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Top1. Introduction
Nowadays more numbers of smart and sophisticated vehicles are moving on the road with numerous types of technical features. Each vehicle is embedded with the onboard unit (OBU), storage devices with a considerable amount of capacity, sensors, radars, radio trans-receivers, and a global positioning system (GPS). This makes the vehicle as a system on the wheel. Meanwhile, CC has shown a tremendous advancement in the building of dynamic cloud in mobile environments (Badger et al., 2012; Pande et al., 2016; Panda & Naik, 2018; Pande et al., 2020; Pande et al., 2021; Pande et al., 2021). The cloud introduces a provision for on-demand amenities of resources and facilities over the Internet as a service (Hayes, 2008). For example, Amazon Web Service (AWS), Microsoft Azure and IBM Cloud services are now the largest providers of dynamic assess capacity in the cloud. This heightening is asserted by expanding more attentiveness of businesses in renting cloud platforms instead of making and maintaining their own data centers (Armbrust et al., 2010). The significant features of CC are virtualization technology, quality of service, resources on request and adaptability towards changing demands of clients. The growing interest in its flexibility makes CC an attractive topic of interest in different technological fields.
One of the fascinated areas of research where the CC concept can be utilized is vehicular networks. In this scenario, the concept of vehicular cloudlet has been represented. It consists of a bunch of vehicles that share available resources among vehicle to vehicle (V2V), vehicle to infrastructure (V2I), vehicle to devices (V2D) and vehicle to pedestrian (V2P) communications. A vehicular cloudlet is categorized into two types. One is a mobile cloudlet and another one is a static cloudlet. Mobile cloudlet, which consists of moving vehicles, is realized on-road environment. Static cloudlet is formed by considering stationary vehicles like vehicles on the parking lot (Abdelhamid et al., 2017; Baby et al., 2013). Each type of cloudlet uses different vehicular cloud services depending upon the mobility of the cloud elements. Figure 1 depicts vehicular cloudlets in the dynamic and static situation and communication in vehicular networks. According to the current scenario, the world’s most big cities face terrible traffic congestion issues due to the increase in the volume of vehicles on the roads. This has driven cities to awful situations, distressing driving experiences and unacceptable urban conditions. In comparison to the mobile environment, the cloudlet comprising of static parked vehicles establishes to be comparatively stable as per computing of tasks, data storage and supplying resources for traditional cloud assistance (Hussain & Beg, 2019). VCC, which has been emerged from VANETs, becomes a very appealing technology because of its characteristics in dealing with many unique, applicable, or sensitive applications. As illustrated in Figure 2, VCC is recognized as the assembly of two paradigms, one is the vehicular network and another one is CC. VANETs paradigm, which has been developed from the mobile ad-hoc network (MANET), is an essential part of the intelligent transport systems in which communication between nodes is based on the single hop or multiple hops. It has shown increasing growth in popularity with advanced technological features and solutions to support a vast range of applications to provide V2V and V2I communications (Abdelhamid et al., 2017; Ma et al., 2010; Papadimitratos et al., 2009; Amadeo et al.,2016; Silva et al., 2016).
Figure 1.
Vehicular cloudlet in dynamic and static environment