A Novel Approach to Cloud Load Balancing Using Advanced Migration Operator

WSN design improves energy efficiency and network scalability by organizing sensor nodes into clusters. Existing methods for addressing these challenges often require substantial processing and memory resources, limiting their practicality This paper proposes the Integrated Energy Efficient Clustering Protocol (IEECP), which aims to reduce and stabilize node energy consumption and to increase the lifespan of sensor networks. The method introduces a new algorithm for selecting and rotating cluster heads (CH) to optimal positions, and it integrates a strategy for energy consumption balancing among sensor nodes with the Grey Wolf Optimizer (GWO) algorithm. A back-off time mechanism is included for CH selection, and the IEECP algorithm uses a rotation mechanism to optimize CH placements. The strategy also combines the K-means clustering method with the GWO methodology to produce balanced-static clusters. The evaluation’s conclusions demonstrate that IEECP is superior to existing techniques and more effective. Improved clustering structure results in stabilized node energy consumption. The novel CH rotation and selection algorithms, together with the marriage of GWO and K-means, are some of the reasons behind the success of IEECP. Compared to previous system our proposed system produced better accuracy, sensitivity, specificity.