scholarly journals PDLB: Path Diversity-aware Load Balancing with Adaptive Granularity in Data Center Network

2022 ◽  
Author(s):  
weimin gao ◽  
huang jiawei ◽  
Li zhaoyi ◽  
zou shaojun ◽  
wang jianxin
Keyword(s):  
Load Balancing ◽  
Data Center ◽  
Large Scale ◽  
Rooted Tree ◽  
Coarse Grained ◽  
Data Center Network ◽  
Path Diversity ◽  
Packet Reordering ◽  
Fine Grained ◽  
Multiple Paths

Abstract Modern data center topologies often take the form of a multi-rooted tree with rich parallel paths to provide high bandwidth. However, various path diversities caused by traffic dynamics, link failures and heterogeneous switching equipments widely exist in production data center network. Therefore, the multi-path load balancer in data center should be robust to these diversities. Although prior fine-grained schemes such as RPS and Presto make full use of available paths, they are prone to experi-ence packet reordering problem under asymmetric topology. The coarse-grained solutions such as ECMP and LetFlow effectively avoid packet reordering, but easily lead to under-utilization of multiple paths. To cope with these inefficiencies, we propose a load balancing mechanism called PDLB, which adaptively adjusts flowcell granularity according to path diversity. PDLB increases flowcell granularity to alleviate packet reordering under large degrees of topology asymmetry, while reducing flowcell granularity to obtain high link utilization under small degrees of topology asymmetry. PDLB is only deployed on the sender without any modification on switch. We evaluate PDLB through large-scale NS2 simulations. The experimental results show that PDLB reduces the average flow completion time by up to ∼11-53% over the state-of-the-art load balancing schemes.

scholarly journals HTPC: heterogeneous traffic-aware partition coding for random packet spraying in data center networks

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Jiawei Huang ◽  
Shiqi Wang ◽  
Shuping Li ◽  
Shaojun Zou ◽  
Jinbin Hu ◽  
...  
Keyword(s):  
Data Center ◽  
Large Scale ◽  
Network Performance ◽  
Rooted Tree ◽  
Heterogeneous Traffic ◽  
Data Center Networks ◽  
Packet Reordering ◽  
Traffic Characteristics ◽  
Network Utilization ◽  
The Impact

AbstractModern data center networks typically adopt multi-rooted tree topologies such leaf-spine and fat-tree to provide high bisection bandwidth. Load balancing is critical to achieve low latency and high throughput. Although the per-packet schemes such as Random Packet Spraying (RPS) can achieve high network utilization and near-optimal tail latency in symmetric topologies, they are prone to cause significant packet reordering and degrade the network performance. Moreover, some coding-based schemes are proposed to alleviate the problem of packet reordering and loss. Unfortunately, these schemes ignore the traffic characteristics of data center network and cannot achieve good network performance. In this paper, we propose a Heterogeneous Traffic-aware Partition Coding named HTPC to eliminate the impact of packet reordering and improve the performance of short and long flows. HTPC smoothly adjusts the number of redundant packets based on the multi-path congestion information and the traffic characteristics so that the tailing probability of short flows and the timeout probability of long flows can be reduced. Through a series of large-scale NS2 simulations, we demonstrate that HTPC reduces average flow completion time by up to 60% compared with the state-of-the-art mechanisms.

scholarly journals Fine-grained load balancing with traffic-aware rerouting in datacenter networks

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Tao Zhang ◽  
Yasi Lei ◽  
Qianqiang Zhang ◽  
Shaojun Zou ◽  
Juan Huang ◽  
...  
Keyword(s):  
Load Balancing ◽  
Large Scale ◽  
Queuing Delay ◽  
Packet Reordering ◽  
Fine Grained ◽  
Network Bandwidth ◽  
Performance Requirements ◽  
Delay Sensitive ◽  
Link Utilization ◽  
Datacenter Networks

