In this work, different heuristic and optimization algorithms are proposed for downstream wavelength scheduling in ring-based WDM-PON mobile backhaul networks, where optical networking units (ONUs) are integrated with...
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In this work, different heuristic and optimization algorithms are proposed for downstream wavelength scheduling in ring-based WDM-PON mobile backhaul networks, where optical networking units (ONUs) are integrated with base stations (BSs). The main objective of this work is to improve the time delay of the packet delivery from the infrastructure to the end-users for both fixed and wireless traffic. This is achieved through dynamic wavelength scheduling and sharing techniques in a converged ring-based WDM-PON access architecture by taking into account the priorities of the data sent and also the cooperation area for mobile users between adjacent ONUs/BSs. Further, an integer linear program (ILP) was developed for wavelength selection, to be used as a benchmark when comparing with the two proposed algorithms. All heuristic algorithms and the optimization algorithm are examined under different traffic load and queue size scenarios to ascertain the network's performance in terms of maximum packet delivery delay.
Age of information is a new network performance metric that captures the freshness of information at end-users. This paper studies the age of information from a scheduling perspective. To that end, we consider a wirel...
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Age of information is a new network performance metric that captures the freshness of information at end-users. This paper studies the age of information from a scheduling perspective. To that end, we consider a wireless broadcast network where a basestation (BS) is updating many users on random information arrivals under a transmission capacity constraint. For the offline case when the arrival statistics are known to the BS, we develop a structural MDP scheduling algorithm and an index scheduling algorithm, leveraging Markov decision process (MDP) techniques and the Whittle's methodology for restless bandits. By exploring optimal structural results, we not only reduce the computational complexity of the MDP-based algorithm, but also simplify deriving a closed form of the Whittle index. Moreover, for the online case, we develop an MDP-based online scheduling algorithm and an index-based online scheduling algorithm. Both the structural MDP scheduling algorithm and the MDP-based online scheduling algorithm asymptotically minimize the average age, while the index scheduling algorithm minimizes the average age when the information arrival rates for all users are the same. Finally, the algorithms are validated via extensive numerical studies.
This paper describes algorithms for scheduling traffic in wireless data networks with multiple channels per cell. The paper assumes that a reservation-based medium access control protocol is used. The main objective o...
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This paper describes algorithms for scheduling traffic in wireless data networks with multiple channels per cell. The paper assumes that a reservation-based medium access control protocol is used. The main objective of the scheduling algorithms is to reduce the computation time while maximizing the utilization of the network resources, thereby improving the system throughput. The scheduling problem is presented as a variant of the bin-packing problem. In this paper, we consider two type of algorithms-contiguous and non-contiguous allocations. The algorithms are studied for wireless networks with single priority traffic and multiple priority traffic. A performance study that considers network utilization, computation time, and the throughput for 10 and 54 Mbps data-streams is presented. The results show that both the proposed algorithms perform better than MULTI-FIT in terms of overall throughput and computation time;and that the non-contiguous allocation performs better than the contiguous algorithm since the former results in smaller number of wasted slots. (C) 2002 Elsevier Science B.V. All rights reserved.
The capacity-achieving coding scheme for the multiple-input multiple-output (MIMO) broadcast channel is dirty-paper coding. With this type of transmission scheme the optimal number of active users that receive data an...
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The capacity-achieving coding scheme for the multiple-input multiple-output (MIMO) broadcast channel is dirty-paper coding. With this type of transmission scheme the optimal number of active users that receive data and the optimal power allocation strategy are highly dependent on the structure of the channel matrix and on the total transmit power available. In the context of packet-data access with adaptive transmission where mobile users are equipped with a single receive antenna and the base station has multiple transmit antennas, we study the optimal number of active users and the optimal power allocation. In the particular case of two transmit antennas, we prove that the optimal number of active users can be a non-monotonic function of the total transmit power. Thus not only the number of users that should optimally be served simultaneously depends on the user channel vectors but also on the power available at the base station transmitter. The expected complexity of optimal scheduling algorithms is thus very high. Yet we then prove that at most as many users as the number of transmit antennas are allocated a large amount of power asymptotically in the high-power region in order to achieve the sum-capacity. Simulations confirm that constraining the number of active users to be no more than the number of transmit antennas incurs only a marginal loss in spectral efficiency. Based on these observations, we propose low-complexity scheduling algorithms with sub-optimal transmission schemes that can approach the sum-capacity of the MIMO broadcast channel by taking advantage of multiuser diversity. The suitability of known antenna selection algorithms is also demonstrated. We consider the cases of complete and partial channel knowledge at the transmitter. We provide simulation results to illustrate our conclusions.
We provide scheduling algorithms that attempt to maximize the profits of a broadcast-based electronic delivery service for digital products purchased, for example, at e-commerce sites on the World Wide Web. Examples o...
