Cloud Computing in VANETs: Architecture, Taxonomy, and Challenges

Cloud Computing in VANETs (CC-V) has been investigated into two major themes of research including Vehicular Cloud Computing (VCC) and Vehicle using Cloud (VuC). VCC is the realization of autonomous cloud among vehicles to share their abundant resources. VuC is the efficient usage of conventional cloud by on-road vehicles via a reliable Internet connection. Recently, number of advancements have been made to address the issues and challenges in VCC and VuC. This paper qualitatively reviews CC-V with the emphasis on layered architecture, network component, taxonomy, and future challenges. Specifically, a four-layered architecture for CC-V is proposed including perception, co-ordination, artificial intelligence and smart application layers. Three network component of CC-V namely, vehicle, connection and computation are explored with their cooperative roles. A taxonomy for CC-V is presented considering major themes of research in the area including design of architecture, data dissemination, security, and applications. Related literature on each theme are critically investigated with comparative assessment of recent advances. Finally, some open research challenges are identified as future issues. The challenges are the outcome of the critical and qualitative assessment of literature on CC-V

SAI: safety application identifier algorithm at MAC layer for vehicular safety message dissemination over LTE VANET networks

Vehicular safety applications have much significance in preventing road accidents and fatalities. Among others, cellular networks have been under investigation for the procurement of these applications subject to stringent requirements for latency, transmission parameters, and successful delivery of messages. Earlier contributions have studied utilization of Long-Term Evolution (LTE) under single cell, Friis radio, or simplified higher layer. In this paper, we study the utilization of LTE under multicell and multipath fading environment and introduce the use of adaptive awareness range. Then, we propose an algorithm that uses the concept of quality of service (QoS) class identifiers (QCIs) along with dynamic adaptive awareness range. Furthermore, we investigate the impact of background traffic on the proposed algorithm. Finally, we utilize medium access control (MAC) layer elements in order to fulfill vehicular application requirements through extensive system-level simulations. The results show that, by using an awareness range of up to 250 m, the LTE system is capable of fulfilling the safety application requirements for up to 10 beacons/s with 150 vehicles in an area of 2 × 2 km2. The urban vehicular radio environment has a significant impact and decreases the probability for end-to-end delay to be ≤100 ms from 93%–97% to 76%–78% compared to the Friis radio environment. The proposed algorithm reduces the amount of vehicular application traffic from 21 Mbps to 13 Mbps, while improving the probability of end-to-end delay being ≤100 ms by 20%. Lastly, use of MAC layer control elements brings the processing of messages towards the edge of network increasing capacity of the system by about 50%

Distributed Artificial Intelligence Solution for D2D Communication in 5G Networks

Device to Device (D2D) Communication is one of the technology components of the evolving 5G architecture, as it promises improvements in energy efficiency, spectral efficiency, overall system capacity, and higher data rates. The above noted improvements in network performance spearheaded a vast amount of research in D2D, which have identified significant challenges that need to be addressed before realizing their full potential in emerging 5G Networks. Towards this end, this paper proposes the use of a distributed intelligent approach to control the generation of D2D networks. More precisely, the proposed approach uses Belief-Desire-Intention (BDI) intelligent agents with extended capabilities (BDIx) to manage each D2D node independently and autonomously, without the help of the Base Station. The paper includes detailed algorithmic description for the decision of transmission mode, which maximizes the data rate, minimizes the power consumptions, while taking into consideration the computational load. Simulations show the applicability of BDI agents in jointly solving D2D challenges.Comment: 10 pages,9 figure

Efficient medium access control protocol for vehicular ad-hoc networks

Intelligent transportation systems (ITS) have enjoyed a tremendous growth in the last decade and the advancement in communication technologies has played a big role behind the success of ITS. Inter-vehicle communication (IVC) is a critical requirement for ITS and due to the nature of communication, vehicular ad-hoc network technology (VANET) is the most suitable communication technology for inter-vehicle communications. In Practice, however, VANET poses some extreme challenges including dropping out of connections as the moving vehicle moves out of the coverage range, joining of new nodes moving at high speeds, dynamic change in topology and connectivity, time variability of signal strength, throughput and time delay. One of the most challenging issues facing vehicular networks lies in the design of efficient resource management schemes, due to the mobile nature of nodes, delay constraints for safety applications and interference. The main application of VANET in ITS lies in the exchange of safety messages between nodes. Moreover, as the wireless access in vehicular environment (WAVE) moves closer to reality, management of these networks is of increasing concern for ITS designers and other stakeholder groups. As such, management of resources plays a significant role in VANET and ITS. For resource management in VANET, a medium access control protocol is used, which makes sure that limited resources are distributed efficiently. In this thesis, an efficient Multichannel Cognitive MAC (MCM) is developed, which assesses the quality of channel prior to transmission. MCM employs dynamic channel allocation and negotiation algorithms to achieve a significant improvement in channel utilisation, system reliability, and delay constraints while simultaneously addressing Quality of Service. Moreover, modified access priority parameters and safety message acknowledgments will be used to improve the reliability of safety messages. The proposed protocols are implemented using network simulation tools. Extensive experiments demonstrated a faster and more efficient reception of safety messages compared to existing VANET technologies. Finally, improvements in delay and packet delivery ratios are presented

Evolution of 5G Network: A Precursor towards the Realtime Implementation of VANET for Safety Applications in Nigeria

  A crucial requirement for the successful real-time design and deployment of Vehicular Adhoc Networks (VANET) is to ensure high speed data rates, low latency, information security, and a wide coverage area without sacrificing the required Quality of Service (QoS) in VANET. These requirements must be met for flawless communication on the VANET. This study examines the generational patterns in mobile wireless communication and looks into the possibilities of adopting fifth generation (5G) network technology for real-time communication of road abnormalities in VANET. The current paper addresses the second phase of a project that is now underway to develop real-time road anomaly detection, characterization, and communication systems for VANET. The major goal is to reduce the amount of traffic accidents on Nigerian roadways. It will also serve as a platform for the real-time deployment and testing of various road anomaly detection algorithms, as well as schemes for communicating such detected anomalies in the VANET.   &nbsp