AbstractModern datacenters provide a wide variety of application services, which generate a mix of delay-sensitive short flows and throughput-oriented long flows, transmitting in the multi-path datacenter network. Though the existing load balancing designs successfully make full use of available parallel paths and attain high bisection network bandwidth, they reroute flows regardless of their dissimilar performance requirements. The short flows suffer from the problems of large queuing delay and packet reordering, while the long flows fail to obtain high throughput due to low link utilization and packet reordering. To address these inefficiency, we design a fine-grained load balancing scheme, namely TR (Traffic-aware Rerouting), which identifies flow types and executes flexible and traffic-aware rerouting to balance the performances of both short and long flows. Besides, to avoid packet reordering, TR leverages the reverse ACKs to estimate the switch-to-switch delay, thus excluding paths that potentially cause packet reordering. Moreover, TR is only deployed on the switch without any modification on end-hosts. The experimental results of large-scale NS2 simulations show that TR reduces the average and tail flow completion time for short flows by up to 60% and 80%, as well as provides up to 3.02x gain in throughput of long flows compared to the state-of-the-art load balancing schemes.

scholarly journals Fine-grained Load Balancing with Traffic-aware Rerouting in DataCenter Networks

2021 ◽  
Author(s):  
Tao Zhang ◽  
Yasi Lei ◽  
Qianqiang Zhang ◽  
Shaojun Zou ◽  
Juan Huang ◽  
...  
Keyword(s):  
Load Balancing ◽  
Large Scale ◽  
Queuing Delay ◽  
Packet Reordering ◽  
Fine Grained ◽  
Network Bandwidth ◽  
Performance Requirements ◽  
Delay Sensitive ◽  
Link Utilization ◽  
Datacenter Networks

Abstract Modern datacenters provide a wide variety of application services, which generate a mix of delay-sensitive short flows and throughput-oriented long flows, transmitting in the multi-path datacenter network. Though the existing load balancing designs successfully make full use of available parallel paths and attain high bisection network bandwidth, they reroute flows regardless of their dissimilar performance requirements. The short flows suffer from the problems of large queuing delay and packet reordering, while the long flows fail to obtain high throughput due to low link utilization and packet reordering. To address these inefficiency, we design a fine-grained load balancing scheme, namely TR (Traffic-aware Rerouting), which identifies flow types and executes flexible and traffic-aware rerouting to balance the performances of both short and long flows. Besides, to avoid packet reordering, TR leverages the reverse ACKs to estimate the switch-to-switch delay, thus excluding paths that potentially cause packet reordering. Moreover, TR is only deployed on the switch without any modification on end-hosts. The experimental results of large-scale NS2 simulations show that TR reduces the average and tail flow completion time for short flows by up to 60% and 80%, as well as provides up to 3.02x gain in throughput of long flows compared to the state-of-the-art load balancing schemes.

scholarly journals Path based load balancing for data center networks using SDN

2019 ◽  
Vol 9 (4) ◽  
pp. 3279
Author(s):  
V. Deeban Chakravarthy ◽  
B. Amutha
Keyword(s):  
Load Balancing ◽  
Data Center ◽  
Software Defined Networking ◽  
The Internet ◽  
Operational Cost ◽  
Link Failures ◽  
Data Center Networking ◽  
Data Centre ◽  
Multiple Paths ◽  
Load Balancer

Due to the increase in the number of users on the internet and the number of applications that is available in the cloud makes Data Center Networking (DCN) has the backbone for computing. These data centre requires high operational cost and also experience the link failures and congestions often. Hence the solution is to use Software Defined Networking (SDN) based load balancer which improves the efficiency of the network by distributing the traffic across multiple paths to optimize the efficiency of the network. Traditional load balancers are very expensive and inflexible. These SDN load balancers do not require costly hardware and can be programmed, which it makes it easier to implement user-defined algorithms and load balancing strategies. In this paper, we have proposed an efficient load balancing technique by considering different parameters to maintain the load efficiently using Open FlowSwitches connected to ONOS controller.

