Broadcast Scheduling With Multiple Concurrent Costs

Liaskos, Christos; Xeros, Andreas; Papadimitriou, Georgios I.; Lestas, Marios; Pitsillides, Andreas

doi:10.1109/tbc.2012.2191028

Cited by 10 publications

(13 citation statements)

References 30 publications

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“…Kenyon and Schabanel [7], [22] study the case of a single "cost" attribute per item, assuming again a schedule of infinite size. Liaskos et al in [9] argued that realistic conditions can require an indefinite number of "cost" attributes per data item (dubbed multi-optimality), and presented a corresponding scheduler. However, [9] reinstated the infinite schedule size assumption, and provided neither proof nor evidence of existence of finite multi-optimal schedules.…”

Section: Related Workmentioning

confidence: 99%

“…Liaskos et al in [9] argued that realistic conditions can require an indefinite number of "cost" attributes per data item (dubbed multi-optimality), and presented a corresponding scheduler. However, [9] reinstated the infinite schedule size assumption, and provided neither proof nor evidence of existence of finite multi-optimal schedules. Furthermore, infinite size implies high complexity [4], meaning that the aforementioned scheduler is fit for infrastructure-based broadcasting only.…”

Section: Related Workmentioning

confidence: 99%

“…Push schedules are always periodic, i.e. repeating patterns, due to the absence of explicit client queries [9]. Each item has its own broadcast period, derived from its attributes.…”

Section: Introductionmentioning

confidence: 99%

“…Nonetheless, setting the item broadcast periods primarily by copyright and not by popularity induces a performance trade-off, raising the mean client waiting time. Therefore, a multi-optimal schedule is defined as one the minimizes the mean waiting time of the clients, subject to multiple mean (running) cost restrictions [7], [9].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Minimal Wireless Broadcast Schedules for Multi-objective Pursuits

Liaskos

Tsioliaridou

Papadimitriou

et al. 2014

IEEE Trans. Veh. Technol.

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Mobile wireless devices can now act as push-based data broadcasters, disseminating information in crowded places. While assuming this role, a device must take into account various factors, such as the mean service time, the energy expenditure or copyright costs. Apart from adhering to multiobjective optimality, a broadcast schedule must also be as small as possible in size, in order to be producible and cache-able on a mobile device. The present paper analytically proves the existence of optimal schedules that are finite, minimal in size. Furthermore, the optimality of the schedule is allowed to refer to an unlimited number of criteria. The analysis shows that multi-objective optimality can be met precisely by extremely small schedules, enabling their use in mobile devices. Simulations indicate perfect efficiency of the minimal schedules in realistic application scenarios.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

“…Push schedules are always periodic, i.e. repeating patterns, due to the absence of explicit client queries [9]. Each item has its own broadcast period, derived from its attributes.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Minimal Wireless Broadcast Schedules for Multi-objective Pursuits

Liaskos

Tsioliaridou

Papadimitriou

et al. 2014

IEEE Trans. Veh. Technol.

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“…Such estimates are obtained using the average number of neighbors of all vehicles in the hovering area, which is in turn calculated online by means of a beaconing mechanism. The proposed scheme has been successfully applied to broadcast applications in [13] and [14].…”

Section: Introductionmentioning

confidence: 99%

Adaptive information hovering in VANETs: Robustness and enhancements

Xeros

Constantinides

Lestas

et al. 2013

2013 International Conference on Connected Vehicles and Expo (ICCVE)

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Information hovering is relevant in vehicular ad hoc networks in cases where critical information needs to be made available to all vehicles in a bounded geographical area, called the hovering area, for a specific amount of time. In cases of low traffic density within the hovering area, a number of vehicles may not receive the critical information due to partitioning of the vehicular network. In previous work we proposed an information hovering scheme which increases the achieved reachability, by employing probabilistic flooding outside the hovering area. Informed vehicles outside the hovering area offer alternative paths towards the uninformed vehicles thus increasing reachability. In this work we investigate the robustness of the proposed protocol with respect to changing hovering area, transmission range of the vehicles and the message loss probability. We verify that the protocol continues to work effectively in all scenarios outperforming other approaches which have been proposed in literature. In addition, we investigate enhancements to the proposed protocol which ensure improved performance in cases of high traffic density within the hovering area. We apply probabilistic flooding within the hovering area and we observe that retransmission probabilities less than one suffice to lead to high reachability values.

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An on-demanded data broadcasting scheduling considering the data item size

Xia

et al. 2014

Wireless Netw

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Broadcast Scheduling With Multiple Concurrent Costs

Cited by 10 publications

References 30 publications

Minimal Wireless Broadcast Schedules for Multi-objective Pursuits

Minimal Wireless Broadcast Schedules for Multi-objective Pursuits

Adaptive information hovering in VANETs: Robustness and enhancements

An on-demanded data broadcasting scheduling considering the data item size

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