Energy and QoS &amp;#x2014; A new perspective in a city vehicular communication network

Idjmayyel, Hamdi; Kumar, Wanod; Qazi, Bilal R.; Elmirghani, Jaafar M. H.

doi:10.1109/glocomw.2011.6162462

Cited by 4 publications

(3 citation statements)

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“…The concept of vehicular networks is still evolving, and research efforts are investigating different perspectives. In [38], [39] the energy efficiency and quality of service (QoS) were studied for different routing and base stations optimization schemes for vehicular networks in a city environment. The same authors in [40] and [41] developed position-based routing schemes for vehicular networks which they proved had a better performance than flood-based protocols.…”

Section: Related Workmentioning

confidence: 99%

Optimized Processing Placement Over a Vehicular Cloud

2022

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Modern vehicles equipped with on-board units (OBU) are playing an essential role in the emerging smart city revolution. The vehicular processing resources, however, are not used to their full potential. The concept of vehicular clouds is proposed to exploit the underutilized vehicular resources to supplement cloud computing services to relieve the burden on centralized cloud data centers and improve quality of service. In this paper we introduce a vehicular cloud architecture supported by fixed edge computing nodes and a central cloud data center. A mixed integer linear programming (MILP) model is developed to optimize the allocation of the processing demands in the distributed architecture while minimizing the overall power consumption. The results show power savings as high as 84% compared to processing in the conventional cloud. A heuristic algorithm with performance approaching that of the MILP model is developed to validate the MILP model and allocate processing demands in real time.INDEX TERMS vehicular clouds, edge computing, fog, power optimization, distributed processing, MILP.

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Section: Related Workmentioning

confidence: 99%

Optimized Processing Placement Over a Vehicular Cloud

2022

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“…cellular or vehicular) as they are not intrinsically over-provisioned and the link quality dependent upon the varying wireless channel, which makes it susceptible to degraded QoS. Recent research on energy savings encompasses various methods, where the principal objective is to maintain quality of service (QoS) for communication networks [8], [25]- [27]. Nevertheless, a few research groups have proposed a number of sleep strategies to make cellular network energy efficient [28]- [30].…”

Section: Related Workmentioning

confidence: 99%

“…A similar strategy was employed on the CPs in a city vehicular CDN, where the number and locations of the CPs were optimized with vehicle mobility and hourly traffic [7], [8]. However, there would be transient variation in traffic within any period of time.…”

Section: Introductionmentioning

confidence: 99%

Load Adaptive Caching Points for a Content Distribution Network

Igder

Idjmayyel

Qazi

et al. 2015

2015 9th International Conference on Next Generation Mobile Applications, Services and Technologies

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-The unprecedented growth in content demand on smartphones has significantly increased the energy consumption of current cellular and backbone networks. Apart from achieving stringent carbon footprint targets, provisioning high data rates to city vehicular users while maintaining quality of service (QoS) remains a serious challenge. In previous work, to support content delivery at high data rates, the number and locations of caching points (CPs) within a content distribution network (CDN) were optimized while reducing the operational energy consumption compared to typical cellular networks. Further reduction in energy consumption may be possible through sleep cycles, which reduces transmission energy consumption. However, sleep cycles degrade the quality of service. Therefore, in this paper, we propose a novel load adaptation technique for a CP which not only enhances content download rate but also reduces transmission energy consumption through random sleep cycles. Unlike a non-load adaptive (deterministic) CP, the performance results reveal that the load adaptive CP achieves considerably lower average piece delay (approximately 60% on average during the day), leveraging the introduction of random sleep cycles to save transmission energy. The proposed CP saves up to 84% transmission energy during off-peak hours and 33% during the whole day while fulfilling content demand in a city vehicular environment.

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