Heuristics to Optimize the Reading of Railway Sensors Data

For real-time systems, time optimizing without increasing the complexity of the system and the applications it relies on is a very challenging problem. Using revised algorithms, the authors propose an improved approach that utilizes the read frequency rate of the data sent by railway track sensors. The track sensors send frequently the captured data to a database in the control unit of the railway monitoring system. The received data will be saved in the database in a table called the DC table. The main question is: How the system can read a maximum number of saved data from the DC table within a predefined time limit? This is an NP-hard problem, and the best solution is to read all DC saved data, while the worst case is to read minimal or no data. For this based problem a new approach was proposed. This approach is based on the separated periods and the jobs algorithm (SPJ) and is demonstrated by six heuristics (LPT, SPT, MF, SS, MSS, and MSK). Experimental results showed that there is no dominance among the implemented six heuristics, heuristic with best results is that based on knapsack problem.