tional overhead on the data-processing entities. Traditional netw orking architecture, tha t is lack of functional abstr action and monitoring capabilities, often fails to meet the dynamics of IoT. Softw are Define Netw ork (SDN) can be a viable al terna tiv e of the traditional netw orking architecture while dealing with IoT. In SDN, manag emen t, monitoring and context sensing of the connected componen ts are sim plifie and can be customized. In this paper , SDN-sensed contextual inf orma tion of differen t componen ts (computa tional entities, netw ork, IoT devices) are combined together to facilita te scalable resource discov ery in IoT. The proposed policy targ ets balanced processing and cong estion-less forw arding of IoT-da ta. Through sim ula tion studies, it has been demonstr ated tha t the SDN-based resource discov ery in IoT outperf orms the traditional netw orking based approaches in terms of resource discov ery time and Quality of Service (QoS) satisf action rate. Received on 09 April 2017; accepted on 13 July 2017; published on 25 September 2017