Article Preview
TopIntroduction
With the wide application and long-term development of network, cloud computing technology has become mature gradually, technologies like virtualization, distributed processing, data processing and cloud storage are also making it more comprehensive and perfect (Zissis & Lekkas, 2011, Jing & Fortes, 2010, Al-Rousan, 2015). Cloud computing applied in traffic system, has brought significant economic and social benefits, many countries including America, Europe and Japan have already integrated it into the development strategy of intelligent traffic system (Armbrust et al. 2010, Kim, Kyong Hoon, et al. 2011, Ismail, 2011, Menzel & Ranjan, 2012). As a result, the wide application of cloud computing technology in the field of traffic and the establishment of traffic cloud data center has become an irreversible trend.
Based on the current construction situation of traffic system in our country, this paper integrates SOA with distributed cloud data center building technology of cloud computing, takes advantage of open-source virtualization technology OpenStack to build the framework of the whole traffic cloud data center (Yao et al., 2012, Ma, 2011, Azeez et al., 2010, Li & Svard, 2010). Moreover, by taking Beijing Municipal Committee of Transport (BMCT)’s cloud data center establishment as an example, incorporated with DENS algorithm, it can overcome the obstacles in terms of unified management, business collaboration and resources allocation among BMCT’s data center and its sub-centers (Azeez, Perera, 2010, Feuerlicht, 2010, Kliazovich et al., 2010).
SOA (Service-oriented Application) is an architectural model applying its components’ services to others by using communications protocols or networks including standardized service contract, service loose coupling, abstraction, reusability, autonomy, compensability and granularity. Previous scholars focused on model-driven development (Ameller, et al., 2015), quality-driven approach (Teixeira et al., 2015) and some applications on cloud computing paradigm (Valilai & Houshmand, 2013), cost-effective data farming (Król & Kitowski, 2016), and ensemble flood forecast (Shi et al., 2015). Recently, it is also widely used in cloud computing; Geerts & O'Leary (2015) presented an architecture for integrating cloud computing and enterprise systems based on the Resource-Event-Agent (REA) model in RosettaNet system and showed different characteristics of the approach; Li et al., 2016 proposed service-oriented mobile cloud computing model in a flexible service provisioning method based on context constraint, and Barry & Dick (2013) introduced Savvy Manager’s Guides of Service-Oriented Architectures, and Cloud Computing.