Dandelion-Encoded Harmony Search Heuristics for Opportunistic Traffic Offloading in Synthetically Modeled Mobile Networks

Abstract

The high data volumes being managed by and transferred through mobile networks in the last few years are the main rationale for the upsurge of research aimed at finding efficient technical means to offload exceeding traffic to alternative communication infrastructures with higher transmission bandwidths. This idea is solidly buttressed by the proliferation of short-range wireless communication technologies (e.g. mobile devices with multiple radio interfaces), which can be conceived as available opportunistic hotspots to which the operator can reroute exceeding network traffic depending on the contractual clauses of the owner at hand. Furthermore, by offloading to such hotspots a higher effective coverage can be attained by those operators providing both mobile and fixed telecommunication services. In this context, the operator must decide if data generated by its users will be sent over conventional 4G+/4G/3G communication links, or if they will instead be offloaded to nearby opportunistic networks assuming a contractual cost penalty. Mathematically speaking, this problem can be formulated as a spanning tree optimization subject to cost-performance criteria and coverage constraints. This paper will elaborate on the efficient solving of this optimization paradigm by means of the Harmony Search meta-heuristic algorithm and the so-called Dandelion solution encoding, the latter allowing for the use of conventional meta-heuristic operators maximally preserving the locality of tree representations. The manuscript will discuss the obtained simulation results over different synthetically modeled setups of the underlying communication scenario and contractual clauses of the users.

An Analysis of Coalition-Competition Pricing Strategies for Multi-operator Mobile Traffic Offloading Using Bi-objective Heuristics

“…The Dandelion code is a bijective mapping between a tree network topology of M + N + 1 nodes and an integer string with length M + N − 1. This code has several properties in terms of inheritance and locality that make it suitable for tackling tree optimization problems by means of Evolutionary Algorithms [19], particularly in telecommunications [20][21][22]. A brief explanation of the encoding and decoding processes is now given:…”