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71
Scheduling Algorithms for a Mixture of RealTime and NonRealTime Data in HDR
 in Proceedings of 17th International Teletraffic Congress (ITC17
"... High Data Rate (HDR) technologz has recently been proposed as an overlay to CDMA... In this paper, we study various scheduling algorithms for a mixture of realtime and nonrealtime data over HDR/CDMA and compare their performance. We study the performance with respect to packet delays and also ave ..."
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Cited by 142 (1 self)
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High Data Rate (HDR) technologz has recently been proposed as an overlay to CDMA... In this paper, we study various scheduling algorithms for a mixture of realtime and nonrealtime data over HDR/CDMA and compare their performance. We study the performance with respect to packet delays and also average throughput, where we use a token based mechanism to give minimum throughput guarantees. We nd that a rule which we call the exponential rule performs well with regard to both these criteria. (In a companion paper, we show that this rule is throughputoptimal, i.e., it makes the queues stable if it is feasible to do so with any other scheduling rule.) Our main conclusion is that intelligent scheduling algorithms in conjunction with token based rate control provide an ecient framework for supporting a mixture of realtime and nonrealtime data applications in a single carrier.
Scheduling in a Queueing System with Asynchronously Varying Service Rates
 Probability in the Engineering and Informational Sciences
"... We consider the following queueing system which arises as a model of a wireless link shared by multiple users. There is a nite number N of input
ows served by a server. The system operates in discrete time t = 0; 1; 2; : : :. Each input
ow can be described as an irreducible countable Markov chain; ..."
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Cited by 94 (8 self)
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We consider the following queueing system which arises as a model of a wireless link shared by multiple users. There is a nite number N of input
ows served by a server. The system operates in discrete time t = 0; 1; 2; : : :. Each input
ow can be described as an irreducible countable Markov chain; waiting customers of each
ow are placed in a queue. The sequence of server states m(t); t = 0; 1; 2; : : : , is a Markov chain with nite number of states M. When server is in state m it can serve m i customers of ow i (in one time slot). The scheduling discipline is a rule that in each time slot chooses the
ow to serve based on the server state and the state of the queues. Our main result is that a simple online scheduling discipline, Modied Largest Weighted Delay First, along with its generalizations, is throughput optimal, namely it ensures that the queues are stable as long as the vector of average arrival rates is within the system maximum stability region. 1
CDMA data QoS scheduling on the forward link with variable channel conditions
, 2000
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Generalized Proportional Fair Scheduling in Third Generation Wireless Data Networks
"... In 3G data networks, network operators would like to balance system throughput while serving users in a fair manner. This is achieved using the notion of proportional fairness. However, so far, proportional fairness has been applied at each base station independently. Such an approach can result in ..."
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Cited by 54 (1 self)
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In 3G data networks, network operators would like to balance system throughput while serving users in a fair manner. This is achieved using the notion of proportional fairness. However, so far, proportional fairness has been applied at each base station independently. Such an approach can result in nonPareto optimal bandwidth allocation when considering the network as a whole. Therefore, it is important to consider proportional fairness in a networkwide context with user associations to base stations governed by optimizing a generalized proportional fairness objective. In this paper, we take the first step in formulating and studying this problem rigorously. We show that the general problem is NPhard and it is also hard to obtain a closetooptimal solution. We then consider a special case where multiuser diversity only depends on the number of users scheduled together. We propose efficient offline optimal algorithms and heuristicbased greedy online algorithms to solve this problem. Using detailed simulations based on the base station layout of a large service provider in the U.S., we show that our simple online algorithm, which assigns a newly arrived user to a base station that improves the generalized proportional fairness objective the most without changing existing users ’ association, is very close to the offline optimal solution. The greedy algorithm can achieve significantly better throughput and fairness in heterogeneous user distributions, when compared to the approach that assigns a user to the base station with the best signal strength.
