  Various types of communication networks are constantly emerging to improve
the connectivity services and facilitate the interconnection of various types
of devices. This involves the development of several technologies, such as
device-to-device communications, wireless sensor networks and vehicular
communications. The various services provided have heterogeneous requirements
on the quality metrics such as throughput, end-to-end latency and jitter.
Furthermore, different network technologies have inherently heterogeneous
restrictions on resources, e.g., power, interference management requirements,
computational capabilities, etc. As a result, different network operations such
as spectrum management, routing, power control and offloading need to be
performed differently. Mathematical optimization techniques have always been at
the heart of such design problems to formulate and propose computationally
efficient solution algorithms. One of the existing powerful techniques of
mathematical optimization is Benders decomposition (BD), which is the focus of
this article. Here, we briefly review different BD variants that have been
applied in various existing network types and different design problems. These
main variants are the classical, the combinatorial, the multi-stage, and the
generalized BD. We discuss compelling BD applications for various network types
including heterogeneous cellular networks, infrastructure wired wide area
networks, smart grids, wireless sensor networks, and wireless local area
networks. Mainly, our goal is to assist the readers in refining the motivation,
problem formulation, and methodology of this powerful optimization technique in
the context of future networks. We also discuss the BD challenges and the
prospective ways these can be addressed when applied to communication networks'
design problems.