Energy-Efficiency in Cloud Data Centers

2013 ◽  
pp. 241-263
Author(s):  
Burak Kantarci ◽  
Hussein T. Mouftah
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Data Center ◽  
Energy Efficient ◽  
Large Scale ◽  
Data Centers ◽  
High Energy ◽  
It Services ◽  
Data Center Network ◽  
Cloud Data

Cloud computing aims to migrate IT services to distant data centers in order to reduce the dependency of the services on the limited local resources. Cloud computing provides access to distant computing resources via Web services while the end user is not aware of how the IT infrastructure is managed. Besides the novelties and advantages of cloud computing, deployment of a large number of servers and data centers introduces the challenge of high energy consumption. Additionally, transportation of IT services over the Internet backbone accumulates the energy consumption problem of the backbone infrastructure. In this chapter, the authors cover energy-efficient cloud computing studies in the data center involving various aspects such as: reduction of processing, storage, and data center network-related power consumption. They first provide a brief overview of the existing approaches on cool data centers that can be mainly grouped as studies on virtualization techniques, energy-efficient data center network design schemes, and studies that monitor the data center thermal activity by Wireless Sensor Networks (WSNs). The authors also present solutions that aim to reduce energy consumption in data centers by considering the communications aspects over the backbone of large-scale cloud systems.

Microstructural Evolution of Synthetic Forsterite Aggregates Deformed to High Strain

2004 ◽  
Vol 467-470 ◽  
pp. 579-584 ◽  
Author(s):  
A. Kellermann Slotemaker ◽  
J.H.P. de Bresser ◽  
C.J. Spiers ◽  
M.R. Drury
Keyword(s):  
Grain Size ◽  
Dynamic Recrystallization ◽  
Grain Growth ◽  
Microstructural Evolution ◽  
Large Scale ◽  
High Strain ◽  
Confining Pressure ◽  
Size Reduction ◽  
Coarse Grained ◽  
Fine Grained

Microstructures provide the crucial link between solid state flow of rock materials in the laboratory and large-scale tectonic processes in nature. In this context, microstructural evolution of olivine aggregates is of particular importance, since this material controls the flow of the Earth’s upper mantle and affects the dynamics of the outer Earth. From previous work it has become apparent that if olivine rocks are plastically deformed to high strain, substantial weakening may occur before steady state mechanical behaviour is approached. This weakening appears directly related to progressive modification of the grain size distribution through competing effects of dynamic recrystallization and syn-deformational grain growth. However, most of our understanding of these processes in olivine comes from tests on coarse-grained materials that show grain size reduction through dynamic recrystallization. In the present study we focused on fine-grained (~1 µm) olivine aggregates (i.e., forsterite/Mg2SiO4), containing ~0.5 wt% water and 10 vol% enstatite (MgSiO3), Samples were axially compressed to varying strains up to a maximum of ~45%, at 600 MPa confining pressure and a temperature of 950°C. Microstructures were characterized by analyzing full grain size distributions and textures using SEM/EBSD. We observed syndeformational grain growth rather than grain size reduction, and relate this to strain hardening seen in the stress-strain curves.

scholarly journals Who Likes What? — SplitLBI in Exploring Preferential Diversity of Ratings

2020 ◽  
Vol 34 (01) ◽  
pp. 262-269
Author(s):  
Qianqian Xu ◽  
Jiechao Xiong ◽  
Zhiyong Yang ◽  
Xiaochun Cao ◽  
Qingming Huang ◽  
...  
Keyword(s):  
Large Scale ◽  
Social Preference ◽  
Learning To Rank ◽  
User Preferences ◽  
Coarse Grained ◽  
Fast Analysis ◽  
Fine Grained ◽  
Level Model ◽  
The Common ◽  
Multi Level

