Sharing video on demand

Bar-Noy, Amotz; Garay, Juan A.; Herzberg, Amir

doi:10.1016/s0166-218x(02)00231-7

Cited by 12 publications

(13 citation statements)

References 21 publications

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“…How to make admission decisions is not trivial. The idea of admission control in the context of deadline scheduling takes the form of "customer notification" [21] where the service provider can choose to accept or decline a customer's request upon the request arrival; see also [22,23] and references therein. The optimal admission control is not known in the literature.…”

Section: Related Workmentioning

confidence: 99%

iEMS for large scale charging of electric vehicles: Architecture and optimal online scheduling

Chen

Tong

2012

2012 IEEE Third International Conference on Smart Grid Communications (SmartGridComm)

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Abstract-The problem of large scale charging of electric vehicles (EVs) is considered. An architecture for the energy management system (EMS) is proposed based on the concept of network switched charging where chargers are controlled by a scheduler that optimizes the overall operating profit of the service provider. It is assumed that the EMS has access to collocated renewable sources (e.g. solar power) and can supplement the renewable with purchased electricity from the grid. The renewable source may vary arbitrarily, and requests of all EVs accepted for service must be completed by their respective deadlines.Under a deterministic model for arbitrary arrivals, charging requests, and service deadlines, online scheduling of EV charging is formulated as a multi-processor deadline scheduling problem for which the optimal scheduler maximizes the competitive ratio against the best offline scheduler. An online scheduling algorithm, referred to as TAGS, is proposed based on the principle of threshold admission and greedy scheduling. TAGS has the complexity of O(n log n) where n is the number of EVs in the facility. It is shown that, when the price offered to the EV customers is higher than the purchasing price of electricity from the grid, TAGS achieves the competitive ratio of 1. Otherwise, TAGS achieves the maximum competitive ratio given by the inverse of a real root of a certain polynomial. Simulations are used to evaluate the performance of TAGS against standard benchmarks and for the setting of optimal charging price.

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Section: Related Workmentioning

confidence: 99%

iEMS for large scale charging of electric vehicles: Architecture and optimal online scheduling

Chen

Tong

2012

2012 IEEE Third International Conference on Smart Grid Communications (SmartGridComm)

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“…The admission control has been considered in the literature under the term "immediate notification" in [19] for the application of video-on-demand. Later, joint admission and scheduling has been studied in [20], [21], [22], [23] for nonpreemptive job requests without non-completion penalty.…”

Section: B Related Workmentioning

confidence: 99%

Large scale charging of Electric Vehicles

Chen

Tong

2012

2012 IEEE Power and Energy Society General Meeting

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Abstract-The problem of scheduling for large scale charging of Electric Vehicles (EVs) is considered. As part of the future EV infrastructure, a Large Scale Charging (LSC) facility is capable of charging hundreds of electric vehicles simultaneously. As an intelligent load in the future smart grid, LSC requires properly designed pricing and scheduling algorithms that take into account the electricity consumed, the arrival-departure characteristics, and overall charging capacity.The scheduling of LSC is formulated as a deadline scheduling problem. Utility functions that combine both amount of charge and tightness of the deadline are proposed. Under arbitrary (and deterministic) arrival, departure, and charging characteristics, a scheduling policy referred to as deadline scheduling with admission control is proposed. The proposed algorithm achieves the highest competitive ratio (against the best offline scheduling) for the utility function linear in charging level among all online scheduling algorithms. It also offers significant gain over benchmark scheduling algorithms such as the Earliest Deadline First (EDF) scheduling and the First Come First Serve (FCFS) scheduling in terms of average performance for general utility functions when tested with randomly generated charging requests.Index Terms-Electric vehicle infrastructure, large scale charging, EV/PHEV charging, demand response.

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“…As in many previous works (e.g., [3,6,9,10,18,20]), we assume that all jobs have the same length . (Note that this assumption is not unrealistic and is applicable to PDD systems using DNS servers.…”

Section: The Modelmentioning

confidence: 99%

“…After defining the patience τ to be the smallest number such that any job of length has a start-up delay at least τ , he proved that the competitive ratio for scheduling such system is exactly 1 + 1 τ +1 . Later, Bar-Noy, Garay and Herzberg [3] studied the scheduling of VOD systems. Their results imply that if the start-up delay d is smaller than √ s/u times the job length , then the competitive ratio κ = Θ(ln u s ).…”

Section: Related Workmentioning

confidence: 99%

Design and Analysis of Online Batching Systems

Hung

Ting

2008

Algorithmica

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In this paper, we study the design and analysis of online batching systems, which can be used to model many popular IT systems such as the Video-On-Demand system and the Pull-based Data Dissemination system. We analyze how the start-up delay affects the performance of these systems and investigate the tradeoff relationship between the number of servers and the length of the start-up delay. We also study a simple online algorithm for scheduling online batching systems. By deriving close lower and upper bounds, we prove that our algorithm is near optimal.

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Sharing video on demand

Cited by 12 publications

References 21 publications

iEMS for large scale charging of electric vehicles: Architecture and optimal online scheduling

iEMS for large scale charging of electric vehicles: Architecture and optimal online scheduling

Large scale charging of Electric Vehicles

Design and Analysis of Online Batching Systems

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