Saving Energy with QoS for Vehicular Communication Hamdi Idjmayyel, Wanod Kumar, Bilal R. Qazi, Jaafar M. H. Elmirghani School of Electronic and Electrical Engineering, University of Leeds, UK {een5hi, elwk, b.r.qazi, j.m.h.elmirghani}@leeds.ac.uk Abstract With the rapid growth of high data rate applications, significant amount of energy is consumed by base stations’ equipment. In order to save energy, it is better to deploy fewer base stations (BSs) or switch off as many as possible. However, this is usually attained at the expense of quality of service (QoS). In this paper, we deploy fewer BSs to reduce energy consumption and study the performance of two routing protocols using our vehicular city simulator to fulfil the QoS. While working in the ad hoc mode, we illustrate that it is important to put the maximum number of vehicular nodes into sleeping mode to save energy. To achieve this, we propose a new clustering scheme where only cluster heads (CHs) can perform out of range communication. Our simulation results prove that we can save up to 2 times the energy compared to the fully operational vehicle-to-roadside (V2R) scenario and up to 9 times compared to other routing scheme while achieving an acceptable QoS. I. INTRODUCTION With the unprecedented growth of service requirements, improving the quality of service (QoS) has been a primary concern in research. Communication networks heavily contribute to the global power consumption these days and their contribution is expected to increase rapidly in the future. As the size of network and users increase, energy efficient system design has received attention from both industry and academia. Therefore there is a need to design systems with lower energy consumption while fulfilling the QoS requirements especially in dynamic environments such as vehicular networks. During the past decades, a lot of effort has been put to improve the network throughput, such as optimisation of the number of base stations. However, high network throughput is associated with high energy consumption, which is usually unaffordable for energy-aware networks. Furthermore, Information and communication technology (ICT) is playing an important role in increasing the carbon footprints. According to [1], the total carbon footprint of the ICT sector in 2007 was estimated as 2% of global carbon emissions with a predicted 6% yearly increase until 2020. Moreover, 37% of the power is consumed by equipment use with telecom infrastructure and devices, while only a quarter of the power use can be attributed to manufacturing; data centres and user terminals account for the rest [2]. This has led to an increased drive for energy efficient mobile networks [1-2] while achieving the required QoS. In a centralised network, base stations consume the most energy compared to other network equipments, hence, research has focused on energy efficient base station deployment strategies [3]. The use of energy aware components with higher efficiencies and load adaptive hardware in addition to software modules in the base stations is among the methods proposed for reducing energy consumption [3]. Since base stations’ hardware consume around 80% of the power [4], we in this paper reduce the energy consumption by minimising the number of base stations while attaining the required QoS. This is achieved by studying different routing schemes where the base station coverage is not present. We have also incorporated a physical layer model to offer a more realistic representation of the communication layer which allows a precise evaluation of the system’s QoS and energy performance. Following the introduction the paper is organised as follows: The background and related work are reviewed in Section II. Section III describes the proposed scenario and the routing protocols investigated. Section IV outlines the system model, physical layer parameters and energy evaluation. The results are analysed in Section V and the paper concludes with Section VI. II. RELATED WORK Routing schemes for vehicle-to-vehicle (V2V) communications have been extensively studied [4-10]. Multi-hop communications is a practical approach to provide end to end services. However, most of the multi-hop routing protocols are flooding-based such as epidemic routing [5], where a lot of unnecessary packets are replicated which result in wasting energy and network resources. In [6], the authors presented a clustering scheme for vehicular ad hoc networks where the nodes are grouped into clusters according to their geographical positions, keeping track of the priorities associated with vehicular traffic information. The communication overhead of some proactive routing protocols increases with the square of the number of nodes in the network [7]. Hence, in order to overcome the scalability problem, a hierarchical routing mechanism is employed which groups the nodes according to specific requirements to allow efficient routing [8]. This technique considerably reduces the size of the routing table compared to other proactive routing schemes such as Destination Sequence Distance Vector (DSDV) routing [9] in which each node should maintain and frequently update its routing table [10]. The Scalability is notably enhanced and the routing overhead is appreciably decreased [11]. Cluster based techniques make a virtual infrastructure in the form of clusters where the nodes in each clusters are sorted based on their characteristics such as location and speed [12]. To the best of our knowledge, very little work has been undertaken on energy efficiency with respect to QoS in a vehicular network. In this paper, we determine the total network energy consumed by proposing comprehensive physical propagation and energy models while calculating the QoS for real-time services in a vehicular network. Using our city simulator [13] we put five of the nine fully functional base stations into sleep mode to save considerable amount of energy and show the impact on QoS. Moreover, an ad hoc setup, consisting of multi- hop routing scheme and our proposed cluster based protocol, is introduced which restores the performance however a trade-off between different QoS parameters and energy is extensively studied. III. SYSTEM MODEL A. The proposed scenario The proposed setup is based on a 3 × 3 m ଶ city scenario with 48 roads and 16 junctions [13]. To illustrate the difference in terms of QoS parameters and energy expenditure, two pure V2R scenarios are proposed, the first one offer full coverage with 9 base stations whereas the other employs 4 base stations. While working under the 4 base stations scenario, a considerable amount of energy is saved, though, this is achieved at the expense of QoS parameters. Figure 1 shows the location of the base stations. Furthermore, a buffer size of 100 messages for vehicular nodes is utilised. The communication ranges for vehicle-to- vehicle (V2V) and vehicle-to-roadside (V2R) are set to 200 m and