An opportunistic and non-anticipating size-aware scheduling proposal for mean holding cost minimization in time-varying channels

In this paper we study how to design a scheduling strategy aimed at minimizing the average holding cost for flows with general size distribution when the feasible transmission rate of each user varies randomly over time. We employ a Whittle-index-based approach in order to achieve an opportunistic and non-anticipating size-aware scheduling index rule proposal. When the flow size distribution belongs to the Decreasing Hazard Rate class, we propose the so-called Attained Service Potential Improvement index rule, which consists in giving priority to the flows with the highest ratio between the current attained-service-dependent completion probability and the expected potential improvement of this completion probability. We further analyze the performance of the proposed scheduler, concluding that it outperforms well-known opportunistic disciplines

Nearly-optimal scheduling of users with Markovian time-varying transmission rates

We address the problem of developing a well-performing and implementable scheduler of users with wireless connections to the central controller, which arise in areas such as mobile data networks, heterogeneous networks, or vehicular communications systems. The main feature of such systems is that the connection quality of each user is time-varying, resulting in time-varying transmission rate corresponding to available channel states. We assume that this evolution is Markovian, relaxing the common but unrealistic assumption of stationary channels. We first focus on the three-state channel and study the optimal policy, showing that threshold policies (of giving higher priority to users with higher transmission rate) are not necessarily optimal. For the general channel we design a scheduler which generalizes the recently proposed Potential Improvement (PI) scheduler, and propose its two practical approximations, whose performance is analyzed and compared to existing alternative schedulers in a variety of simulation scenarios. We suggest and give evidence that the variant of PI which only relies on the steady-state distribution of the channel, performs extremely well, and therefore should be used for practical implementation

Scheduling in a random environment: stability and asymptotic optimality

International audienceWe investigate the scheduling of a common resource between several concurrent users when the feasible transmission rate of each user varies randomly over time. Time is slotted, and users arrive and depart upon service completion. This may model, for example, the flow-level behavior of end-users in a narrowband HDR wireless channel (CDMA 1xEV-DO). As performance criteria, we consider the stability of the system and the mean delay experienced by the users. Given the complexity of the problem, we investigate the fluid-scaled system, which allows to obtain important results and insights for the original system: 1) We characterize for a large class of scheduling policies the stability conditions and identify a set of maximum stable policies, giving in each time-slot preference to users being in their best possible channel condition. We find in particular that many opportunistic scheduling policies like Score-Based, Proportionally Best, or Potential Improvement are stable under the maximum stability conditions, whereas the opportunistic scheduler Relative-Best or the cμ-rule are not. 2) We show that choosing the right tie-breaking rule is crucial for the performance (e.g., average delay) as perceived by a user. We prove that a policy is asymptotically optimal if it is maximum stable and the tie-breaking rule gives priority to the user with the highest departure probability. We will refer to such tie-breaking rule as myopic. 3) We derive the growth rates of the number of users in the system in overload settings under various policies, which give additional insights on the performance. 4) We conclude that simple priority-index policies with the myopic tie-breaking rule are stable and asymptotically optimal. All our findings are validated with extensive numerical experiments

A Novel Scheduling Index Rule Proposal for QoE Maximization in Wireless Networks

This paper deals with the resource allocation problem aimed at maximizing users’ perception of quality in wireless channels with time-varying capacity. First of all, we model the subjective quality-aware scheduling problem in the framework of Markovian decision processes. Then, given that the obtaining of the optimal solution of this model is unachievable, we propose a simple scheduling index rule with closed-form expression by using a methodology based on Whittle approach. Finally, we analyze the performance of the achieved scheduling proposal in several relevant scenarios, concluding that it outperforms the most popular existing resource allocation strategies

Tidal range technologies and state of the art in review

Tidal range technology has seen much development and interest in recent years. The times when a barrage scheme would be rejected due to environmental and cost concerns is coming to an end. A large variety of new lower cost and less invasive methods have since emerged in the forms of tidal lagoons, reefs and fences. Since the construction of La Rance in 1967, advancements in turbine technologies and design has since resulted in a plethora of new, exciting turbine designs for tidal energy. A selection of new turbines with possible tidal range applications includes the modified bulb turbine with two sets of guide vanes, a counter-rotating turbine, Archimedes screw and a gyro device. However, the same design is continuously being chosen – the Kaplan bulb turbine. Through the use of a marking criterion covering key aspects that should be considered when choosing a turbine a variety of the new designs available are investigated. The key aspects researched include, environmental effects, the two-way efficiency, initial costs and maintenance costs/difficulty

Flow-level stability and performance of channel-aware priority-based schedulers

Abstract—Channel-aware scheduling in modern wireless networks enables the system to exploit the random rate variations across different users to increase the performance of the system. We analyze channel-aware priority-based downlink scheduling policies at the so-called flow level with a stochastically varying number of users. The priority can be any monotonously increasing function of the instantaneous rate of the user, which generalizes the well-known linear weight-based policies. Also, ties are allowed within a user class, as well as between user classes. As the main result, we characterize when these priority-based policies are stable under an intuitive necessary condition, which holds for arbitrary tie breaking rules and is independent of the flow size distribution. Additionally, for the policies for which the necessary condition is not sufficient, a more stringent condition is derived in the case of two traffic classes. Finally, extensive simulations have been performed to compare the performance of different priority-based and utility-based policies. I

