scholarly journals On the Optimal Control of Parallel Processing Networks with Resource Collaboration and Multitasking

2021 ◽  
Author(s):  
Erhun Özkan
Keyword(s):  
Parallel Processing ◽  
Heavy Traffic ◽  
Resource Scheduling ◽  
System Capacity ◽  
Parallel Networks ◽  
Holding Cost ◽  
Resource Collaboration ◽  
Synchronization Constraints ◽  
Diffusion Scale ◽  
Processing Networks

We study scheduling control of parallel processing networks in which some resources need to simultaneously collaborate to perform some activities and some resources multitask. Resource collaboration and multitasking give rise to synchronization constraints in resource scheduling when the resources are not divisible, that is, when the resources cannot be split. The synchronization constraints affect the system performance significantly. For example, because of those constraints, the system capacity can be strictly less than the capacity of the bottleneck resource. Furthermore, the resource scheduling decisions are not trivial under those constraints. For example, not all static prioritization policies retain the maximum system capacity, and the ones that retain the maximum system capacity do not necessarily minimize the delay (or, in general, the holding cost). We study optimal scheduling control of a class of parallel networks and propose a dynamic prioritization policy that retains the maximum system capacity and is asymptotically optimal in diffusion scale and a conventional heavy-traffic regime with respect to the expected discounted total holding cost objective.

scholarly journals Control of Fork-Join Processing Networks with Multiple Job Types and Parallel Shared Resources

2021 ◽  
Author(s):  
Erhun Özkan
Keyword(s):  
Queueing Networks ◽  
Queueing Network ◽  
Optimal Scheduling ◽  
Shared Resources ◽  
Asymptotically Optimal ◽  
Scheduling Policy ◽  
Synchronization Constraints ◽  
Processing Network ◽  
Diffusion Scale ◽  
Processing Networks

A fork-join processing network is a queueing network in which tasks associated with a job can be processed simultaneously. Fork-join processing networks are prevalent in computer systems, healthcare, manufacturing, project management, justice systems, and so on. Unlike the conventional queueing networks, fork-join processing networks have synchronization constraints that arise because of the parallel processing of tasks and can cause significant job delays. We study scheduling in fork-join processing networks with multiple job types and parallel shared resources. Jobs arriving in the system fork into arbitrary number of tasks, then those tasks are processed in parallel, and then they join and leave the network. There are shared resources processing multiple job types. We study the scheduling problem for those shared resources (i.e., which type of job to prioritize at any given time) and propose an asymptotically optimal scheduling policy in diffusion scale.

Passenger Boarding/Alighting Management in Urban Rail Transportation

2012 ◽  
Author(s):  
Sonia Baee ◽  
Farshad Eshghi ◽  
S. Mehdi Hashemi ◽  
Rayehe Moienfar
Keyword(s):  
Travel Time ◽  
System Performance ◽  
Heavy Traffic ◽  
System Capacity ◽  
Rapid Decline ◽  
Rail Transportation ◽  
Satisfaction Level ◽  
Urban Rail ◽  
Subway System ◽  
Measures Of Performance

Heavy traffic consequences in crowded cities can be extremely reduced by using mass transportation. Recent extensive studies on Tehran subway system, as a representative of crowded cities, show that ever increasing commutation demand results in rapid decline in service quality and satisfaction level, system capacity wastage, and poorer system performance. Since passenger boarding/alighting period is noticeable compared to the inter-station travel time, it seems that passenger boarding/alighting management would play a significant role in system performance improvement. Aiming at increasing satisfaction level and service success rate, while reducing travel time, different boarding/alighting strategies are proposed. Passengers behaviors are carefully simulated based on a microscopic model, through introducing an inclination function which governs a passengers movement in a two-dimensional queue. Simulation results, in terms of three aforementioned measures of performance, show that in less crowded stations, the first strategy, expectedly, outperforms the other two. However, in crowded stations (e.g. interchange stations) the third strategy outperforms the others significantly.

A Frequency Reuse Scheme Based on Interference Pre-Cancellation and Resource Scheduling for Multi-Beam Satellite Downlink Signal

2014 ◽  
Vol 548-549 ◽  
pp. 1085-1088
Author(s):  
Yi Nuo He ◽  
Wei Zheng ◽  
Bin Li ◽  
Ya Zhe Gao ◽  
Jian Jun Wu
Keyword(s):  
Spectral Efficiency ◽  
Scheduling Algorithm ◽  
Resource Scheduling ◽  
Satellite System ◽  
Frequency Reuse ◽  
System Capacity ◽  
Channel Interference ◽  
High Spectral Efficiency ◽  
Downlink Signal

A frequency reuse scheme is proposed in this paper for multi-beam satellite system to improve spectral efficiency as well as system capacity. Firstly, in order to reuse same channel among beams, Tomlinson-Harashima precoding (THP) is introduced to pre-cancel downlink interference of users from different beams. Secondly, a resource scheduling algorithm is proposed to jointly work with THP. Finally, simulations are executed to validate the proposed scheme, which suggest that compared to traditional frequency reuse scheme, the proposed frequency reuse scheme can successfully eliminate co-channel interference with a high spectral efficiency.

Optimal dynamic scheduling of a general class of parallel-processing queueing systems

1998 ◽  
Vol 30 (04) ◽  
pp. 1130-1156 ◽  
Author(s):  
Noah Gans ◽  
Garrett van Ryzin
Keyword(s):  
Parallel Processing ◽  
Closed Form ◽  
General Class ◽  
Dynamic Scheduling ◽  
Broad Class ◽  
Heavy Traffic ◽  
Queueing Systems ◽  
Optimal System ◽  
Call System ◽  
Optimal Dynamic

In this paper we develop policies for scheduling dynamically arriving jobs to a broad class of parallel-processing queueing systems. We show that in heavy traffic the policies asymptotically minimize a measure of the expected system backlog, which we call system work. Our results yield succinct, closed-form expressions for optimal system work in heavy traffic.

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