2019 IEEE 27th International Conference on Network Protocols (ICNP)最新文献_第4页

A Heterogeneous Parallel Packet Processing Architecture for NFV Acceleration 一种用于NFV加速的异构并行分组处理体系结构

2019 IEEE 27th International Conference on Network Protocols (ICNP) Pub Date : 2019-10-01 DOI: 10.1109/ICNP.2019.8888106

Jinshu Su, Biao Han, Gaofeng Lv, Tao Li, Zhigang Sun

引用次数: 1

Placement and Allocation of Virtual Network Functions: Multi-dimensional Case 虚拟网络功能的放置与分配:多维案例

2019 IEEE 27th International Conference on Network Protocols (ICNP) Pub Date : 2019-10-01 DOI: 10.1109/ICNP.2019.8888148

G. Sallam, Zizhan Zheng, Bo Ji

{"title":"Placement and Allocation of Virtual Network Functions: Multi-dimensional Case","authors":"G. Sallam, Zizhan Zheng, Bo Ji","doi":"10.1109/ICNP.2019.8888148","DOIUrl":"https://doi.org/10.1109/ICNP.2019.8888148","url":null,"abstract":"Network function virtualization (NFV) is an emerging design paradigm that replaces physical middlebox devices with software modules running on general purpose commodity servers. While gradually transitioning to NFV, Internet service providers face the problem of where to introduce NFV in order to make the most benefit of that; here, we measure the benefit by the amount of traffic that can be serviced through the NFV. This problem is non-trivial as it is composed of two challenging subproblems: 1) placement of nodes to support virtual network functions (referred to as VNF-nodes); and 2) allocation of the VNF-nodes resources to network flows; the two subproblems need to be considered jointly to satisfy the objective of serving the maximum amount of traffic. This problem has been studied recently but for the one-dimensional setting, where all network flows require one network function, which requires a unit of resource to process a unit of flow. In this work, we extend to the multi-dimensional setting, where flows can require multiple network functions, which can also require a different amount of each resource to process a unit of flow. The multi-dimensional setting introduces new challenges in addition to those of the onedimensional setting (e.g., NP-hardness and non-submodularity) and also makes the resource allocation a multi-dimensional generalization of the generalized assignment problem with assignment restrictions. To address these difficulties, we propose a novel two-level relaxation method and utilize the primal-dual technique to design two approximation algorithms that achieve an approximation ratio of$displaystyle frac {(Z-1)(mathrm {e}-1)}{2mathrm {e}^{2}Z(kR)^{1/(Z-1)}}$ (and $displaystyle frac {(mathrm {e}-1)(Z-1)}{2mathrm {e}(Z-1+mathrm {e}ZR^{1/(Z-1)})}$, where k (resp. R) is the number of VNF-nodes (resp. resources), and Z is a measure of the available resource compared to flow demand. Finally, we perform extensive trace-driven simulations to show the effectiveness of the proposed algorithms.","PeriodicalId":385397,"journal":{"name":"2019 IEEE 27th International Conference on Network Protocols (ICNP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129643680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

COMPaaS DLV: Composable Infrastructure for Deep Learning in an Academic Research Environment COMPaaS DLV:学术研究环境中深度学习的可组合基础设施

2019 IEEE 27th International Conference on Network Protocols (ICNP) Pub Date : 2019-10-01 DOI: 10.1109/ICNP.2019.8888070

Maxine D. Brown, L. Renambot, Lance Long, Timothy Bargo, Andrew E. Johnson

{"title":"COMPaaS DLV: Composable Infrastructure for Deep Learning in an Academic Research Environment","authors":"Maxine D. Brown, L. Renambot, Lance Long, Timothy Bargo, Andrew E. Johnson","doi":"10.1109/ICNP.2019.8888070","DOIUrl":"https://doi.org/10.1109/ICNP.2019.8888070","url":null,"abstract":"In today’s Big Data era, data scientists require new computational instruments in order to quickly analyze large-scale datasets using complex codes and quicken the rate of scientific progress. While Federally-funded computer resources, from supercomputers to clouds, are beneficial, they are often limiting - particularly for deep learning and visualization - as they have few Graphics Processing Units (GPUs). GPUs are at the center of modern high-performance computing and artificial intelligence, efficiently performing mathematical operations that can be massively parallelized, speeding up codes used for deep learning, visualization and image processing, more so than general-purpose microprocessors, or Central Processing Units (CPUs). The University of Illinois at Chicago is acquiring a much-in-demand GPU-based instrument, COMPaaS DLV - COMposable Platform as a Service Instrument for Deep Learning & Visualization, based on composable infrastructure, an advanced architecture that disaggregates the underlying compute, storage, and network resources for scaling needs, but operates as a single cohesive infrastructure for management and workload purposes. We are experimenting with a small system and learning a great deal about composability, and we believe COMPaaS DLV users will benefit from the varied workflow that composable infrastructure allows.","PeriodicalId":385397,"journal":{"name":"2019 IEEE 27th International Conference on Network Protocols (ICNP)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130860994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

A Linguistics-based Stacking Approach to Disposable Domains Detection 一种基于语言的可丢弃域的叠加检测方法

