A Survey of Anticipatory Mobile Networking: Context-Based Classification, Prediction Methodologies, and Optimization Techniques

TL;DR

This survey reviews recent advances in anticipatory mobile networking, focusing on context-based classification, prediction methodologies, and optimization techniques to enhance network performance by forecasting future conditions.

Contribution

It systematically analyzes existing prediction and optimization tools in anticipatory networking and links them with application objectives and challenges.

Findings

Identification of key prediction techniques used in anticipatory networking

Analysis of optimization strategies aligned with network scenarios

Discussion of open challenges and future research directions

Abstract

A growing trend for information technology is to not just react to changes, but anticipate them as much as possible. This paradigm made modern solutions, such as recommendation systems, a ubiquitous presence in today's digital transactions. Anticipatory networking extends the idea to communication technologies by studying patterns and periodicity in human behavior and network dynamics to optimize network performance. This survey collects and analyzes recent papers leveraging context information to forecast the evolution of network conditions and, in turn, to improve network performance. In particular, we identify the main prediction and optimization tools adopted in this body of work and link them with objectives and constraints of the typical applications and scenarios. Finally, we consider open challenges and research directions to make anticipatory networking part of next generation networks.