10 - Energy optimization in low-power wide area networks by using heuristic techniques

Abstract

Optimization problems are common in many fields and different domains of the human activities where we need to find optimal or near-optimal solutions for specific problems with the capability to meet some limitations. More specifically, optimization focuses on the development of efficient and powerful computing infrastructures that among others will be exploited so as to accelerate meta-heuristic techniques by significantly improving their performance. Thus, many heuristic algorithms have been developed for finding faster near-optimal solutions. Heuristic algorithms can quickly generate a solution with acceptable quality. The heuristics and meta-heuristics include the genetic algorithms, ant colony algorithm, the simulated annealing, gray wolf optimization, and so on. This chapter critically reviews various meta-heuristic optimization techniques used for energy optimization in wireless sensor network along with their detailed analysis, and evaluation on the basis of various parameters. The study and evaluation is useful in improving the performance of existing methods as well as helpful in the development of new methods.