Resource allocation in wireless access network : A queueing theoretic approach

To meet its performance targets, the future 5G networks need to greatly optimize the Radio Access Networks (RANs), which connect the end users to the core network. In this thesis, we develop mathematical models to study three aspects of the operation of the RAN in modern wireless systems. The models are analyzed using  the techniques borrowed mainly from queueing theory and stochastic control. Also, simulations are extensively used to gain further insights. First, we provide a detailed Markov model of the random access process in LTE. From this, we observe that the bottleneck in the signaling channel causes congestion in the  access  when a large number of M2M devices attempt to enter the network. Then, in the context of the so-called Heterogeneous networks (HetNets), we suggest  dynamic load balancing schemes that alleviate this congestion and reduce the overall access delay. We then use flow-level models for elastic data traffic to study the problem of coordinating the activities of the neighboring base stations.  We seek to minimize the flow-level delay when there are various classes of users. We classify the users based on their locations, or, in dynamic TDD systems, on the direction of service the network is providing to them. Using interacting queues and different operating policies of running such queues, we study the amount of gain the dynamic policies can provide over the static probabilistic policies. Our results show that simple dynamic policies can  provide very good performance in the cases considered. Finally, we consider the problem of opportunistically scheduling the flows of users with time-varying channels  taking into account   the size of data they need to transfer. Using flow-level models in a system with homogeneous channels, we provide the optimal scheduling policy when there are  no new job arrivals. We also suggest the method to implement such a policy in a time-slotted system. With heterogeneous channels, the problem is intractable for the flow-level techniques. Therefore, we utilize the framework of the restless-multi-armed-bandit (RMAB) problems employing the so-called Whittle index approach. The Whittle index approach, by relaxing the scheduling constraints, makes the problem separable, and thereby provides an exact solution to the modified problem. Our simulations suggest that when  this solution is applied as a heuristic to the original problem, it gives good performance, even with dynamic job arrivals

Packet scheduling in satellite LTE networks employing MIMO technology.

Doctor of Philosophy in Electronic Engineering. University of KwaZulu-Natal, Durban 2014.Rapid growth in the number of mobile users and ongoing demand for different types of telecommunication services from mobile networks, have driven the need for new technologies that provide high data rates and satisfy their respective Quality of Service (QoS) requirements, irrespective of their location. The satellite component will play a vital role in these new technologies, since the terrestrial component is not able to provide global coverage due to economic and technical limitations. This has led to the emergence of Satellite Long Term Evolution (LTE) networks which employ Multiple-In Multiple-Out (MIMO) technology. In order to achieve the set QoS targets, required data rates and fairness among various users with different traffic demands in the satellite LTE network, it is crucial to design an effective scheduling and a sub-channel allocation scheme that will provide an optimal balance of all these requirements. It is against this background that this study investigates packet scheduling in satellite LTE networks employing MIMO technology. One of the main foci of this study is to propose new cross-layer based packet scheduling schemes, tagged Queue Aware Fair (QAF) and Channel Based Queue Sensitive (CBQS) scheduling schemes. The proposed schemes are designed to improve both fairness and network throughput without compromising users’ QoS demands, as they provide a good trade-off between throughput, QoS demands and fairness. They also improve the performance of the network in comparison with other scheduling schemes. The comparison is determined through simulations. Due to the fact that recent schedulers provide a trade-off among major performance indices, a new performance index to evaluate the overall performance of each scheduler is derived. This index is tagged the Scheduling Performance Metric (SPM). The study also investigates the impact of the long propagation delay and different effective isotropic radiated powers on the performance of the satellite LTE network. The results show that both have a significant impact on network performance. In order to actualize an optimal scheduling scheme for the satellite LTE network, the scheduling problem is formulated as an optimization function and an optimal solution is obtained using Karush-Kuhn-Tucker multipliers. The obtained Near Optimal Scheduling Scheme (NOSS), whose aim is to maximize the network throughput without compromising users’ QoS demands and fairness, provides better throughput and spectral efficiency performance than other schedulers. The comparison is determined through simulations. Based on the new SPM, the proposed NOSS1 and NOSS2 outperform other schedulers. A stability analysis is also presented to determine whether or not the proposed scheduler will provide a stable network. A fluid limit technique is used for the stability analysis. Finally, a sub-channel allocation scheme is proposed, with the aim of providing a better sub-channel or Physical Resource Block (PRB) allocation method, tagged the Utility Auction Based (UAB) subchannel allocation scheme that will improve the system performance of the satellite LTE network. The results show that the proposed method performs better than the other scheme. The comparison is obtained through simulations