A Dominating Tree Based Leader Election Algorithm for Smart Cities IoT Infrastructure

Multi-attribute based self-stabilizing algorithm for leader election in distributed systems

“…Kutten et al propounded a randomized election algorithm [23] for asynchronous complete networks which are essentially singularly optimal. Kadjouh et al proposed a dominating tree based algorithm [22] to elect a leader for smart cities in IoT infrastructure. It is a low energy consuming and fault-tolerant leader election algorithm.…”

Deep reinforcement learning based transmission policy enforcement and multi-hop routing in QoS aware LoRa IoT networks

“…Above equation represents the S ta , A ct and R ew for the allocated data parameters in the LoRa environment. Initially path of action and state of action is to find an optimum transmission policy that is given in eqn ( 18), then probability is find for the unknown state based on the previous state and action which given in eqn (19) and reward is given based on the action of the allocated parameters such as less S F, high C, high bw and CF. As QRank is considered in SAC, required level of QoS is ensured in terms of PRR and delay.…”

“…An increase in energy consumption directly degrades the performance of the overall network by decreasing the lifetime of IoTnodes. It is necessary to consider the energy consumption factor of each node in order to achieve an overall QoS level [18,19,20,21].…”

Honeycomb: An open-source distributed system for smart buildings

“…Ongaro proposed the Raft algorithm, 66 which solved the distributed consensus problem and tolerated failures of some nodes. Kadjouh proposed the DoTRo algorithm, 67 which can construct a spanning tree when electing the leader. The DoTRo algorithm is robust to node failures.…”