Base station scheduling of requests with fixed deadlines

Agarwal, Megha; Puri, A.

doi:10.1109/infcom.2002.1019293

Cited by 37 publications

(50 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1. In this field the QoS frame indicates its Traffic Category (0-7) or Traffic Stream (8)(9)(10)(11)(12)(13)(14)(15) and the size (in terms of number of bytes) of the corresponding queue in the QSTA. A QSTA which needs to request a new TXOP can transmit a Null QoS data frame, just to inform HC about the request.…”

Section: Hybrid Coordination Function-hcfmentioning

confidence: 99%

“…Reference [14] presents an architecture for fair queuing based scheduling where the medium access layer, link layer and network layer are optimized to achieve the desirable QoS using a multirate multipath transparent CDMA based physical layer. Finally, [15] studies the problem of scheduling QoS requests when the capacity of the channel between the base station and the mobiles varies due to fading. Among the main results of [15] has been that a simple greedy algorithm can be at least as efficient as the offline optimal algorithm, which needs to know all future channel conditions and requests.…”

Section: A Functional Characteristics Of An 80211e Traffic Schedulermentioning

confidence: 99%

“…Finally, [15] studies the problem of scheduling QoS requests when the capacity of the channel between the base station and the mobiles varies due to fading. Among the main results of [15] has been that a simple greedy algorithm can be at least as efficient as the offline optimal algorithm, which needs to know all future channel conditions and requests. It also shows that no online algorithm can do better.…”

Section: A Functional Characteristics Of An 80211e Traffic Schedulermentioning

confidence: 99%

“…The scheduler entity [11,14,15] which coexists with the Access Point of an infrastructure network, is responsible for the provision of QoS. To be specific, the accommodation of resource access and resource sharing among several users depends on the scheduler.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Providing quality of service guarantees in wireless LANs compliant with 802.11e

Korakis

2005

Computer Networks

View full text Add to dashboard Cite

Section: Hybrid Coordination Function-hcfmentioning

confidence: 99%

Section: A Functional Characteristics Of An 80211e Traffic Schedulermentioning

confidence: 99%

Section: A Functional Characteristics Of An 80211e Traffic Schedulermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Providing quality of service guarantees in wireless LANs compliant with 802.11e

Korakis

2005

Computer Networks

View full text Add to dashboard Cite

“…In [1] the authors discuss the scheduling problem with fixed deadlines and prove that the greedy algorithm performs no worse than half of offline optimal schedule in terms revenue. This approach considers the problem on a packet by packet basis and hence we feel that this approach is inappropriate for the real wireless scheduling systems.…”

Section: Previous Workmentioning

confidence: 99%

Opportunistic scheduling for wireless systems with multiple interfaces and multiple constraints

Kulkarni¹,

Rosenberg²

2003

Proceedings of the 8th International Workshop on Modeling Analysis and Simulation of Wireless and Mobile Systems - MSWIM '03

View full text Add to dashboard Cite

We consider a scheduling problem for packet based systems with time-varying channel conditions. Designing scheduling mechanisms that take advantage of time-varying channel conditions, which are different for different users, is necessary to improve system performance; however this has to be done in a way that provides some level of fairness among the users. Such scheduling mechanisms are termed as opportunistic. We generalize the opportunistic scheduling mechanisms in the literature on two fronts. First, we formulate and solve an opportunistic scheduling problem with multiple general long term QoS constraints and a general system objective function. We call the solution of this opportunistic scheduling problem as a generalized water filling solution. Then, we generalize this problem to include multiple interface systems in which several users can be served simultaneously. Apart from the long term QoS constraints specified by each user, multiple interface systems are constrained with other physical limitations imposed by the system structure. Our main contribution is to show that the structure of the optimal opportunistic scheduling policy is carried over to the problem with general constraints and multiple interfaces. We also study the stability of the multiple interface systems and propose a throughput optimal scheduling rule for such systems.

show abstract

Analytical modelling and performance evaluation of realistic time‐controlled M2M scheduling over LTE cellular networks

Gotsis

Lioumpas

Alexiou

2013

Trans Emerging Tel Tech

View full text Add to dashboard Cite

Supporting emerging machine-to-machine (M2M) communications over Long-term Evolution (LTE)/LTE Advanced cellular networks in an efficient way will be beneficial for both telecommunication communities. The first step to migrate to an M2M-enabled cellular standard is to provide these new services through the existing architectures and protocols, while maintaining seamless backward compatibility. To this end, we thoroughly examined a key LTE Medium Access Control entity, which is the packet scheduler, and proposed solutions based on the time-controlled M2M feature, to deal with the diverse M2M traffic characteristics and quality-of-service requirements. Starting from the single M2M class case, we extended our study to more realistic scenarios, involving more M2M classes with diverse quality-of-service requirements. We defined analytical models for predicting the system performance on the basis of queueing theory concepts and considered the interaction between classes with different priorities. The proposed analytical models are validated through extensive system-level simulations. On the basis of the insight obtained from our analytical approach, we modified an existing scheduling algorithm to improve the performance of low-priority M2M device groups, and we demonstrated its superior performance both experimentally and analytically.

show abstract

Base station scheduling of requests with fixed deadlines

Cited by 37 publications

References 16 publications

Providing quality of service guarantees in wireless LANs compliant with 802.11e

Providing quality of service guarantees in wireless LANs compliant with 802.11e

Opportunistic scheduling for wireless systems with multiple interfaces and multiple constraints

Analytical modelling and performance evaluation of realistic time‐controlled M2M scheduling over LTE cellular networks

Contact Info

Product

Resources

About