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Service Migration in Fog Computing Enabled Cellular Networks to Support Real-Time Vehicular Communications
KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Optical Network Laboratory (ON Lab).
KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Optical Network Laboratory (ON Lab).
RISE Viktoria, S-41756 Gothenburg, Sweden..
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2019 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 13704-13714Article in journal (Refereed) Published
Abstract [en]

Driven by the increasing number of connected vehicles and related services, powerful communication and computation capabilities are needed for vehicular communications, especially for real-time and safety-related applications. A cellular network consists of radio access technologies, including the current long-term evolution (LTE), the LTE advanced, and the forthcoming 5th generation mobile communication systems. It covers large areas and has the ability to provide high data rate and low latency communication services to mobile users. It is considered the most promising access technology to support real-time vehicular communications. Meanwhile, fog is an emerging architecture for computing, storage, and networking, in which fog nodes can be deployed at base stations to deliver cloud services close to vehicular users. In fog computing-enabled cellular networks, mobility is one of the most critical challenges for vehicular communications to maintain the service continuity and to satisfy the stringent service requirements, especially when the computing and storage resources are limited at the fog nodes. Service migration, relocating services from one fog server to another in a dynamic manner, has been proposed as an effective solution to the mobility problem. To support service migration, both computation and communication techniques need to be considered. Given the importance of protocol design to support the mobility of the vehicles and maintain high network performance, in this paper, we investigate the service migration in the fog computing-enabled cellular networks. We propose a quality-of-service aware scheme based on the existing handover procedures to support the real-time vehicular services. A case study based on a realistic vehicle mobility pattern for Luxembourg scenario is carried out, where the proposed scheme, as well as the benchmarks, are compared by analyzing latency and reliability as well as migration cost.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2019. Vol. 7, p. 13704-13714
Keywords [en]
Connected vehicles, fog computing, service migration
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:kth:diva-245959DOI: 10.1109/ACCESS.2019.2893571ISI: 000458796400035Scopus ID: 2-s2.0-85061733224OAI: oai:DiVA.org:kth-245959DiVA, id: diva2:1296419
Note

QC 20190315

Available from: 2019-03-15 Created: 2019-03-15 Last updated: 2019-08-27Bibliographically approved
In thesis
1. Ultra-low latency communication for 5G transport networks
Open this publication in new window or tab >>Ultra-low latency communication for 5G transport networks
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The fifth generation (5G) mobile communication system is envisioned to serve various mission-critical Internet of Thing (IoT) applications such as industrial automation, cloud robotics and safety-critical vehicular communications. The requirement of the end-to-end latency for these services is typically within the range between 0.1 ms and 20 ms, which is extremely challenging for the conventional cellular network with centralized processing. As an integral part of the cellular network, the transport network, referred to as the segment in charge of the backhaul of radio base stations or/and the fronthaul of remote radio unit, plays an especially important role to meet such a stringent requirement on latency.This thesis investigates how to support the ultra-low latency communications for 5G transport networks, especially for backhaul networks. First, a novel passive optical network (PON) based mobile backhaul is proposed and tailored communication protocols are designed to enhance the connectivity among adjacent base stations (BSs). Simulation results show that an extremely low latency (less than 1 ms packet delay) for communications among the BSs can be achieved, which thereby can be used to support fast handover for users with high mobility (e.g., vehicles).Furthermore, the thesis presents a fog computing enabled cellular networks (FeCN), in which computing, storage, and network functions are provisioned closer to end users, thus the latency on transport networks can be reduced significantly. In the context of FeCN, the high mobility feature of users brings critical challenges to maintain the service continuity with stringent service requirements. In the meanwhile, transmitting the associated services from the current fog server to the target one to fulfill the service continuity, referred to as service migration, has been regarded as a promising solution for mobility management. However, service migration cannot be completed immediately, and may lead to a situation where users experience loss of access to the service. To solve such issues, a quality-of-service (QoS) aware service migration strategy is proposed. The method is based on the existing handover procedures with newly introduced distributed fog computing resource management scheme to minimize the potential negative effects induced by service migration. The performance of the proposed schemes is evaluated by a case study, where realistic vehicle mobility pattern in the metropolitan network scenario of Luxembourg is used to reflect the real world environment. Results show that low end-to-end latency (e.g., 10 ms) for vehicular communication can be achieved with typical vehicle mobility. During service migration, both the traffic generated by migration and other traffic (e.g., control information, video) are transmitted via mobile backhaul networks. To balance the performance of the two kinds of traffic, a delay-aware bandwidth slicing scheme is proposed in PON-based mobile backhaul networks. Simulation results show that, with the proposed method, migration data can be transmitted successfully within a required time threshold, while the latency and jitter for non-migration traffic with different priorities can be reduced significantly.

