• A socioecological model for advanced service discovery in machine-to-machine communication networks

      Liu, Lu; Antonopoulos, Nikolaos; Zheng, Minghui; Zhan, Yongzhao; Ding, Zhijun; University of Derby; University of Derby, Derby, UK; University of Derby, Derby, UK; Hubei University for Nationalities, Enshi, China; Jiangsu University, Zhenjiang, China; et al. (Association for Computing Machinery, 2016-03-11)
      The new development of embedded systems has the potential to revolutionize our lives and will have a significant impact on future Internet of Thing (IoT) systems if required services can be automatically discovered and accessed at runtime in Machine-to-Machine (M2M) communication networks. It is a crucial task for devices to perform timely service discovery in a dynamic environment of IoTs. In this article, we propose a Socioecological Service Discovery (SESD) model for advanced service discovery in M2M communication networks. In the SESD network, each device can perform advanced service search to dynamically resolve complex enquires and autonomously support and co-operate with each other to quickly discover and self-configure any services available in M2M communication networks to deliver a real-time capability. The proposed model has been systematically evaluated and simulated in a dynamic M2M environment. The experiment results show that SESD can self-adapt and self-organize themselves in real time to generate higher flexibility and adaptability and achieve a better performance than the existing methods in terms of the number of discovered service and a better efficiency in terms of the number of discovered services per message.
    • Vehicular cloud networks: Architecture, applications and security issues

      Ahmad, Farhan; Kazim, Muhammad; Adnane, Asma; Abir, Awad; University of Derby, Derby, UK; Software Res. Inst., Athlone Inst. of Technol., Athlone, Ireland (IEEE, 2015-12-07)
      Vehicular Ad Hoc Networks (VANET) are the largest real life application of ad-hoc networks where nodes are represented via fast moving vehicles. This paper introduces the future emerging technology, i.e., Vehicular Cloud Networking (VCN) where vehicles and adjacent infrastructure merge with traditional internet clouds to offer different applications ranging from low sized applications to very complex applications. VCN is composed of three types of clouds: Vehicular cloud, Infrastructure cloud and traditional Back-End (IT) cloud. We introduced these clouds via a three tier architecture along with their operations and characteristics. We have proposed use cases of each cloud tier that explain how it is practically created and utilised while taking the vehicular mobility in consideration. Moreover, it is critical to ensure security, privacy and trust of VCN network and its assets. Therefore, to describe the security of VCN, we have provided an in-depth analysis of different threats related to each tier of VCN. The threats related to vehicular cloud and infrastructure cloud are categorized according to their assets, i.e., vehicles, adjacent infrastructure, wireless communication, vehicular messages, and vehicular cloud threats. Similarly, the Back-End cloud threats are categorized into data and network threats. The possible implications of these threats and their effects on various components of VCN are also explained in detail.