Big Data Optimization Within Real World Monitoring Constraints

Abstract

Large scale monitoring systems can provide information to decision makers. As the available measurement data grows, the need for available and reliable interpretation also grows. To this, as decision makers require the timely arrival of information, the need for high performance interpretation of measurement data also grows. Big Data optimization techniques can enable designers and engineers to realize large scale monitoring systems in real life, by allowing these systems to comply to real world constrains in the area of performance, reliability and reliability. Using several examples of real world monitoring systems this chapter discusses different approaches in optimization: data, analysis, system architecture and goal oriented optimization.