The impact of node velocity diversity on mobile opportunistic network performance

Abstract

Mobile opportunistic network is a special kind of mobile ad hoc networks, in which nodes can communicate and interact with each other without a fixed communication infrastructure. Data dissemination between nodes utilizes a store-carry-forward paradigm. In this paper, we explore the impact of node velocity diversity on the performance of mobile opportunistic networks while keeping the average velocity of nodes consistent with each other. The numerical results indicate that greater node velocity diversity always implies longer average communication and the smaller number of communications within the constant total communication time. Thus, it is important to improve the performance of mobile opportunistic networks by adjusting the velocity diversity in response to the requirement of the network and in order to make full use of communication resources. In particular, we construct mathematical models to analyze node contact times and link numbers. Lastly, we verify the correctness of models and theories we proposed by using the Opportunistic Network Environment simulator.

Introduction

With the rapid growth of wireless communications and integrated circuits, various portal smart devices, such as portable computers, smart phones and PDAs, have been more and more popular. These portal smart devices carried by moving humans may organize into a Delay Tolerant Network (DTN) (Hui et al., 2011, Soares et al., 2014). Similar to the traditional Mobile Ad hoc Networks (MANETs) (Rodríguez-Covili et al., 2012, Varaprasad et al., 2008), there is no fixed infrastructures in such DTNs, in which the nodes communicate with each other by utilizing their contract opportunities and depending on short-distance wireless links, like Wi-Fi or Bluetooth. Due to sparse deployment and moving randomness of nodes, the network topology changes frequently, leading to no end-to-end path between the source node and the destination at any time. Therefore, once receiving a message, a node usually stores it in its buffer, carries it while moving, and forwards it to other encountered nodes until the message reaches the destination (Cacciapuoti et al., 2013). Due to the moving randomness of nodes, communication opportunities between nodes become unpredictable. So DTNs are also called Mobile Opportunistic Networks (MONs) (Pirozmand et al., 2014). MONs can deal with the problems like network segmentation, long time delay and so on, which are difficult for the existing network technologies to solve. So MONs have been applied in many areas, such as emergency response communications, vehicle networks, environmental monitoring, wildlife tracking and sociality-aware advertisements. MONs have got deep attention from academic field and industrial area (Martín-Campillo and Martí, 2012, Martín-Campillo et al., 2013).

In MONs, nodes take the store-carry-forward mechanism to deliver messages. And the path between the source node and the destination which is based on hop by hop opportunistic contacts changes dynamically due to the mobility of nodes. A node may deliver a message to its destination node even if there is no path between the source and the destination currently. Therefore, the opportunistic contacts and communications become more and more critical. However, opportunistic contacts are closely related to the mobility model which is used to describe node movement patterns and includes the change of node׳s location, direction, speed and acceleration (Zhang et al., 2013, Luo et al., 2013). Nowadays, the researches on mobility model in MONs are in full swing, and related investigations mainly focus on creating mobility models to realize more realistic description of node movement patterns (Chung and Go, 2012). Therefore, how to make better use of opportunistic contacts between nodes by analyzing the regularities of node contacts which are obtained from moving process in the real world, how to get more contact opportunities or more communication time to a certain extent, and how to make a valuable communication with faster and more reliable performance have become the key challenges in mobile opportunistic networks. But it is very difficult to deal with these problems because of the unpredictable mobility of nodes in MONs.

Our main contributions are summarized as follows. Firstly, we propose a new concept and measuring standard for velocity diversity which indicates the difference between nodes׳ velocity. Secondly, we utilize several mathematical models and frameworks to analyze the communication time and the communication frequency between nodes under random mobility model. Thirdly, we analyze the impact of node velocity diversity on network performance while keeping the average velocity of nodes consistent with each other. Through theoretical analysis and extensive simulations, we find that greater node velocity diversity implies longer expected communication time and smaller expected number of communications, while the total communication time in the network would keep constant. According to these conclusions, we can not only improve the network performance by adjusting the velocity diversity in response to the requirement of the network, but also take full advantages of communication resources to transmit messages in MONs.

The rest of this paper is organized as follows. In Section 2, we review the previous work in this area. We describe nodes movement features under different random mobility models that we will use later, and put forward the velocity diversity in Section 3. In Section 4, we develop mathematical models to calculate the average communication time and analyze the impact of node׳s velocity diversity on network performance. We propose mathematical models to calculate the number of communications and the total communication time in Section 5. In Section 6, we validate our theoretical results by extensive simulations. We conclude this paper in Section 7 with a brief summary and an outline of future work.