Information-Centric Mobile Edge Computing for Connected Vehicle Environments

Grewe, Dennis; Wagner, Marco; Arumaithurai, Mayutan; Psaras, Ioannis; Kutscher, Dirk

doi:10.1145/3098208.3098210

Cited by 80 publications

(62 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are comprehensive survey works [40], [41] which are specific to the MEC related research in this area, so we do not mention individual papers here. The industries also pay attention for MEC application to the connected vehicles and activities to foster the ecosystem is starting in some consortiums [42], [43], [44], etc.…”

Section: Connected Vehiclesmentioning

confidence: 99%

Multi-access Edge Computing: A Survey

Tanaka

Yoshida

Möri

et al. 2018

Journal of Information Processing

View full text Add to dashboard Cite

Multi-access Edge Computing (MEC) can be defined as a model for enabling business oriented, cloud computing platform within multiple types of the access network (e.g., LTE, 5G, WiFi, FTTH, etc.) at the close proximity of subscribers to serve delay sensitive, context aware applications. To pull out the most of the potential, MEC has to be designed as infrastructure, to support many kind of IoT applications and their eco system, in addition to sufficiently management mechanism. In this context, various research and standardization efforts are ongoing. This paper provides a comprehensive survey of the state-of-the-art research efforts on MEC domain, with focus on the architectural proposals as infrastracture, the issue of the partitioning of processing among the user devices, edge servers, and a cloud, and the issue of the resource management.

show abstract

Section: Connected Vehiclesmentioning

confidence: 99%

Multi-access Edge Computing: A Survey

Tanaka

Yoshida

Möri

et al. 2018

Journal of Information Processing

View full text Add to dashboard Cite

show abstract

“…Current works on content-centric networks typically assume fixed network scenarios [4,5]. With recent advances in wireless mobile communication technologies and devices, Mobile Edge Computings (MECs) running as virtual entities have emerged and imposed high degree of mobility of network participants such as subscriber mobility [4].…”

Section: Related Workmentioning

confidence: 99%

“…With recent advances in wireless mobile communication technologies and devices, Mobile Edge Computings (MECs) running as virtual entities have emerged and imposed high degree of mobility of network participants such as subscriber mobility [4]. Mobile publisher data problem is still not understood sufficiently clearly [6] and leads to lower quality of the services.…”

Section: Related Workmentioning

confidence: 99%

Understanding Complementary Multi-layer Collaborative Heuristics for Adaptive Caching in Heterogeneous Mobile Opportunistic Networks

Huynh

Radenkovic

2018

2018 14th International Wireless Communications &Amp; Mobile Computing Conference (IWCMC)

View full text Add to dashboard Cite

Abstract-Current research aims to deal with emerging challenges of the opportunistic discovery of content stored in remote mobile publishers and the delivery to the subscribers in heterogeneous mobile opportunistic networks. Innovative network and service architectures leverage in-network caching to improve transmission efficiency, reduce delay and handle disconnections. In this paper, we investigate the influences of multi-dimensional heuristics utilised by our adaptive collaborative caching framework CafRepCache on the performance of content dissemination and query in heterogeneous mobile opportunistic environments. We consider the complementary multi-layer heuristics that combine social driven, resources driven, ego network driven and content popularity driven analytics. We extensively evaluate the performance of each complementary heuristic and discuss the impact of each one on every layer of our caching framework across heterogeneous real-world mobility, connectivity traces and use YouTube dataset for different workload and content popularity patterns. We show that the multilayer heuristics enable CafRepCache to be responsive to dynamically changing network topology, congestion avoidance and varying patterns of content publishers/subscribers which balances the trade-off that achieves higher cache hit ratio, delivery success ratios while keeping lower delays and packet loss.Keywords-Opportunistic mobile networks, content discovery and retrieval, content caching, multi-layer heuristics and utilities.

show abstract

“…In order to support the above cited emerging ITS services, it is envisioned that the communication infrastructure will rely on several emerging paradigms. The cloud computing is a key enabler of ITS services, it is used by the ITS system actors to collect, process and exchange data to provide vehicle with relevant services [16,17]. On the other hand, fog and edge computing are crucial to support ITS services with stringent latency requirements, by bringing processing closer to vehicles [16,18].…”

Section: Introductionmentioning

confidence: 99%

Towards Dynamic Controller Placement in Software Defined Vehicular Networks

Toufga

Abdellatif

Assouane

et al. 2020

Sensors

View full text Add to dashboard Cite

The emerging SDVN (Software Defined Vehicular Network) paradigm promises to bring flexibility and efficient resource utilization to vehicular networks, enabling the emergence of novel Intelligent Transportation Services. However, as it was initially designed with wired network in mind, applying the SDN paradigm to a vehicular context faces new challenges related to the peculiar characteristics of this network (high node mobility and node density, and the presence of wireless links). In this paper, we focus on one of the critical architectural elements of SDVN, namely, the SDN Controller Placement, and promote the use of dynamic placement methods that take into account the dynamicity of vehicular networks' topology. We also describe the different approaches towards a dynamic controller placement and also propose an ILP (Integer Linear Programming) based dynamic placement method that adaptively readjusts the number and placement of controllers according to road traffic fluctuations. The proposed method is evaluated using a realistic traffic trace from Luxembourg City. Simulation results show that our approach outperforms the static approach as proposed in the literature.Most existing research work have been elaborated on the opportunities that the SDVN concept could bring when applied to vehicular networks [10]. However, some challenges need to be addressed to reach these expected opportunities. Among these challenges, we mention firstly, the network topology discovery, which is a crucial service in the Software Defined Vehicular Netowrk (SDVN) system [11]. Its main goal is to build and maintain an up-to-date view of the underlying network. The density and high mobility of vehicles make the design of this service a challenging task. Secondly, the connectivity between the vehicles and their controller is partly wireless [12]. In fact, vehicles can go through areas without network coverage, this could make the controller temporarily unreachable, which may impact network performance. Thirdly, the mobility of vehicles can result in frequent changes of their attached SDN controller. This impacts the established sessions with the initial controller, as well as an increase of network overhead due to inter-controller vehicles information exchange. The SDN controller placement is a key architectural element that can help mitigating the above mentioned challenges. It consists of computing the number of SDN controllers to deploy and derive their placement in the network. This choice must be done appropriately given the critical role of an SDN controller in this architecture. First, wireless link connectivity and quality must be considered in order to minimize the connectivity losses between vehicles and their controllers. Second, the SDN Controller coverage should be defined carefully taking into account the density and mobility of vehicles. This helps avoiding SDN controllers' overload as well as improving the performance of vehicle-to-controller communications, and also, minimizing the number of changes in the set of deploy...

show abstract

Information-Centric Mobile Edge Computing for Connected Vehicle Environments

Cited by 80 publications

References 16 publications

Multi-access Edge Computing: A Survey

Multi-access Edge Computing: A Survey

Understanding Complementary Multi-layer Collaborative Heuristics for Adaptive Caching in Heterogeneous Mobile Opportunistic Networks

Towards Dynamic Controller Placement in Software Defined Vehicular Networks

Contact Info

Product

Resources

About