Abstract [sv]

5:e generationens (5G) mobilnät förväntas stödja olika kritiska tillämpningar av Sakernas Internet (IoT), såsom industriell automation, moln-baserad robotik och säkerhetskritisk fordonskommunikation. Kravet på envägs totalfördröjning för dessa tjänster ligger typiskt i intervallet mellan 0,1 ms och 20 ms, vilket är extremt utmanande för det konventionella mobilnätet med centraliserad databearbetning. Transportnätet, det segment av nätet som är ansvarigt för sammankoppling av radiobasstationer (s.k. backhaul) och/eller anslutning av radioenheter (s.k. fronthaul), är en integrerad del av mobilnätet och spelar en särskilt viktig roll för att möta ett sådana stringenta krav på fördröjningen.Denna avhandling undersöker hur man kan stödja de kommunikation med ultralåga fördröjning för 5G-transportnät, speciellt för backhaul-nätverk. Först beaktas ett nytt passivt optiskt nätverk (PON) förmobil backhaul, och skräddarsydda kommunikationsprotokoll utformas för att förbättra uppkopplingen mellan alla angränsande basstationer (BS). Simuleringsresultat visar att en extremt låg fördröjning (mindre än 1 ms paketfördröjning) för kommunikation mellan basstationerna kan uppnås, vilket kan användas för att stödja snabb överlämning mellan basstationer (s.k. handover) för mobila användare med hög rörlighet (t.ex. fordon).Vidare presenterar avhandlingen ett dim-baserat (fog computing) mobilnät (FeCN), där databehandling, lagring och nätverksfunktioner tillhandahålls närmare slutanvändarna, vilket innebär att fördröjningen på transportnät kan minskas betydligt. I samband med FeCN är hantering av mobila användare en av de mest kritiska utmaningarna för användare som kännetecknas av hög rörlighet. Utmaningen är att upprätthålla tjänsten kontinuerligt och att uppfylla de stringenta tjänstekraven. Tjänstemigrering, dvs flytt av tjänster från en server till en annan på ett dynamiskt sätt, har betraktats som en lovande lösning för hantering av mobila användare. Tjänstemigrering kan dock inte slutföras omedelbart, vilket kan leda till en situation där användare upplever att de förlorar åtkomst till tjänsterna. För att lösa dessa frågor är föreslås en migreringsstrategi som beaktar tjänstekvaliteten (QoS). Metoden bygger på befintliga handover-procedurer med nyntroducerade resurshanteringssystem baserade på distribuerad fog computing, för att minimera de eventuella negativa effekter som induceras av tjänstemigrering. En fallstudie, baserad på ett realistiskt mobilitetsmönster för fordon i ett Luxemburg-scenario, genomförs med hjälp av simuleringsstudier för att utvärdera prestanda för de föreslagna systemen. Resultaten visar att låg fördröjning (t.ex., 10 ms) för fordonskommunikation kan uppnås med typisk fordonsmobilitet. Under tjänstemigrering skickas både trafiken genererad av migreringen och annan datatrafik (t.ex., kontrollinformation och video) via mobila backhaul-nätverk. För att balansera prestandan för de två typerna av trafik, föreslås ett system för bandreddsuppdelning i PON-baserade mobila backhaul-nätverk som tar fördröjning i beaktan. Simuleringsresultat visar att med den föreslagna metoden kan migreringsdata framgångsrikt överföras inom den tidsgräns som krävs, medan fördröjningen och fördröjningsvariationer v övrig trafik med olika prioriteringar kan minskas betydligt.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2019
Series
TRITA-EECS-AVL ; 2019:59
National Category
Communication Systems
Research subject
Information and Communication Technology
Identifiers
urn:nbn:se:kth:diva-256503 (URN)978-91-7873-243-2 (ISBN)
Public defence
2019-09-20, Sal 308, ELECTRUM, Kistagången 16, Kista, Stockholm, 10:00 (English)
Opponent
Supervisors
Available from: 2019-08-27 Created: 2019-08-26 Last updated: 2019-08-27Bibliographically approved

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