A theory of QoS for wireless
 In Proc. of IEEE INFOCOM
, 2009
"... Abstract—Wireless networks are increasingly used to carry applications with QoS constraints. Two problems arise when dealing with traffic with QoS constraints. One is admission control, which consists of determining whether it is possible to fulfill the demands of a set of clients. The other is find ..."
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Cited by 49 (17 self)
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Abstract—Wireless networks are increasingly used to carry applications with QoS constraints. Two problems arise when dealing with traffic with QoS constraints. One is admission control, which consists of determining whether it is possible to fulfill the demands of a set of clients. The other is finding an optimal scheduling policy to meet the demands of all clients. In this paper, we propose a framework for jointly addressing three QoS criteria: delay, delivery ratio, and channel reliability. We analytically prove the necessary and sufficient condition for a set of clients to be feasible with respect to the above three criteria. We then establish an efficient algorithm for admission control to decide whether a set of clients is feasible. We further propose two scheduling policies and prove that they are feasibility optimal in the sense that they can meet the demands of every feasible set of clients. In addition, we show that these policies are easily implementable on the IEEE 802.11 mechanisms. We also present the results of simulation studies that appear to confirm the theoretical studies and suggest that the proposed policies outperform others tested under a variety of settings. I.
A large deviations analysis of scheduling in wireless networks
 Earlier versions of the paper appeared in the IEEE CDC 2004, IEEE CDC 2005 and IEEE ISIT
, 2006
"... We consider a cellular network consisting of a base station and N receivers. The channel states of the receivers are assumed to be identical and independent of each other. The goal is to compare the throughput of two different scheduling policies (a queuelengthbased policy and a greedy scheduling ..."
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Cited by 37 (7 self)
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We consider a cellular network consisting of a base station and N receivers. The channel states of the receivers are assumed to be identical and independent of each other. The goal is to compare the throughput of two different scheduling policies (a queuelengthbased policy and a greedy scheduling policy) given an upper bound on the queue overflow probability or the delay violation probability. We first consider a simple channel model, where each channel is assumed to be in one of two states (ON or OFF). Given an upper bound on the delay violation probability or an upper bound on the queue overflow probability, we show that the total network throughput of the queuelengthbased policy is strictly larger than the throughput of the greedy policy for all N. Further, the throughput of the queuelengthbased policy is a strictly increasing function of N while the throughput of the greedy policy does not have this property. Finally, for general channel state models, we show that the relative performances of the the greedy and QLB policies have a similar behavior. policy.
Scheduling in IEEE 802.16e Mobile WiMAX Networks: Key Issues and a Survey
 IEEE JOURNAL ON SPECIAL AREAS IN COMMUNICATIONS (JSAC)
, 2009
"... Abstract — Interest in broadband wireless access (BWA) has been growing due to increased user mobility and the need for data access at all times. IEEE 802.16e based WiMAX networks promise the best available quality of experience for mobile data service users. Unlike wireless LANs, WiMAX networks inc ..."
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Cited by 35 (4 self)
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Abstract — Interest in broadband wireless access (BWA) has been growing due to increased user mobility and the need for data access at all times. IEEE 802.16e based WiMAX networks promise the best available quality of experience for mobile data service users. Unlike wireless LANs, WiMAX networks incorporate several quality of service (QoS) mechanisms at the Media Access Control (MAC) level for guaranteed services for data, voice and video. The problem of assuring QoS is basically that of how to allocate available resources among users in order to meet the QoS criteria such as delay, delay jitter and throughput requirements. IEEE standard does not include a standard scheduling mechanism and leaves it for implementer differentiation. Scheduling is, therefore, of special interest to all WiMAX equipment makers and service providers. This paper discusses the key issues and design factors to be considered for scheduler designers. In addition, we present an extensive survey of recent scheduling research. We classify the proposed mechanisms based on the use of channel conditions. The goals of scheduling are to achieve the optimal usage of resources, to assure the QoS guarantees, to maximize goodput and to minimize power consumption while ensuring feasible algorithm complexity and system scalability.
