Investigation of pushback based detection and prevention of network bandwidth attacks

2005 ◽  
Author(s):  
Ningning Wu ◽  
Jing Zhang
Keyword(s):  
Network Bandwidth

Enhancing the use of Object Based Contents Addressable Storage

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Simab Hasan Rizvi
Keyword(s):  
File System ◽  
Application Performance ◽  
Shared Storage ◽  
Data Intensive ◽  
Network Bandwidth ◽  
Storage Performance ◽  
Efficient Management ◽  
Object Based ◽  
Data Volume ◽  
Potential Benefits

In Today's age of Tetra Scale computing, the application has become more data intensive than ever. The increased data volume from applications, in now tackling larger and larger problems, and has fuelled the need for efficient management of this data. In this paper, a technique called Content Addressable Storage or CAS, for managing large volume of data is evaluated. This evaluation focuses on the benefits and demerits of using CAS it focuses, i) improved application performance via lockless and lightweight synchronization ofaccess to shared storage data, ii) improved cache performance, iii) increase in storage capacity and, iv) increase network bandwidth. The presented design of a CAS-Based file store significantly improves the storage performance that provides lightweight lock less user defined consistency semantics. As a result, this file system shows a 28% increase in read bandwidth and 13% increase in write bandwidth, over a popular file system in common use. In this paper the potential benefits of using CAS for a virtual machine are estimated. The study also explains mobility application for active use and public deployment.

scholarly journals Evaluating the Performance of Three Popular Web Mapping Libraries: A Case Study Using Argentina’s Life Quality Index

2020 ◽  
Vol 9 (10) ◽  
pp. 563
Author(s):  
Alejandro Zunino ◽  
Guillermo Velázquez ◽  
Juan Pablo Celemín ◽  
Cristian Mateos ◽  
Matías Hirsch ◽  
...  
Keyword(s):  
Life Quality ◽  
Web Technologies ◽  
Web Mapping ◽  
Network Bandwidth ◽  
Web Map ◽  
Raster Maps ◽  
Dynamic Web ◽  
Network Usage ◽  
Overall Performance

Recent Web technologies such as HTML5, JavaScript, and WebGL have enabled powerful and highly dynamic Web mapping applications executing on standard Web browsers. Despite the complexity for developing such applications has been greatly reduced by Web mapping libraries, developers face many choices to achieve optimal performance and network usage. This scenario is even more complex when considering different representations of geographical data (raster, raw data or vector) and variety of devices (tablets, smartphones, and personal computers). This paper compares the performance and network usage of three popular JavaScript Web mapping libraries for implementing a Web map using different representations for geodata, and executing on different devices. In the experiments, Mapbox GL JS achieved the best overall performance on mid and high end devices for displaying raster or vector maps, while OpenLayers was the best for raster maps on all devices. Vector-based maps are a safe bet for new Web maps, since performance is on par with raster maps on mid-end smartphones, with significant less network bandwidth requirements.

scholarly journals Software-Defined Optimal Computation Task Scheduling in Vehicular Edge Networking

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 955
Author(s):  
Zhiyuan Li ◽  
Ershuai Peng
Keyword(s):  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Dynamic Network ◽  
Parameter Tuning ◽  
Global Optimum ◽  
Research Field ◽  
Edge Computing ◽  
Transmission Delay ◽  
Smart Vehicles ◽  
Network Bandwidth

With the development of smart vehicles and various vehicular applications, Vehicular Edge Computing (VEC) paradigm has attracted from academic and industry. Compared with the cloud computing platform, VEC has several new features, such as the higher network bandwidth and the lower transmission delay. Recently, vehicular computation-intensive task offloading has become a new research field for the vehicular edge computing networks. However, dynamic network topology and the bursty computation tasks offloading, which causes to the computation load unbalancing for the VEC networking. To solve this issue, this paper proposed an optimal control-based computing task scheduling algorithm. Then, we introduce software defined networking/OpenFlow framework to build a software-defined vehicular edge networking structure. The proposed algorithm can obtain global optimum results and achieve the load-balancing by the virtue of the global load status information. Besides, the proposed algorithm has strong adaptiveness in dynamic network environments by automatic parameter tuning. Experimental results show that the proposed algorithm can effectively improve the utilization of computation resources and meet the requirements of computation and transmission delay for various vehicular tasks.

scholarly journals Bandwidth-Aware Rescheduling Mechanism in SDN-Based Data Center Networks

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1774
Author(s):  
Ming-Chin Chuang ◽  
Chia-Cheng Yen ◽  
Chia-Jui Hung
Keyword(s):  
Data Center ◽  
Completion Time ◽  
Network Performance ◽  
Data Locality ◽  
Task Completion ◽  
Data Center Networks ◽  
Task Completion Time ◽  
Data Packets ◽  
Network Bandwidth ◽  
Data Process

Recently, with the increase in network bandwidth, various cloud computing applications have become popular. A large number of network data packets will be generated in such a network. However, most existing network architectures cannot effectively handle big data, thereby necessitating an efficient mechanism to reduce task completion time when large amounts of data are processed in data center networks. Unfortunately, achieving the minimum task completion time in the Hadoop system is an NP-complete problem. Although many studies have proposed schemes for improving network performance, they have shortcomings that degrade their performance. For this reason, in this study, we propose a centralized solution, called the bandwidth-aware rescheduling (BARE) mechanism for software-defined network (SDN)-based data center networks. BARE improves network performance by employing a prefetching mechanism and a centralized network monitor to collect global information, sorting out the locality data process, splitting tasks, and executing a rescheduling mechanism with a scheduler to reduce task completion time. Finally, we used simulations to demonstrate our scheme’s effectiveness. Simulation results show that our scheme outperforms other existing schemes in terms of task completion time and the ratio of data locality.

scholarly journals Cooperation and information replication in wireless networks

2016 ◽  
Vol 374 (2062) ◽  
pp. 20150123 ◽  
Author(s):  
Konstantinos Poularakis ◽  
Leandros Tassiulas
Keyword(s):  
Network Performance ◽  
Access Network ◽  
Network Architectures ◽  
Backbone Networks ◽  
Network Bandwidth ◽  
Multicast Service ◽  
Radio Access ◽  
Maximum Benefit ◽  
Wireless Medium ