Optimal Sensor Association and Data Collection in Power Materials Warehouse Based on Internet of Things

In order to realize the intelligent management of a power materials warehouse, Internet Things based on wireless sensor networks (WSNs) is promising effective solution. Considering limited battery capacity nodes, optimization topology control and determination amount collected data are critical for prolonging survival time WSNs increasing satisfaction warehouse supplier. Therefore, in this paper, an problem association acquisition proposed, subproblem modeled as knapsack problem. To cope with it, block coordinate descent method used obtain suboptimal A scheme ant colony algorithm (ACO) upper lower bounds also obtained. After this, cluster head selection given find optimal head. Finally, experimental simulations show that algorithms proposed paper can effectively improve energy utilization ensure warehouse.