scholarly journals Affiliation-Hiding Authentication with Minimal Bandwidth Consumption

2011 ◽  
pp. 85-99
Author(s):  
Mark Manulis ◽  
Bertram Poettering
Keyword(s):  
Bandwidth Consumption

scholarly journals Efficient Placement of Service Function Chains in Cloud Computing Environments

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 323
Author(s):  
Marwa A. Abdelaal ◽  
Gamal A. Ebrahim ◽  
Wagdy R. Anis
Keyword(s):  
Energy Consumption ◽  
Load Balancing ◽  
Response Time ◽  
Optimization Problem ◽  
Service Providers ◽  
Virtual Network ◽  
Placement Problem ◽  
Service Function ◽  
Network Functions ◽  
Bandwidth Consumption

The widespread adoption of network function virtualization (NFV) leads to providing network services through a chain of virtual network functions (VNFs). This architecture is called service function chain (SFC), which can be hosted on top of commodity servers and switches located at the cloud. Meanwhile, software-defined networking (SDN) can be utilized to manage VNFs to handle traffic flows through SFC. One of the most critical issues that needs to be addressed in NFV is VNF placement that optimizes physical link bandwidth consumption. Moreover, deploying SFCs enables service providers to consider different goals, such as minimizing the overall cost and service response time. In this paper, a novel approach for the VNF placement problem for SFCs, called virtual network functions and their replica placement (VNFRP), is introduced. It tries to achieve load balancing over the core links while considering multiple resource constraints. Hence, the VNF placement problem is first formulated as an integer linear programming (ILP) optimization problem, aiming to minimize link bandwidth consumption, energy consumption, and SFC placement cost. Then, a heuristic algorithm is proposed to find a near-optimal solution for this optimization problem. Simulation studies are conducted to evaluate the performance of the proposed approach. The simulation results show that VNFRP can significantly improve load balancing by 80% when the number of replicas is increased. Additionally, VNFRP provides more than a 54% reduction in network energy consumption. Furthermore, it can efficiently reduce the SFC placement cost by more than 67%. Moreover, with the advantages of a fast response time and rapid convergence, VNFRP can be considered as a scalable solution for large networking environments.

Proactive Video Push for Optimizing Bandwidth Consumption in Hybrid CDN-P2P VoD Systems

2018 ◽  
Author(s):  
Yuanxing Zhang ◽  
Chengliang Gao ◽  
Yangze Guo ◽  
Kaigui Bian ◽  
Xin Jin ◽  
...  
Keyword(s):  
Bandwidth Consumption

scholarly journals CDC: Classification Driven Compression for Bandwidth Efficient Edge-Cloud Collaborative Deep Learning

2020 ◽  
Author(s):  
Yuanrui Dong ◽  
Peng Zhao ◽  
Hanqiao Yu ◽  
Cong Zhao ◽  
Shusen Yang
Keyword(s):  
Deep Learning ◽  
Classification Accuracy ◽  
Data Privacy ◽  
Privacy Preservation ◽  
Fine Tuning ◽  
Quantization Scheme ◽  
Raw Data ◽  
Resource Limited ◽  
Lower Accuracy ◽  
Bandwidth Consumption

The emerging edge-cloud collaborative Deep Learning (DL) paradigm aims at improving the performance of practical DL implementations in terms of cloud bandwidth consumption, response latency, and data privacy preservation. Focusing on bandwidth efficient edge-cloud collaborative training of DNN-based classifiers, we present CDC, a Classification Driven Compression framework that reduces bandwidth consumption while preserving classification accuracy of edge-cloud collaborative DL. Specifically, to reduce bandwidth consumption, for resource-limited edge servers, we develop a lightweight autoencoder with a classification guidance for compression with classification driven feature preservation, which allows edges to only upload the latent code of raw data for accurate global training on the Cloud. Additionally, we design an adjustable quantization scheme adaptively pursuing the tradeoff between bandwidth consumption and classification accuracy under different network conditions, where only fine-tuning is required for rapid compression ratio adjustment. Results of extensive experiments demonstrate that, compared with DNN training with raw data, CDC consumes 14.9× less bandwidth with an accuracy loss no more than 1.06%, and compared with DNN training with data compressed by AE without guidance, CDC introduces at least 100% lower accuracy loss.

A Cooperative Hybrid Caching Strategy for P2P Mobile Network

2013 ◽  
Vol 347-350 ◽  
pp. 1992-1996
Author(s):  
Mo Zhou ◽  
Bo Ji ◽  
Kun Peng Han ◽  
Hong Sheng Xi
Keyword(s):  
Delay Time ◽  
Mobile Network ◽  
Mobile Users ◽  
Caching Strategy ◽  
Network Bandwidth ◽  
Wireless Users ◽  
Simulation Results ◽  
Bandwidth Consumption ◽  
Increasing Demand ◽  
Network Technologies

Recently mobile network technologies develop quickly. To meet the increasing demand of wireless users, many multimedia proxies have been deployed over wireless networks. The caching nodes constitute a wireless caching system with an architecture of P2P and provide better service to mobile users. In this paper, we formulate the caching system to optimize the consumption of network bandwidth and guarantee the response time of mobile users. Two strategies: single greedy caching strategy and cooperative hybrid caching strategy are proposed to achieve this goal. Single greedy caching aims to reduce bandwidth consumption from the standpoint of each caching node, while cooperative hybrid caching allows sharing and coordination of multiple nodes, taking both bandwidth consumption and popularity into account. Simulation results show that cooperative hybrid caching outperforms single greedy caching in both bandwidth consumption and delay time.

Weighted Large Margin Nearest Center Distance-Based Human Depth Recovery With Limited Bandwidth Consumption

2018 ◽  
Vol 27 (12) ◽  
pp. 5728-5743 ◽  
Author(s):  
Meiyu Huang ◽  
Xueshuang Xiang ◽  
Yiqiang Chen ◽  
Da Fan
Keyword(s):  
Large Margin ◽  
Limited Bandwidth ◽  
Depth Recovery ◽  
Bandwidth Consumption ◽  
Center Distance

On the Impact of Content Sharing on the Bandwidth Consumption of Cloud Storage

2018 ◽  
pp. 1-1
Author(s):  
Glauber Goncalves ◽  
Idilio Drago ◽  
Alex Borges ◽  
Ana Paula Couto ◽  
Jussara Almeida
Keyword(s):  
Cloud Storage ◽  
Content Sharing ◽  
Bandwidth Consumption ◽  
The Impact

scholarly journals A New QoS Routing Scheme Based on Bandwidth Consumption for MANETs

2009 ◽  
Vol 17 ◽  
pp. 14-25
Author(s):  
Toshiaki Osada ◽  
Gen Kitagata ◽  
Debasish Chakraborty ◽  
Takuo Suganuma ◽  
Norio Shiratori
Keyword(s):  
Qos Routing ◽  
Routing Scheme ◽  
Bandwidth Consumption

scholarly journals Detecting Malicious Cloud Bandwidth Consumption using Machine Learning

2016 ◽  
Vol 8 (5) ◽  
pp. 2199-2205 ◽  
Author(s):  
Chidananda Murthy P. ◽  
Manjunatha A.S. ◽  
Anku Jaiswal ◽  
Madhu B.R.
Keyword(s):  
Machine Learning ◽  
Bandwidth Consumption
Sign in / Sign up

Export Citation Format

Share Document