Wireless sensor networks (WSN) are important communication components of an internet of things (IoT). With the development of IoT and the increasing number of connected devices, network structure management and maintenance face the serious challenge of energy consumption. By balancing the network load, the energy consumption can be improved effectively. In the conventional WSN architecture, the two prerequisites of the load-balancing mechanism, flexibility and adaptability, are difficult to achieve. softwaredefined networking (SDN) is a novel network architecture that can promote flexibility and adaptability using a centralized controller. In this paper, a novel SDN architecture aimed at reducing load distribution and prolonging lifetime is proposed, which consists of different components such as topology, BS and controller discovery, link, and virtual routing. Accordingly, a new mechanism is proposed for load-balancing routing through SDN and virtualization. Through direct monitoring of the link load information and the network running status, the employed OpenFlow protocol can determine load-balancing routing for every flow in different IoT applications. The flows in different resource applications can be directed to a base station (BS) via various routes. This implementation reduces the exchange of network status and other relevant information. Virtual routing aims to weigh forward nodes and select the best node for each IoT application. The simulation results show the distribution of load over the network in the proposed algorithm and are characterized by the balanced network energy consumption, but also it prolongs network lifetime in comparison to the LEACH, improved LEACH, and LEACH-C algorithms. IoT, load balancing, routing, SDN, WSN. INDEX TERMS

Low power and limited processing are characteristics of nodes in Wireless sensor networks. Therefore, optimal consumption of energy for WSN protocols seems essential. In a number of WSN applications, sensor nodes sense data periodically from environment and transfer it to the sink. Because of limitation in energy and selection of best route, for the purpose of increasing network remaining energy a node with most energy level will be used for transmission of data. The most part of energy in nodes is wasted on radio transmission; thus decreasing number of transferred packets in the network will result in increase in node and network lifetimes. In algorithms introduced for data transmission in such networks up to now, a single route is used for data transmissions that results in decrease in energy of nodes located on this route which in turn results in increasing of remaining energy. In this paper a new method is proposed for selection of data transmission route that is able to solve this problem. This method is based on learning automata that selects the route with regard to energy parameters and the distance to sink. In this method energy of network nodes finishes rather simultaneously preventing break down of network into two separate parts. This will result in increased lifetime. Simulation results show that this method has been very effective in increasing of remaining energy and it increases network lifetime.

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