Real Time Services for Cloud Computing Enabled Vehicle Networks

G.sasikala G.sasikala
2013 IOSR Journal of Computer Engineering  
Cloud computing technique is gaining more and more popularity recently. It can be applied to the vehicle applications to ensure real time performance as well as to improve accuracy and comfort degree for drivers. In this paper, we propose our novel vehicle cloud architecture which includes device level, communication level and service level. Each of these levels is explained in further detail with flow chart and taxonomy definition. Some innovative and real time vehicle cloud services are
more » ... uced to show the wide potential applications of vehicles and some discussion about research challenges, context classification is also provided. I. Introduction With the fast development of automotive industry as well as Information and Communication Technology (ITC), our daily lives have been largely influenced and people tend to spend more and more time relevant to vehicles. It can be foreseen that the next generation transportation system will become a more powerful system by utilizing existing ommunication, network and computer infrastructure. Currently one of the challenging issues to the road transportation system is the traffic congestion, which causes huge amount of financial and human life cost. In the United States alone, there is a loss of $78 billion with 4.2 billion lost hours and 2.9 billion gallons lost of wasted gasoline in 2007 [1] , not to mention about car accident with human casualty Intelligent Transportation System (ITS) [2-4] has been developed to monitor traffic information, to reduce car accident, to alleviate workload of drivers and to improve their comfort degree. Usually, GPS-based devices, video camera, as well as other road side units (RSU) and road side infrastructure (RSI) are utilized in parallel with ITS deployment. In fact, vehicle is a very complex integrated system with mechanical system, computing and communication systems. On the one hand, all in-car vehicle resources (like CPU, memory, power, and communication units) need harmonious scheduling to achieve optimal efficiency. Also the sensor and actuator devices need to closely work with each other. On the other hand, each vehicle needs to cooperate with other vehicles or RSI in a vehicle-to-vehicle (V2V) or vehicle-toinfrastructure (V2I) manner in order to share and utilize external resources in a more effective way. To facilitate the interaction between vehicle drivers and outside car world, a novel vehicle cloud (V-Cloud) architecture with real time services is proposed in this article. The concept of cloud computing (CC) is presented from economical point of view and the key idea is to rent the software, platform and services rather than to buy them [5] . There are three types of cloud computing services, namely 1) Infrastructure as a Service (IaaS) where cloud providers provide their customers with storage, processing and network resources; 2) Platform as a Service (PaaS) where the development tools are hosted in the cloud and accessed through a browser; 3) Software as a Service (SaaS) where the provider provide customers with application services in a pay-as-you-go manner. The contribution of this article includes: 1) we propose a novel three tier V-Cloud architecture with detail explanation of each tier; 2) we provide detailed analysis and discussion about some sub-tier issues such as body area sensor network (BASN), context-aware middleware module etc. The flow chart and relevant taxonomy if also given; 3) we present some innovative and real time services for future cloud vehicle applications II. Related Work In recent years, vehicles are equipped with smart phone devices with more powerful sensing, communication and processing capabilities. In [6] the authors the authors propose a VTrack system by using mobile phone in order to improve energy efficiency and sensor unreliability. They use hidden Real Time Services for Cloud Computing Enabled Vehicle Networks www.iosrjournals.org processing, if the driver's heart rate is higher than a pre-defined threshold, a warning message or sound will be sent or vibrating chair will be initiated to remind driver. The car will even get stopped under urgent situations. On the right side of Tier-1 in Figure 1 are some portable devices with more flexibility and stronger capabilities. By using GPS localization technique, drivers can reduce their time on road and administrative centers can schedule vehicles (like bus, taxi) in a more efficient way especially during rush hours. Smart phone can largely enhance driver's comfort and convenience degree based on its strong sensing, processing and communication functions. More importantly, some customized application can be developed to interact with the Internet and other BASN devices like bio-sensors and video sensors etc. PC-based devices like in-car navigator can provide very friendly and interactive interface to users and they can enjoy various services such as road traffic monitoring, entertainment (audio, video, TV), Internet and resource sharing with other vehicles. Other devices like Bluetooth, WiFi can provide additional support and services to drivers based on their standard communication interface. C. Tier-2: Communication Level Due to the fast development of IT technology such as wireless communication, networking and signal processing techniques in the last decades of years, there are various alternatives for drivers to communicate with the outside world Figure 3 gives the classification of our proposed V-Cloud communication taxonomy in Tier-2. Based on the communication objects, communication level in Tiere-2 can be further divided into in-car communication module, vehicle-tovehicle (V2V) communication module and vehicle-toinfrastructure (V2I) communication module. The tier-2 module in Figure 1 mainly shows the V2I sub-module which includes the communication with satellite network, 3G wireless network and Internet. The in-car communication between different types of sensors, actuators and intelligent devices is mentioned in Section 3.2 with special focus on BASN.
doi:10.9790/0661-1110814 fatcat:hu323wqa35avhmjjlc4o3bamla