In recent years, learning user preferences has received significant attention. A shortcoming of existing learning to rank work lies in that they do not take into account the multi-level hierarchies from social choice to individuals. In this paper, we propose a multi-level model which learns both the common preference or utility function over the population based on features of alternatives to-be-compared, and preferential diversity functions conditioning on user categories. Such a multi-level model, enables us to simultaneously learn a coarse-grained social preference function together with a fine-grained personalized diversity. It provides us prediction power for the choices of new users on new alternatives. The key algorithm in this paper is based on Split Linearized Bregman Iteration (SplitLBI) algorithm which generates a dynamic path from the common utility to personalized preferential diversity, at different levels of sparsity on personalization. A synchronized parallel version of SplitLBI is proposed to meet the needs of fast analysis of large-scale data. The validity of the methodology are supported by experiments with both simulated and real-world datasets such as movie and dining restaurant ratings which provides us a coarse-to-fine grained preference learning.

scholarly journals Paleoenvironment and taphonomy of the dinosaur-bearing Ischigualasto Formation (Upper Triassic, Argentina)

1992 ◽  
Vol 6 ◽  
pp. 249-249 ◽  
Author(s):  
Raymond R. Rogers ◽  
Catherine A. Forster ◽  
Cathleen L. May ◽  
Alfredo Monetta ◽  
Paul C. Sereno
Keyword(s):  
Large Scale ◽  
Lower Half ◽  
Coarse Grained ◽  
Fine Grained ◽  
Karoo Basin ◽  
Sand Body ◽  
Faunal Succession ◽  
New Material ◽  
Group A ◽  
Depositional Setting

The oldest-known dinosaurs (Herrerasaurus, Pisanosaurus) occur within the Ischigualasto Formation. Recent work in the formation has brought to light significant new material, including the complete skeleton of a new primitive dinosaur. We sketch below the paleoenvironment and faunal succession during the range of these early dinosaurs, and review some of the taphonomic factors that shaped their fossil record.The Ischigualasto Formation (Carnian?) is included within the Agua de la Peña Group, a series of continental Triassic deposits exposed in the Ischigualasto-Ville Union Basin of northwest Argentina. Ischigualasto sediments rest unconformably upon the carbonaceous fluvial/lacustrine Los Rastros Formation; this contact is characterized locally by marked angular discordance. The upper contact is gradational into red-beds of the Los Colorados Formation. Medium- to coarse-grained conglomeratic sandstones, siltstones, and silty mudstones dominate the section. Sand bodies are characterized by medium- to large-scale trough cross-stratification and broad lenticular/narrow sheet geometries, and are interpreted as deposits of shallow, low-sinuosity streams. Siltstones and mudstones show pervasive evidence of soil development, including root traces, nodular caliche horizons, and pedogenic slickensides. Deposits attributable to lacustrine/paludal sedimentation are scarce, and freshwater vertebrates and invertebrates are extremely rare. These data suggest an upland depositional setting on a low-relief alluvial plain with seasonal climate.The Ischigualasto vertebrate fauna includes archosaurs, rhynchosaurs, traversodontid and carnivorous cynodonts, and temnospondyl amphibians. Rhynchosaurs dominate (relative specimen abundance) in the lower half of the section, but are absent from the upper half. Traversodontid cynodonts occur throughout the formation, but are much more abundant up-section. Archosaurs, carnivorous cynodonts, and particularly temnospondyls are rare throughout, with dinosaurs limited to the lower half. No major stratigraphic or sedimentologic changes occur up-section, and there is no evidence for significant shifts in physical or chemical taphonomic processes. Thus, trends in relative taxon abundance likely record a true biotic signal (e.g., local extinction, immigration) rather than a taphonomically-driven preservational bias.Fossils are preserved as isolated carcasses or disarticulated elements, most often in fine-grained overbank facies. Bone beds and microsites are conspicuously absent. Temnospondyl remains were found within a local carbonaceous lens developed upon a sand body, suggesting autochthonous burial in an abandoned-channel setting. Isolated skulls, particularly those of the traversodontid Exaeretodon, are extremely common. Fifteen isolated crania of this cynodont were mapped in a single stratum with limited areal exposure. Abundant preservation of isolated therapsid crania has also been reported in the Beaufort Series (Permo-Triassic) of the Karoo Basin, South Africa (Smith, 1980). Post-disarticulation hydrodynamic sorting (enhanced by scavenging?) of an areally dispersed mass-mortality assemblage may explain this unusual occurrence.

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