Efficient Packet Scheduling Using Channel Adaptive Fair Queueing in Distributed Mobile Computing Systems

Wang, Li; Kwok, Yue Kuen; Lau, Wing-Cheong; Lau, Vincent K. N.

doi:10.1023/b:mone.0000031589.32967.0f

Cited by 14 publications

(10 citation statements)

References 28 publications

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“…This can be justified as follows. The difference between the average SNR of the two direct links (A → B, A → C) is not very important (2 dB), and thus, the analytical expressions of the two SNR-based schedulers become equivalent [see (15)]. Moreover, we can see that node C has a better performance than node B.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…The optimization of these three characteristics is the basic target of a "good" scheduling scheme. From a user's point of view, the optimization of the resource sharing corresponds to an equal distribution of the available resources between the users (nodes) [15]. Moreover, a performance optimization can be achieved by the support of the multiuser-diversity concept [16].…”

Section: Three Required Features Of a Scheduling Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

Scheduling for Amplify-and-Forward Cooperative Networks

Krikidis

Belfiore

2007

IEEE Trans. Veh. Technol.

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We consider a basic cooperative network that is composed of three nodes which use Amplify-and-Forward as a cooperative strategy. This simple setup assumes that each time, one node is the source, one node is the relay, and one node is the destination. Here, we focus on the scheduling problem, which is defined as the distribution of the three roles (source, relay, and destination) to the three nodes. Based on two extreme scheduling approaches, which are a periodical and an instantaneous channel-based distribution of the roles, we propose a number of scheduling algorithms. These algorithms are classified according to three essential design features: fairness, channel adaptation, and distributed coordination. These features are related to the equilibrium, the performance, and the computational complexity of a scheduling algorithm. Among the approaches presented, there is one which jointly satisfies all of them and, thus, is the most appropriate. This solution combines a "smart" round-robin source selection with a normalized instantaneous signal-to-noise ratio relay selection and seems to be a practical solution for ad hoc systems. The proposed algorithms are compared, and their advantages/disadvantages are obtained by analytical and simulation results.

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Section: Numerical Resultsmentioning

confidence: 99%

Section: Three Required Features Of a Scheduling Algorithmmentioning

confidence: 99%

Scheduling for Amplify-and-Forward Cooperative Networks

Krikidis

Belfiore

2007

IEEE Trans. Veh. Technol.

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“…• extend our proposed algorithm with a generalized channel model with a set of channel states, like the one described in [21], so as to better capture the channel adaptive behaviour with the state of a link; • design a proper admission control scheme and combine it with the setting of goodput thresholds to maintain a certain efficiency target; and • devise an adaptive algorithm to dynamically adjust the goodput thresholds.…”

Section: Discussionmentioning

confidence: 99%

“…Channel adaptive fair queueing (CAFQ) [21] attempts to provide outcome fairness by defining a new notion of fairness, known as channel-adaptive fairness (CAF), to account for the effect of throughput variation due to different states of a link. A parameter Δ is used to keep track of the difference of the service received by a real system and an idealized one.…”

Section: Related Workmentioning

confidence: 99%

Bandwidth-Guaranteed Fair Scheduling with Effective Excess Bandwidth Allocation for Wireless Networks

Cao

Leung²,

Li³

2008

IEEE Trans. Wireless Commun.

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“…Wang and his colleagues [21] address the problem that the current channel model is overly simplified with a good state and a bad state. They argue that the current scheduling algorithms designed with the channel model cannot work properly in the practical environment, which is much more complicated than the two-state model.…”

Section: Fair Queuing Algorithmsmentioning

confidence: 99%