Resource Allocation in Vehicular Cloud Computing Systems With Heterogeneous Vehicles and Roadside Units

2018 ◽  
Vol 5 (5) ◽  
pp. 3692-3700 ◽  
Author(s):  
Chun-Cheng Lin ◽  
Der-Jiunn Deng ◽  
Chia-Chi Yao
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Computing Systems ◽  
Vehicular Cloud Computing ◽  
Vehicular Cloud

An SMDP-Based Resource Allocation in Vehicular Cloud Computing Systems

2015 ◽  
Vol 62 (12) ◽  
pp. 7920-7928 ◽  
Author(s):  
Kan Zheng ◽  
Hanlin Meng ◽  
Periklis Chatzimisios ◽  
Lei Lei ◽  
Xuemin Shen
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Computing Systems ◽  
Vehicular Cloud Computing ◽  
Vehicular Cloud

scholarly journals A Safety Resource Allocation Mechanism against Connection Fault for Vehicular Cloud Computing

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Tianpeng Ye ◽  
Zhou Su ◽  
Jun Wu ◽  
Longhua Guo ◽  
Jianhua Li ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Real Time ◽  
Traffic Control ◽  
Intelligent Transportation System ◽  
Probability Model ◽  
Allocation Mechanism ◽  
Vehicular Cloud Computing ◽  
Vehicular Cloud ◽  
Resource Allocation Mechanism

The Intelligent Transportation System (ITS) becomes an important component of the smart city toward safer roads, better traffic control, and on-demand service by utilizing and processing the information collected from sensors of vehicles and road side infrastructure. In ITS, Vehicular Cloud Computing (VCC) is a novel technology balancing the requirement of complex services and the limited capability of on-board computers. However, the behaviors of the vehicles in VCC are dynamic, random, and complex. Thus, one of the key safety issues is the frequent disconnections between the vehicle and the Vehicular Cloud (VC) when this vehicle is computing for a service. More important, the connection fault will disturb seriously the normal services of VCC and impact the safety works of the transportation. In this paper, a safety resource allocation mechanism is proposed against connection fault in VCC by using a modified workflow with prediction capability. We firstly propose the probability model for the vehicle movement which satisfies the high dynamics and real-time requirements of VCC. And then we propose a Prediction-based Reliability Maximization Algorithm (PRMA) to realize the safety resource allocation for VCC. The evaluation shows that our mechanism can improve the reliability and guarantee the real-time performance of the VCC.

On-Demand Routing Protocols for Vehicular Cloud Computing

2021 ◽  
pp. 96-122
Author(s):  
Ramesh C. Poonia ◽  
Linesh Raja
Keyword(s):  
Cloud Computing ◽  
Communication Networks ◽  
Routing Protocols ◽  
Node Mobility ◽  
Mobility Patterns ◽  
Computing Systems ◽  
Vehicular Cloud Computing ◽  
Vehicular Cloud ◽  
On Demand ◽  
Demand Routing

In vehicular cloud computing systems (VCC), the overlapping transmission range of each vehicle ensures a unified and common channel for communication among the vehicles. The flexibility of VCC systems opens the door to myriad applications that contribute to the safety and comfort of the passengers. They are distributed, self-organizing communication networks built up by moving vehicles, and are thus characterized by very high node mobility and limited degrees of freedom in mobility patterns. Such particular features often make the standard networking protocol inefficient or unusable, hence the growing effort in the development of communication protocols, which are specific to vehicular networks. Routing protocols should be selected carefully after carrying out literature review. This chapter has investigated different on-demand routing protocols and focused to identify the efficient on-demand routing protocol that can give better performance in realistic environments of vehicular cloud computing systems.

Mobility management on 5G Vehicular Cloud Computing systems

2019 ◽  
Vol 16 ◽  
pp. 15-44 ◽  
Author(s):  
Emmanouil Skondras ◽  
Angelos Michalas ◽  
Dimitrios D. Vergados
Keyword(s):  
Cloud Computing ◽  
Mobility Management ◽  
Computing Systems ◽  
Vehicular Cloud Computing ◽  
Vehicular Cloud

scholarly journals Network Slicing on 5G Vehicular Cloud Computing Systems

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1474
Author(s):  
Emmanouil Skondras ◽  
Angelos Michalas ◽  
Dimitrios J. Vergados ◽  
Emmanouel T. Michailidis ◽  
Nikolaos I. Miridakis ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Multiple Input Multiple Output ◽  
Access Network ◽  
Network Access ◽  
Network Slicing ◽  
Vehicular Cloud Computing ◽  
Vehicular Cloud ◽  
Sdn Controller

Fifth generation Vehicular Cloud Computing (5G-VCC) systems support various services with strict Quality of Service (QoS) constraints. Network access technologies such as Long-Term Evolution Advanced Pro with Full Dimensional Multiple-Input Multiple-Output (LTE-A Pro FD-MIMO) and LTE Vehicle to Everything (LTE-V2X) undertake the service of an increasing number of vehicular users, since each vehicle could serve multiple passenger with multiple services. Therefore, the design of efficient resource allocation schemes for 5G-VCC infrastructures is needed. This paper describes a network slicing scheme for 5G-VCC systems that aims to improve the performance of modern vehicular services. The QoS that each user perceives for his services as well as the energy consumption that each access network causes to user equipment are considered. Subsequently, the satisfactory grade of the user services is estimated by taking into consideration both the perceived QoS and the energy consumption. If the estimated satisfactory grade is above a predefined service threshold, then the necessary Resource Blocks (RBs) from the current Point of Access (PoA) are allocated to support the user’s services. On the contrary, if the estimated satisfactory grade is lower than the aforementioned threshold, additional RBs from a Virtual Resource Pool (VRP) located at the Software Defined Network (SDN) controller are committed by the PoA in order to satisfy the required services. The proposed scheme uses a Management and Orchestration (MANO) entity implemented by a SDN controller, orchestrating the entire procedure avoiding situations of interference from RBs of neighboring PoAs. Performance evaluation shows that the suggested method improves the resource allocation and enhances the performance of the offered services in terms of packet transfer delay, jitter, throughput and packet loss ratio.

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