2019 IEEE 27th International Conference on Network Protocols (ICNP) Pub Date : 2019-10-01 DOI: 10.1109/ICNP.2019.8888097

Yuwei Zeng, Yongzheng Zhang, Tianning Zang, Xunxun Chen, Yipeng Wang

引用次数: 2

ReDiCom: Resilient Communication for First Responders in Disaster Management ReDiCom:灾害管理中第一响应者的弹性通信

2019 IEEE 27th International Conference on Network Protocols (ICNP) Pub Date : 2019-10-01 DOI: 10.1109/ICNP.2019.8888115

Jiachen Chen, Yuxuan Xing, K. Ramakrishnan, Mohammad Jahanian, H. Seferoglu, M. Yuksel

{"title":"ReDiCom: Resilient Communication for First Responders in Disaster Management","authors":"Jiachen Chen, Yuxuan Xing, K. Ramakrishnan, Mohammad Jahanian, H. Seferoglu, M. Yuksel","doi":"10.1109/ICNP.2019.8888115","DOIUrl":"https://doi.org/10.1109/ICNP.2019.8888115","url":null,"abstract":"Effective communication among first responders during and in the aftermath of a disaster can affect outcomes dramatically. We seek to build a resilient architecture that allows first responders to communicate even with: 1) damage to infrastructure — civilian and / or specialized communication facilities may be damaged by the disaster, and 2) dynamically formed groups — first responder teams may be formed dynamically in response to a disaster and team member addresses (e.g., phone numbers, network addresses) may not be known to one another. We propose a resilient network architecture that allows efficient communication among first responders during and after a disaster [1]. We seek to support dynamically formed groups for incident response, allowing first responders to securely and conveniently communicate based on roles (names). The architecture supports communication in disasters by 1) building resilience into the framework across all the layers, 2) creating a framework that allows communication by role and identity, rather than addresses, 3) supporting multiple modalities (data, voice) for communication among dynamically formed first responder teams, and 4) providing robust and resilient communication and computing even when facilities are error- and disruption-prone.","PeriodicalId":385397,"journal":{"name":"2019 IEEE 27th International Conference on Network Protocols (ICNP)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131919120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Busoni: Policy Composition and Northbound Interface for IPv6 Segment Routing Networks IPv6网段路由网络的策略组成和北向接口

2019 IEEE 27th International Conference on Network Protocols (ICNP) Pub Date : 2019-10-01 DOI: 10.1109/ICNP.2019.8888104

Osamah L. Barakat, Pier Luigi Ventre, S. Salsano, Xiaoming Fu

引用次数: 1

[Copyright notice] (版权)

2019 IEEE 27th International Conference on Network Protocols (ICNP) Pub Date : 2019-10-01 DOI: 10.1109/icnp.2019.8888072

引用次数: 0

Load Migration Protocol for SDN Controllers SDN控制器负载迁移协议

2019 IEEE 27th International Conference on Network Protocols (ICNP) Pub Date : 2019-10-01 DOI: 10.1109/ICNP.2019.8888102

M. A. Beiruti, Y. Ganjali

引用次数: 0

Congestion Control for Cross-Datacenter Networks 跨数据中心网络的拥塞控制

2019 IEEE 27th International Conference on Network Protocols (ICNP) Pub Date : 2019-10-01 DOI: 10.1109/ICNP.2019.8888042

Gaoxiong Zeng, Wei Bai, Ge Chen, Kai Chen, Dongsu Han, Yibo Zhu, Lei Cui

{"title":"Congestion Control for Cross-Datacenter Networks","authors":"Gaoxiong Zeng, Wei Bai, Ge Chen, Kai Chen, Dongsu Han, Yibo Zhu, Lei Cui","doi":"10.1109/ICNP.2019.8888042","DOIUrl":"https://doi.org/10.1109/ICNP.2019.8888042","url":null,"abstract":"Geographically distributed applications hosted on cloud are becoming prevalent. They run on cross-datacenter network that consists of multiple data center networks (DCNs) connected by a wide area network (WAN). Such a cross-DC network imposes significant challenges in transport design because the DCN and WAN segments have vastly distinct characteristics (e.g., butter depths, RTTs). In this paper, we find that existing DCN or WAN transports reacting to ECN or delay alone do not (and cannot be extended to) work well for such an environment. The key reason is that neither of the signals, by itself, can simultaneously capture the location and degree of congestion. This is due to the discrepancies between DCN and WAN. Motivated by this, we present the design and implementation of GEMINI that strategically integrates both ECN and delay signals for cross-DC congestion control. To achieve low latency, GEMINI bounds the inter-DC latency with delay signal and prevents the intra-DC packet loss with ECN. To maintain high throughput, GEMINI modulates the window dynamics and maintains low butter occupancy utilizing both congestion signals. GEMINI is implemented in Linux kernel and evaluated by extensive testbed experiments. Results show that GEMINI achieves up to 53%, 31% and 76% reduction of small flow average completion times compared to TCP Cubic, DCTCP and BBR; and up to 58% reduction of large flow average completion times compared to TCP Vegas.","PeriodicalId":385397,"journal":{"name":"2019 IEEE 27th International Conference on Network Protocols (ICNP)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122197712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 32

On Studying CPU Performance of CloudLab Hardware CloudLab硬件CPU性能研究

2019 IEEE 27th International Conference on Network Protocols (ICNP) Pub Date : 2019-10-01 DOI: 10.1109/ICNP.2019.8888128

Dmitry Duplyakin, Alexandru Uta, Aleksander Maricq, R. Ricci

引用次数: 2