In energy-constrained wireless sensor networks, low energy utilization and unbalanced energy distribution are seriously affecting the operation of the network. Therefore, efficient and reasonable routing algorithms are needed to achieve higher Quality of Service (QoS). For the Dempster–Shafer (DS) evidence theory, it can fuse multiple attributes of sensor nodes with reasonable theoretical deduction and has low demand for prior knowledge. Based on the above, we propose an energy efficient and reliable routing algorithm based on DS evidence theory (DS-EERA). First, DS-EERA establishes three attribute indexes as the evidence under considering the neighboring nodes’ residual energy, traffic, the closeness of its path to the shortest path, etc. Then we adopt the entropy weight method to objectively determine the weight of three indexes. After establishing the basic probability assignment (BPA) function, the fusion rule of DS evidence theory is applied to fuse the BPA function of each index value to select the next hop. Finally, each node in the network transmits data through this routing strategy. Theoretical analysis and simulation results show that DS-EERA is promising, which can effectively prolong the network lifetime. Meanwhile, it can also reach a lower packet loss rate and improve the reliability of data transmission.
Along with the increasing demands for the applications running on the wireless sensor network (WSN), energy consumption and congestion become two main problems to be resolved urgently. However, in most scenes, these two problems aren't considered simultaneously. To address this issue, in this paper a solution that sufficiently maintains energy efficiency and congestion control for energy-harvesting WSNs is presented. We first construct a queuing network model to detect the congestion degree of nodes. Then with the help of the principle of flow rate in hydraulics, an optimizing routing algorithm based on congestion control (CCOR) is proposed. The CCOR algorithm is designed by constructing two functions named link gradient and traffic radius based on node locations and service rate of packets. Finally, the route selection probabilities for each path are allocated according to the link flow rates. The simulation results show that the proposed solution significantly decreases the packet loss rate and maintains high energy efficiency under different traffic load.
The network lifetime of wireless rechargeable sensor network (WRSN) is commonly extended through routing strategy or wireless charging technology. In this paper, we propose an optimization algorithm from the aspects of both charging and routing process. To balance the network energy in charging part, node’s charging efficiency is balanced by dynamically planning charging point positions and the charging time is allocated according to the energy consumption rate of nodes. Moreover, the routing method is adapted to the node’s charging efficiency. The adaptive routing strategy assigns more forwarding tasks to nodes that can get more energy during the charging phase, and makes the data packets transmit farther away, thus reducing the average hops and energy consumption of the network. Finally, the simulation results reveal that the proposed algorithm has certain advantages in prolonging the network lifetime, reducing the average hop counts and balancing the energy of each node.
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