Network unfairness in dragonfly topologies

Dragonfly networks arrange network routers in a two-level hierarchy, providing a competitive cost-performance solution for large systems. Non-minimal adaptive routing (adaptive misrouting) is employed to fully exploit the path diversity and increase the performance under adversarial traffic patterns. Network fairness issues arise in the dragonfly for several combinations of traffic pattern, global misrouting and traffic prioritization policy. Such unfairness prevents a balanced use of the resources across the network nodes and degrades severely the performance of any application running on an affected node. This paper reviews the main causes behind network unfairness in dragonflies, including a new adversarial traffic pattern which can easily occur in actual systems and congests all the global output links of a single router. A solution for the observed unfairness is evaluated using age-based arbitration. Results show that age-based arbitration mitigates fairness issues, especially when using in-transit adaptive routing. However, when using source adaptive routing, the saturation of the new traffic pattern interferes with the mechanisms employed to detect remote congestion, and the problem grows with the network size. This makes source adaptive routing in dragonflies based on remote notifications prone to reduced performance, even when using age-based arbitration.Peer ReviewedPostprint (author's final draft

Deadlock avoidance with virtual channels

High Performance Computing is a rapidly evolving area of computer science which attends to solve complicated computational problems with the combination of computational nodes connected through high speed networks. This work concentrates on the networks problems that appear in such networks and specially focuses on the Deadlock problem that can decrease the efficiency of the communication or even destroy the balance and paralyze the network. Goal of this work is the Deadlock avoidance with the use of virtual channels, in the switches of the network where the problem appears. The deadlock avoidance assures that will not be loss of data inside network, having as result the increased latency of the served packets, due to the extra calculation that the switches have to make to apply the policy.La computación de alto rendimiento es una zona de rápida evolución de la informática que busca resolver complicados problemas de cálculo con la combinación de los nodos de cómputo conectados a través de redes de alta velocidad. Este trabajo se centra en los problemas de las redes que aparecen en este tipo de sistemas y especialmente se centra en el problema del "deadlock" que puede disminuir la eficacia de la comunicación con la paralización de la red. El objetivo de este trabajo es la evitación de deadlock con el uso de canales virtuales, en los conmutadores de la red donde aparece el problema. Evitar el deadlock asegura que no se producirá la pérdida de datos en red, teniendo como resultado el aumento de la latencia de los paquetes, debido al overhead extra de cálculo que los conmutadores tienen que hacer para aplicar la política.La computació d'alt rendiment és una àrea de ràpida evolució de la informàtica que pretén resoldre complicats problemes de càlcul amb la combinació de nodes de còmput connectats a través de xarxes d'alta velocitat. Aquest treball se centra en els problemes de les xarxes que apareixen en aquest tipus de sistemes i especialment se centra en el problema del "deadlock" que pot disminuir l'eficàcia de la comunicació amb la paralització de la xarxa. L'objectiu d'aquest treball és l'evitació de deadlock amb l'ús de canals virtuals, en els commutadors de la xarxa on apareix el problema. Evitar deadlock assegura que no es produirà la pèrdua de dades en xarxa, tenint com a resultat l'augment de la latència dels paquets, degut al overhead extra de càlcul que els commutadors han de fer per aplicar la política

COOR-PLT: A hierarchical control model for coordinating adaptive platoons of connected and autonomous vehicles at signal-free intersections based on deep reinforcement learning

Platooning and coordination are two implementation strategies that are frequently proposed for traffic control of connected and autonomous vehicles (CAVs) at signal-free intersections instead of using conventional traffic signals. However, few studies have attempted to integrate both strategies to better facilitate the CAV control at signal-free intersections. To this end, this study proposes a hierarchical control model, named COOR-PLT, to coordinate adaptive CAV platoons at a signal-free intersection based on deep reinforcement learning (DRL). COOR-PLT has a two-layer framework. The first layer uses a centralized control strategy to form adaptive platoons. The optimal size of each platoon is determined by considering multiple objectives (i.e., efficiency, fairness and energy saving). The second layer employs a decentralized control strategy to coordinate multiple platoons passing through the intersection. Each platoon is labeled with coordinated status or independent status, upon which its passing priority is determined. As an efficient DRL algorithm, Deep Q-network (DQN) is adopted to determine platoon sizes and passing priorities respectively in the two layers. The model is validated and examined on the simulator Simulation of Urban Mobility (SUMO). The simulation results demonstrate that the model is able to: (1) achieve satisfactory convergence performances; (2) adaptively determine platoon size in response to varying traffic conditions; and (3) completely avoid deadlocks at the intersection. By comparison with other control methods, the model manifests its superiority of adopting adaptive platooning and DRL-based coordination strategies. Also, the model outperforms several state-of-the-art methods on reducing travel time and fuel consumption in different traffic conditions.Comment: This paper has been submitted to Transportation Research Part C: Emerging Technologies and is currently under revie

A Novel Voice Priority Queue (VPQ) Schedule and Algorithm for VoIP over WLAN Network

The VoIP deployment on Wireless Local Area Networks (WLANs), which is based on IEEE 802.11 standards, is increasing. Currently, many schedulers have been introduced such as Weighted Fair Queueing (WFQ), Strict Priority (SP) General processor sharing (GPS), Deficit Round Robin (DRR), and Contention-Aware Temporally fair Scheduling (CATS). Unfortunately, the current scheduling techniques have some drawbacks on real-time applications and therefore will not be able to handle the VoIP packets in a proper way. The objective of this research is to propose a new scheduler system model for the VoIP application named final stage of Voice Priority Queue (VPQ) scheduler. The scheduler system model is to ensure efficiency by producing a higher throughput and fairness for VoIP packets. In this paper, only the final Stage of the VPQ packet scheduler and its algorithm are presented. Simulation topologies for VoIP traffic were implemented and analyzed using the Network Simulator (NS-2). The results show that this method can achieve a better and more accurate VoIP quality throughput and fairness index over WLANs

A comprehensive survey on cooperative intersection management for heterogeneous connected vehicles

Nowadays, with the advancement of technology, world is trending toward high mobility and dynamics. In this context, intersection management (IM) as one of the most crucial elements of the transportation sector demands high attention. Today, road entities including infrastructures, vulnerable road users (VRUs) such as motorcycles, moped, scooters, pedestrians, bicycles, and other types of vehicles such as trucks, buses, cars, emergency vehicles, and railway vehicles like trains or trams are able to communicate cooperatively using vehicle-to-everything (V2X) communications and provide traffic safety, efficiency, infotainment and ecological improvements. In this paper, we take into account different types of intersections in terms of signalized, semi-autonomous (hybrid) and autonomous intersections and conduct a comprehensive survey on various intersection management methods for heterogeneous connected vehicles (CVs). We consider heterogeneous classes of vehicles such as road and rail vehicles as well as VRUs including bicycles, scooters and motorcycles. All kinds of intersection goals, modeling, coordination architectures, scheduling policies are thoroughly discussed. Signalized and semi-autonomous intersections are assessed with respect to these parameters. We especially focus on autonomous intersection management (AIM) and categorize this section based on four major goals involving safety, efficiency, infotainment and environment. Each intersection goal provides an in-depth investigation on the corresponding literature from the aforementioned perspectives. Moreover, robustness and resiliency of IM are explored from diverse points of view encompassing sensors, information management and sharing, planning universal scheme, heterogeneous collaboration, vehicle classification, quality measurement, external factors, intersection types, localization faults, communication anomalies and channel optimization, synchronization, vehicle dynamics and model mismatch, model uncertainties, recovery, security and privacy

Best effort measurement based congestion control

Abstract available: p.