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We provide scheduling algorithms that attempt to maximize the profits of a broadcast-based electronic delivery service for digital products purchased, for example, at e-commerce sites on the World Wide Web. Examples of such products include multimedia objects such as CDs and DVDs. Other examples include software and, with increasing popularity, electronic books as well. We consider two separate alternatives, depending in part on the sophistication of the set-top box receiving the product at the customer end. The first, more restrictive option, assumes that the atomic unit of transmission of the product is the entire object, which must be transmitted in order from start to finish. We provide a solution based in part on a transportation problem formulation for this so-called noncyclic scheduling problem. The second alternative, which is less restrictive, assumes that the product may be transmitted cyclically in smaller segments, starting from an arbitrary point in the object. Three heuristics are provided for this difficult cyclic scheduling problem. Both scenarios assume that the broadcasts of the same digital product to multiple customers can be "batched." We examine the effectiveness of these algorithms via simulation experiments under varying parametric assumptions. Each of the three cyclic scheduling algorithms perform better than the noncyclic algorithm. Moreover, one of the cyclic scheduling algorithms emerges as the clear winner.
A task that suspends itself to wait for an I/O completion or to wait for an event from another node in distributed environments is called an I/O blocking task. In conventional hard real-time scheduling theories, there...
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ISBN:
(纸本)9780769529752
A task that suspends itself to wait for an I/O completion or to wait for an event from another node in distributed environments is called an I/O blocking task. In conventional hard real-time scheduling theories, there exist several approaches to schedule such I/O blocking tasks within the conventional framework of rate monotonic analysis (RMA). However most of them are pessimistic. In this paper we propose effective algorithms that can schedule a task set which includes I/O blocking tasks under dynamic priority assignment. We present a new critical instant theorem for multi-frame task set under dynamic priority assignment. The schedulability is analyzed under the new critical instant theorem. For the schedulability analysis, this paper presents saturation summation which is used to calculate maximum interference function (MIF). With the saturation summation, the schedulability of a task set including I/O blocking tasks can be analyzed more accurately. We propose an algorithm which is based on a Frame Laxity Monotonic scheduling (FLMS). Genetic algorithm is also applied. From our experiments, we can conclude that the FLMS can significantly reduce the time of the calculation time, and GA can improve task schedulability ratio than the FLMS.
As the penetration level of plug-in hybrid electric vehicles (PHEVs) increases, the stress on the distribution system will become more pronounced. In this paper, we concentrate on PHEV charging in public infrastructur...
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ISBN:
(纸本)9781457710964;9781457710957
As the penetration level of plug-in hybrid electric vehicles (PHEVs) increases, the stress on the distribution system will become more pronounced. In this paper, we concentrate on PHEV charging in public infrastructures, such as shared parking lots in commercial office campuses and shopping malls. In such clustered scenarios, PHEV charging demand can vary significantly and stochastically with time, and the overall system performance is a result of a trade-off between the peak load on the distribution system and the consumer specified charging deadlines that are met successfully. However, unlike distributed residential charging, those scenarios can benefit from centralized algorithms to schedule the charging of vehicles. This paper considers the design of such scheduling algorithms. We show that through proper design of the scheduling algorithms, the parking lot owner can balance distribution system load with quality of charging service.
In the paper we consider tree-based L-level convergecast networks, in which leaf nodes correspond to data sources (DS), a root node - to a base station (BS), and other nodes - to intermediate repeaters (IR). At a star...
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ISBN:
(纸本)9781479940509
In the paper we consider tree-based L-level convergecast networks, in which leaf nodes correspond to data sources (DS), a root node - to a base station (BS), and other nodes - to intermediate repeaters (IR). At a startup phase each DS generates a random number of messages for transmission to a BS. For such a model a lower bound for an average duration of collision-free convergecast is given. Also we propose a collision-free messages transmission scheduling algorithms for which the lower bound is achieved at L -> infinity.
The scheduling algorithm used in a network switch significantly impacts the switch's performance and thereby the performance of the entire network. To keep up with the ongoing demands for higher network performanc...
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ISBN:
(纸本)9781728102139
The scheduling algorithm used in a network switch significantly impacts the switch's performance and thereby the performance of the entire network. To keep up with the ongoing demands for higher network performance, a myriad of scheduling algorithms have been investigated. We propose that FPGAs can be outstanding candidates for benchmarking scheduling algorithms, and that it can be beneficial to have customized scheduling algorithms which are enabled by FPGA based switches due to their reconfigurable architectures. This paper presents the first FPGA targeted survey on high performance scheduling algorithms used in the most popular switch architecture, input-buffered crossbars, with the aim of guiding future research on high performance network switching.
The bus that connects processors to memory is known to be a major architectural bottleneck in SMPs. However, both software and scheduling policies for these systems generally focus on memory hierarchy optimizations an...
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ISBN:
(纸本)0769520170
The bus that connects processors to memory is known to be a major architectural bottleneck in SMPs. However, both software and scheduling policies for these systems generally focus on memory hierarchy optimizations and do not address the bus bandwidth limitations directly. In this paper we first present experimental results which indicate that bus saturation can cause an up to almost three-fold slow-down to applications. Motivated by these results, we introduce two scheduling policies that take into account the bus bandwidth consumption of applications. The necessary information is provided by performance monitoring counters which are present in all modern processors. Our algorithms organize jobs so that processes with high-bandwidth and low-bandwidth demands are co-scheduled to improve bus bandwidth utilization without saturating the bus. We found that our scheduler is effective with applications of varying bandwidth requirements, from very low to close to the limit of saturation. We also tuned our scheduler for robustness in the presence of bursts of high bus bandwidth consumption from individual jobs. The new scheduling policies improve system throughput by up to 68% (26% in average) in comparison with the standard Linux scheduler.
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