FellowMe Cache: Fog Computing approach to enhance (QoE) in Internet of Vehicles

Highlights

• ICN can enable the in-network caching in intermediate nodes and servers and SDN facilitates the design and administration of network services.

• The storage of requested content near the end user reduces delay and cost transmission.

• The best choice of the cache nodes can more enhance the QoE.

• The selection of cache nodes is based on the factor influence metric that takes into account the ZI, the link quality between nodes, the user preference and the connectivity degree of each node.

Abstract

Among metrics that highly affect video quality and quality of experience (QoE), we can cite the delay and cost transmission caused by mobile network overhead. Moreover, Information centric networking (ICN) is a new architecture that is proposed as a technique that offers very high throughput rates and very low latency, especially in QoE sensitive applications such as multimedia content delivery for the future communication networks. Indeed, unused memory in user equipment can be used to cache contents and afford it to the other nearby users on demand. This caching method is considered as one of the most promising solutions to enhance the QoE of users. On the other hand, one of the major research goals is to improve caching nodes decision based on nodes’ characteristics. In this paper, we propose a new programmable architecture named FollowMeCache based on Software Defined Network (SDN), ICN approaches and Fog Computing for cache node selection using the Connected Dominating Sets (CDS) in order to reduce the download delay and cost for the users’ requested video. In fact, we define cache node selection algorithm based on Influence factor to elect the appropriate nodes from the CDS set to build the cache. This metric takes into consideration the connectivity degree, Zone of Interest (ZI), node capacity, user preference and its location. In order to evaluate the proposed solution, we define a smart event use case. The performance evaluation is conducted by using network simulator and the obtained results show that our approach can give significant gain in terms of network throughput and the transmission delay.

Introduction

With the increasing growth of the Internet of things (IoT) [1], there will be tens of billions of connected devices. These connected devices will have sensing and intelligent capabilities for communication, collecting data and collaboration. As a typical example of IoT, we can cite Internet of Vehicle (IoV) [2], [3] based on sharing ubiquitous information and content such as location tracking, remote monitoring…between vehicles with little or no human intervention. Device-to-device (D2D) communication [4] to deliver requested content without using the cellular network, can be considered as an attractive solution for future IoV networks. Vehicle to Vehicle communication (V2V) [5] and D2D can significantly offload network traffic and enhance its performance [6], [7]. Indeed, V2V/D2D communications are a direct communication between two mobile vehicles without the use of a base station (BS) or a telecommunications network: The new features of mobile users today such as large storage capacity, computational power, long battery life, GPS location functions, as well as heterogeneous wireless interfaces such as WIFI, cellular, and Bluetooth... allow them to play a more active role in content distributions rather than simply being a passive device for consuming mobile data [8]. Therefore mobility [9], [10] can help the nodes to improve the energy efficiency of the network.

On the other hand, there has been a new emerging trend in integrating ICN and SDN together in the future research field [11]. ICN [12] is a novel architecture that is proposed as a technique which has the potential to get a very high throughput rate and very low latency, especially in QoE sensitive applications such as multimedia content delivery for the future communication networks [13]. ICN is defined as a communication paradigm that aims to replace current IP networks [14]. In ICN, a node broadcasts its interest in content/information by using the name of this content. Each node in the network can respond, to this interest, if it has the requested content, which makes content independent of a specific node (address) in the network [15]. This is achieved by allowing nodes to store information when transferring information from the interests/responses between a source and a destination. Also, ICN has been proposed as a promising solution for IoT scenarios [1], [15]. Besides, SDN separates the data and control planes and introduces flexible programmability to network equipment, which facilitates the design, management and administration of network services.

In this paper, we focus on the dissemination and data transmission in vehicular networks while reducing the communication cost in terms of overhead, energy and cellular traffic. This environment is possible via the vehicular heterogeneous networks where vehicles (devices) are equipped with both cellular and non cellular communication interfaces. In order to connect vehicles to Internet with minimum cellular traffic and cost. We present an hybrid and pro active architecture FollowMeCahce based on SDN and ICN approaches and CDS algorithm [16]. It is very important to propose an hybrid architecture to consider the different technologies’ characteristics (licensed such as D2D communication in 5G, Machine-Type Communication (MTC) and unlicensed like IEEE802.11 (WiFi), IEEE802.15.1 (Bluetooth)...) and to ensure their coexistence. Besides, we rely on Fog Computing in our approach to be closer to the IoT devices/sensors and extends the Cloud-based computing, storage and networking facilities [17].

The main contribution of this work is as follow: mobile content objects will be carried by mobile devices and spread around to nearby interested consumers directly without engaging the cellular infrastructure in the data plane. In this case, mobile devices will be considered as an integral part of the mobile network with their own contribution of resources to serve other users. The advantage here is to effectively save the most expensive cellular spectrum resources via offloading to V2V based communications in support of content delivery. For that, in order to focus on the best choice of cache nodes and optimize network performance, we rely on FollowMeCache approach and we propose cache node selection algorithm (CNS) to create virtual Backbone (VB) [16], [18] and select the most appropriate cache nodes based on influence factor metric. In other words, VB nodes distributed in the zone of interest ZI having a high degree of connectivity and high quality link with other mobile nodes, thus they have a high probability to be the cache nodes of our system.

The rest of the paper is organized as follows: we present a brief overview of the existing caching strategies in Section 2. In Section 3, we describe the proposed hybrid and programmable FollowMeCache architecture, its different modules and their interaction. In Section 4, we present the cache nodes selection mechanism used with the CDS algorithm, and the Influence Factor metric. In Section 5, we discuss and analyze the obtained simulation results to evaluate the performance of the proposed solution applied to an IoV use case. Finally, the conclusion is addressed in the last section. A schematic overview of the main body is provided in Fig. 1 to help understand the logic of the paper.