Downlink packet scheduling in LTE cellular networks: Key design issues and a survey
 IEEE Communications Surveys and Tutorials
, 2013
"... Future generation cellular networks are expected to provide ubiquitous broadband access to a continuously growing number of mobile users. In this context, LTE systems represent an important milestone towards the so called 4G cellular networks. A key feature of LTE is the adoption of advanced Radio ..."
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Cited by 20 (2 self)
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Future generation cellular networks are expected to provide ubiquitous broadband access to a continuously growing number of mobile users. In this context, LTE systems represent an important milestone towards the so called 4G cellular networks. A key feature of LTE is the adoption of advanced Radio Resource Management procedures in order to increase the system performance up to the Shannon limit. Packet scheduling mechanisms, in particular, play a fundamental role, because they are responsible for choosing, with fine time and frequency resolutions, how to distribute radio resources among different stations, taking into account channel condition and QoS requirements. This goal should be accomplished by providing, at the same time, an optimal tradeoff between spectral efficiency and fairness. In this context, this paper provides an overview on the key issues that arise in the design of a resource allocation algorithm for LTE networks. It is intended for a wide range of readers as it covers the topic from basics to advanced aspects. The downlink channel under frequency division duplex configuration is considered as object of our study, but most of the considerations are valid for other configurations as well. Moreover, a survey on the most recent techniques is reported, including a classification of the different approaches presented in literature. Performance comparisons of the most wellknown schemes, with particular focus
Manysources Delay Asymptotics with Applications to Priority Queues
"... In this paper, we study discretetime priority queueing systems fed by a large number of arrival streams. We first provide bounds on the actual delay asymptote in terms of the virtual delay asymptote. Then, under suitable assumptions on the arrival process to the queue, we show that these asymptote ..."
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Cited by 18 (5 self)
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In this paper, we study discretetime priority queueing systems fed by a large number of arrival streams. We first provide bounds on the actual delay asymptote in terms of the virtual delay asymptote. Then, under suitable assumptions on the arrival process to the queue, we show that these asymptotes are the same. As an application of this result, we then consider a priority queueing system with two queues. Using the earlier result, we derive an upper bound on the tail probability of the delay. Under certain assumptions on the rate function of the arrival process, we show that the upper bound is tight. We then consider a system with Markovian arrivals and numerically evaluate the delay tail probability and validate these results with simulations.
Control of EndtoEnd Delay Tails in a Multiclass Network: LWDF Discipline Optimality
 Annals of Applied Probability
"... We consider a multiclass queueing network with N customer classes, each having an arbitrary fixed route through the network. (Thus, the network is not necessarily feedforward.) We show that the largest weighted delay first (LWDF) discipline is an optimal scheduling discipline in the network in the f ..."
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Cited by 18 (2 self)
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We consider a multiclass queueing network with N customer classes, each having an arbitrary fixed route through the network. (Thus, the network is not necessarily feedforward.) We show that the largest weighted delay first (LWDF) discipline is an optimal scheduling discipline in the network in the following sense. Let wi be the (random) instantaneous largest endtoend delay of a class i customer in the network in stationary regime. For any set of positive constants α1,...,αN, the LWDF discipline associated with this set maximizes (among all disciplines) the quantity (1) min αi lim i=1,...,N n→∞ −1 n log P(wi>n) = lim n→∞ −1 log P(r>n), n where r. = maxi wi/αi is the maximal weighted delay in the network. [This result is a generalization of the singleserver result proved by A. L. Stolyar and K. Ramanan in Ann. Appl. Probab. 11 (2001) 1–48.] As the key element of the proof, we establish the following critical node property: In a LWDF network, there exists a most likely path to build large r, which is a most likely path to do so in one of the network nodes in isolation. Such a most likely path has a very simple structure: its parameters [and the optimal value of (1)] can be computed by solving a finitedimensional optimization problem for each network node.