Internet of things (IoT) is a network of smart things. This indicates the ability of these physical things to transfer information with other physical things. The characteristics of these networks, such as topology dynamicity and energy constraint, challenges the routing problem in these networks. Previous routing methods could not achieve the required performance in this type of network. Therefore, developers of this network designed and developed specific methods in order to satisfy the requirements of these networks. One of the routing methods is utilization of multipath protocols which send data to its destination using routes with separate links. One of such protocols is RPL routing protocol. In this paper, this method is improved using composite metrics which chooses the best paths used for separate routes to send packets. We propose Energy and Load aware RPL (ELaM-IoT) protocol, which is an enhancement of RPL protocol. It uses a composite metric, calculated based on remaining energy, hop count, Link Expiration Time (LET), load and battery depletion index (BDI) for the route selection. In order to evaluate and report the results, the proposed ELaM-IoT method is compared to the ERGID and ADRM-IoT approaches with regard to average remaining energy, and network lifetime. The results demonstrate the superior performance of the proposed ELaM-IoT compared to the ERGID and ADRM-IoT approaches.
Internet of Things (IoT) is a network of smart things. It indicates the ability that the mentioned physical things transfer information with each other. The characteristics of these networks, such as topology dynamicity and energy constraint, make the routing problem a challenging task in these networks. Traditional routing methods could not achieve the required performance in these networks. Therefore, developers of these networks have to consider specific routing methods in order to satisfy their requirements. One of the routing methods is utilization of the multipath protocols in which data are sent to its destination using multiple routes with separate links. One of such protocols is AOMDV routing protocol. In this paper, AOMDV is improved using gray system theory which chooses the best paths used for separate routes to send packets. To do this, Ad hoc On-demand Multipath Distance Vector (AOMDV) packet format is altered and some fields are added to it so that energy criteria, link expiration time, and signal-to-noise ratio can also be considered during selection of the best route. The proposed method named RMPGST-IoT is introduced which chooses the routes with highest rank for concurrent transmission of data, using a specific method based on the gray system theory. In order to evaluate the results, the proposed Routing Multipath based on Gray System Theory (RMPGST)-IoT method is compared to the Emergency Response IoT based on Global Information Decision (ERGID) and Ad hoc Delay-aware Distributed Routing Model (ADRM)-IoT approaches in terms of throughput, packet receiving rate, packet loss rate, average remaining energy, and network lifetime. The results demonstrate that the performance of the proposed RMPGST-IoT is superior to that of ERGID and ADRM-IoT approaches.
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