Software Defined Networking-based Vehicular Adhoc Network with Fog Computing

Vehicular Adhoc Networks (VANETs) have been attracted a lot of research recent years. Although VANETs are deployed in reality offering several services, the current architecture has been facing many difficulties in deployment and management because of poor connectivity, less scalability, less flexibility and less intelligence. We propose a new VANET architecture called FSDN which combines two emergent computing and network paradigm Software Defined Networking (SDN) and Fog Computing as a prospective solution. SDN-based architecture provides flexibility, scalability, programmability and global knowledge while Fog Computing offers delay-sensitive and location-awareness services which could be satisfy the demands of future VANETs scenarios. We figure out all the SDN-based VANET components as well as their functionality in the system. We also consider the system basic operations in which Fog Computing are leveraged to support surveillance services by taking into account resource manager and Fog orchestration models. The proposed architecture could resolve the main challenges in VANETs by augmenting Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), Vehicle-to-Base Station communications and SDN centralized control while optimizing resources utility and reducing latency by integrating Fog Computing. Two use-cases for non-safety service (data streaming) and safety service (Lane-change assistance) are also presented to illustrate the benefits of our proposed architecture

Fog Computing: A Taxonomy, Survey and Future Directions

In recent years, the number of Internet of Things (IoT) devices/sensors has increased to a great extent. To support the computational demand of real-time latency-sensitive applications of largely geo-distributed IoT devices/sensors, a new computing paradigm named "Fog computing" has been introduced. Generally, Fog computing resides closer to the IoT devices/sensors and extends the Cloud-based computing, storage and networking facilities. In this chapter, we comprehensively analyse the challenges in Fogs acting as an intermediate layer between IoT devices/ sensors and Cloud datacentres and review the current developments in this field. We present a taxonomy of Fog computing according to the identified challenges and its key features.We also map the existing works to the taxonomy in order to identify current research gaps in the area of Fog computing. Moreover, based on the observations, we propose future directions for research

Advancement in infotainment system in automotive sector with vehicular cloud network and current state of art

The automotive industry has been incorporating various technological advancement on top-end versions of the vehicle order to improvise the degree of comfortability as well as enhancing the safer driving system. Infotainment system is one such pivotal system which not only makes the vehicle smart but also offers abundance of information as well as entertainment to the driver and passenger. The capability to offer extensive relay of service through infotainment system is highly dependent on vehicular adhoc network as well as back end support of cloud environment. However, it is know that such legacy system of vehicular adhoc network is also characterized by various problems associated with channel capacity, latency, heterogeneous network processing, and many more. Therefore, this paper offers a comprehensive insight to the research work being carried out towards leveraging the infotainment system in order to obtain the true picture of strength, limitation, and open end problems associated with infotainment system

Software-Defined Network-Based Vehicular Networks: A Position Paper on Their Modeling and Implementation

There is a strong devotion in the automotive industry to be part of a wider progression towards the Fifth Generation (5G) era. In-vehicle integration costs between cellular and vehicle-to-vehicle networks using Dedicated Short Range Communication could be avoided by adopting Cellular Vehicle-to-Everything (C-V2X) technology with the possibility to re-use the existing mobile network infrastructure. More and more, with the emergence of Software Defined Networks, the flexibility and the programmability of the network have not only impacted the design of new vehicular network architectures but also the implementation of V2X services in future intelligent transportation systems. In this paper, we define the concepts that help evaluate software-defined-based vehicular network systems in the literature based on their modeling and implementation schemes. We first overview the current studies available in the literature on C-V2X technology in support of V2X applications. We then present the different architectures and their underlying system models for LTE-V2X communications. We later describe the key ideas of software-defined networks and their concepts for V2X services. Lastly, we provide a comparative analysis of existing SDN-based vehicular network system grouped according to their modeling and simulation concepts. We provide a discussion and highlight vehicular ad-hoc networks' challenges handled by SDN-based vehicular networks.Comment: 14 pages, 3 figures, Sensors 201

