Energy-balanced Clustering Routing Research Articles

A Distributed Unequal Clustering Routing Protocol Based on the Improved Sine Cosine Algorithm for WSN

In order to balance the overall energy consumption and improve the energy efficiency of wireless sensor network (WSN), a distributed energy-balanced unequal clustering routing protocol based on the improved sine cosine algorithm (DUCISCA) is proposed. Firstly, DUCISCA adopts a time-based cluster head competition algorithm. In this algorithm, the broadcast time depends on the residual energy of the candidate cluster head, the distance to the base station, and the number of neighbour nodes. Secondly, a competition radius considering the distance from node to base station and the residual energy of node is proposed. It can balance energy consumption of nodes in different locations to avoid the “hot spot” problem. At the same time, it adopts a time-based broadcast mechanism. The waiting time depends on the residual energy of CCHs, the distance to the BS, and the number of neighbour nodes, which can effectively reduce the overhead of nodes. Thirdly, the energy of cluster head, the number of neighbour nodes, and the distance from the ordinary node to the cluster heads need to be taken into account to get a better clustering result. Finally, in order to speed up convergence and improve the ability to jump out of local optimum, the improved sine-cosine algorithm (ISCA) based on Latin hypercube sampling and adaptive mutation is proposed. The improvement strategies adopted by ISCA are expressed as follows: Firstly, the diversity of the population is enhanced through LHS population initialization. Secondly, the adaptive weight strategy is introduced to accelerate the convergence speed of the algorithm. Finally, the population is disturbed by Gaussian mutation or Levy flight to jump out of the local optimum. The standard deviation of cluster heads’ residual energy in intercluster communication is taken as the objective function to search the energy-balanced intercluster data forwarding path based on ISCA. Compared with EEUC, DEBUC, I-EEUC, and M-DEBUC, the simulation results prove that DUCISCA can effectively balance the overall network energy consumption and prolong the network lifetime.

Real-Time Collection of Training Distance of Long-Distance Runners Based on Wireless Sensor Network

The real-time and accurate collection of long-distance runners’ training distance can provide real-time scientific basis for long-distance runners’ physical training. Therefore, the real-time collection method of long-distance runners’ training distance based on wireless sensor network is studied in this paper. In this model, the position tracking algorithm of long-distance runners based on wireless sensor network is introduced to collect the training distance of long-distance runners. When collecting the training distance, the energy balanced clustering routing algorithm based on energy and location is used to optimize and balance the energy consumption distribution of nodes and prolong the network life cycle, so that the training distance of long-distance runners can be collected in real time. Through the test, in the straight line and curve training path, this method has significant accuracy in collecting the training distance of single and multiple long-distance runners and can collect the training distance of long-distance runners in real time, which has significant application value.

Simplified clustering and improved intercluster cooperation approach for wireless sensor network energy balanced routing

The equilibrium use of energy is very important for wireless sensor networks (WSN) with limited energy in order to avoid premature network collapse. The existing methods either need too complex calculations for precise clustering, or are too simple to overburden a few cluster heads. In order to solve these problems, we proposed energy balanced clustering routing (EBCR) in this paper. It could maximize the WSN life in energy non-harvesting scenario or improve energy utilization efficiency in energy harvesting scenario without increasing the amount of calculations. It gives a complete solution to the process of cluster head election, clustering, and intercluster routing algorithm. Firstly, a light weight cluster head election and a distributed cluttering method are proposed by introducing dynamic cluster radius and intersection region node division schemes with new principles. Thus, lightweight distributed clustering achieves the advantages of balancing the burden of cluster heads and alleviating hot zone problem. Then we optimized the cluster cooperative routing algorithm by analyzing cooperation and competition among cluster heads. The intercluster cooperative routing algorithm greatly improves the transmission efficiency between cluster heads. Moreover, this paper analyzes the reasons why the algorithm achieves more balanced energy usage, higher energy efficiency, and fewer calculations compared to the existing mainstream algorithms. At last, simulation results show that EBCR algorithm has advantages in terms of network energy consumption, number of surviving nodes in energy non-harvesting scenario compared with the delay-constrained energy-efficient cluster-based multi-hop routing (DCEM) method. Simulation also gives EBCR algorithm performance under various energy harvesting scenarios, which is quite satisfactory in energy utilization efficiency comparing with DCEM method. EBCR algorithm has superior performance in terms of balanced energy usage, low computation complexity, and high energy efficiency.

Energy-balanced Adaptive Clustering Routing for Indoor Wireless Sensor Networks

Energy-balanced Adaptive Clustering Routing for Indoor Wireless Sensor Networks

Wireless Meter Reading Based Energy-Balanced Steady Clustering Routing Algorithm for Sensor Networks

According to the characteristics of wireless meter reading system, an energy-balanced and energy-efficient steady clustering routing algorithm (EBSC, Energy-Balanced Steady Clustering) ...