Energy Efficient Resource Allocation Scheme via Auction-Based Offloading in Next-Generation Heterogeneous Networks

Energy Efficient Resource Allocation Scheme via Auction-Based Offloading in Next-Generation Heterogeneous Networks

Alexandra Bousia (University of Thessaly, Greece)
DOI: 10.4018/978-1-5225-2023-8.ch008
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Abstract

The focus of this chapter is centered on the network underutilization during low traffic periods (e.g., night zone), which enables the Mobile Network Operators (MNOs) to save energy by having their traffic served by third-party Small Cells (SCs), thus being able to switch off their Base Stations(BSs). In this chapter, a novel market approach is proposed to foster the opportunistic utilization of unexploited SCs capacity, where the MNOs lease the resources of third-party SCs and deactivate their BSs. Motivated by the conflicting interests of the MNOs and the restricted capacity of the SCs, we introduce a combinatorial auction framework. A multiobjective framework is formulated and a greedy auction algorithm is given to provide an energy efficient solution for the resource allocation problem within polynomial time. In addition, an extensive mathematical analysis is given for the calculation of the SCs cost, which is useful in the market framework. Finally, extended experimental results to estimate the potential energy and cost savings are provided.
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Introduction

During the last few years, the rapid and radical evolution of mobile telecommunication services along with the emerging demand for multimedia applications due to the widespread use of laptops, tablets and smart-phones have led to a growing demand for data transmission. The traffic load is experiencing a growing increase by the factor of 10 every 5 years approximately (Global Action Plan, 2012; Cisco, 2015). Overall mobile data traffic is expected to reach 24.3 exabytes per month by 2019, a 13- fold increase and at a Compound Annual Growth Rate (CAGR) of 57% from 2014 to 2019 (Cisco, 2015). The mobile applications, in particular, are expected to grow in staggering rates, with mobile video showing the higher growth and getting up to 66.5%. Thus, the increasingly expanding market of web-enabled mobile devices opens the path towards a wide range of previously unimagined (data- based) applications and creates the need for ubiquitous availability of Internet (better coverage) and faster broadband connections (higher Quality of Service (QoS)) (Loozen, Murdoch, & Orr, 2013).

In order to tackle with the challenges of future mobile networks and handle the predicted increase in mobile traffic volume, operators face the need to expand their wireless infrastructure. The telecommunications companies work towards the massive deployment of their networks. At this point, it is highlighted that there were more than 8 million Base Stations (BSs) deployed and serving mobile users in 2012 (Correia et al., 2012). Let us point out here that the largest mobile telecommunications operators may maintain approximately 238000 BS sites worldwide (Vodafone Group, 2012). Moreover, the number of deployed BSs grows as the users requirements increase every year. Furthermore, Wi-Fi Access Points (APs) and third-party Small Cells (SCs), such as picocells, femtocells and mircocells, are extensively deployed in public and private areas, such as university campuses, business parks, and user homes during the last decade, introducing the trend of Heterogeneous Networks (HetNets). However, these deployments may lead to increase in energy consumption because of the extra cells that are also underutilized some hours of the day when the traffic load is low. Nevertheless, by introducing sleep mode in BSs, heterogeneous cellular networks can outperform traditional macro-cell-only networks in terms of energy efficiency.

In this chapter, motivated by the aforementioned issues and in order to foster the utilization of unexploited Internet connections, a new and open market is proposed, where a Mobile Network Operator (MNO) can lease the bandwidth made available by a third-party company through its SCs to switch off the BS and save large amounts of energy under low traffic conditions (guaranteeing the QoS constraints). Since the SCs capacity is limited, the proposal of the chapter considers the diverse predilections of each MNO. On the other hand, the third-party wants to maximize its income by leasing its capacity to the MNOs, a goal that may contradict the MNOs’ tendency to save energy. Specifically, an operator is willing to lease capacity provided that its whole traffic can be offloaded, whereas the third-party may prefer to lease its resources to different MNOs, hindering the deactivation of the BSs. To that end, the offloading problem is formulated as a reverse auction. At this point, it is highlighted that the SC network cost is mathematically analyzed, as well. The main contributions of this work are summarized below:

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