Vehicle-Life Interaction in Fog-Enabled Smart Connected and Autonomous Vehicles

Traffic accidents have become a major issue for researchers, academia, government and vehicle manufacturers over the last few years. Many accidents and emergency situations frequently occur on the road. Unfortunately, accidents lead to health injuries, destruction of some infrastructure, bad traffic flow, and more importantly these events cause deaths of hundreds of thousands of people due to not getting treatment in time. Thus, we need to develop an efficient and smart emergency system to ensure the timely arrival of an ambulance service to the place of the accident in order to provide timely medical help to those injured. In addition, we also need to communicate promptly with other entities such as hospitals so that they can make appropriate arrangements and provide timely medical information to emergency personnel on the scene including alerting those related to the injured person(s). In this paper, we have developed an intelligent protocol that uses connected and autonomous vehicles\u27 scenarios in Intelligent Transportation System (ITS) so that prompt emergency services can be provided to reduce the death rate caused. The proposed protocol smartly connects with all the relevant entitles during the emergency while maintaining a smooth traffic flow for the arrival of the ambulance service. Moreover, our protocol also mitigates the broadcasting of messages circulating over the network for delay sensitive tasks. The evaluation results, based on the performance metrics such as channel collision, average packet delay, packet loss, and routing-overhead demonstrate that our proposed protocol outperforms previously proposed protocols such as Emergency Message Dissemination for Vehicular (EMDV), Contention Based Broadcasting (CBB), and Particle Swarm Optimization Contention-based Broadcast (PCBB) protocols. Finally, we discuss several issues and challenges that need to be addressed in the network in order to achieve more a reliable, efficient, connected, and autonomous vehicular network

Routing Strategy for Internet of Vehicles based on Hierarchical SDN and Fog Computing

تم اکتشاف الحوسبة الضبابیة لحل مشكلة نقص المصادر في مستشعرات إنترنت الأشياء (IoT) ومعالجة المهام بسرعة. انترنت المركبات (IoV) هو تطبيق خاص من شبكات إنترنت الأشياء التي تتكون من أجهزة استشعار غير متجانسة موجودة في المركبات. تقوم هذه المستشعرات بنقل المهام إلى خوادم الحوسبة الضابية التي تعالجها وتعطي الإجابات للمستشعرات.  على اي حال، فإن حركة المركبات تؤثر على عملية تسليم هذه الاجابات. عندما تخرج السيارة المصدرة للمهمة من مجال خادم ضبابي معين خلال وقت معالجة هذه المهمة، فأنه لن يتم وصول الاجابة لتلك السيارة بشكل صحيح. لذلك، يحتاج إلى حساب المسار الأمثل لتلك السيارة. تتسبب هذه العملية في تجاوز الموعد النهائي للمهمة وتقليل الإنتاجية. للتغلب على هذه المشكلة، يقدم هذا البحث معمارية هرمية مبنية على الشبكات المعرفة بالبرمجيات (SDN) وحوسبة الضباب لشبكة IoV. تتألف هذه المعمارية من طبقة سيارات IoV, بيئة حوسبة ضبابية ووحدات تحكم SDN شبه مركزية ووحدة تحكم SDN  مركزية. علاوة على ذلك ، تم اقتراح إستراتيجية توجيهية تسمى إستراتيجية توجيه ذات تأخير جيد بالاعتماد على الحوسبة الضبابية و ال SDN لشبكات ال IoV (DRSFI) .تقوم وحدات التحكم SDN بتنفيذ DRSFI لحساب المسارات مع أدنى تأخير مع الأخذ بنظر الاعتبار قيد النطاق الترددي المتاح وموقع وسرعة المركبة. من نتائج محاكاة سيناريوهات مختلفة مع سرعات حركة متنوعة وعداد مختلفة من المهام، استنتجنا أن النظام المقترح أفضل من نظام IoV-Fog-Central SDN  ونظام IoV-Fog من حيث متوسط التأخير من البداية إلى النهاية و النسبة المئوية لخسارة الحزم والنسبة المئوية للإرسال الناجح.The fog computing is invited to solve the lack of resources problem in the sensors of Internet of Things (IoT) and handle the tasks quickly. Internet of Vehicles (IoV) is a special application of IoT networks that composed of heterogeneous sensors that are found in vehicles. These sensors transfer the tasks to the fog servers that process them and give the responses to the sensors. However, the mobility of vehicles effects on the delivery operation of responses. When the source vehicle of a task exited from the domain of some fog server through the processing time of this task, the response will not be reached to that vehicle correctly. Therefore, it is need to compute the optimal path to that vehicle. This process causes exceeding the task deadline and decreasing the throughput. To overcome this issue, this paper produces a hierarchical architecture based on Software Defined Network (SDN) and fog computing for IoV networks. This architecture consists of IoV vehicles, fog computing framework, semi-central SDN controllers and central SDN controller layers. Moreover, a routing strategy is proposed called Delay-Efficient Routing strategy based on SDN and Fog computing for IoV (DRSFI). The SDN controllers perform DRSFI to compute the routes with minimum delay with taking into consideration the available bandwidth constraint and the location and speed of the vehicle. From the results of simulation of different scenarios with various mobility speeds and various number of tasks, we concluded that the proposed system is better than IoV-Fog-central SDN system and IoV-Fog system in terms of average delay from end to end, percentage of packet loss and percentage of successfully transmission. &nbsp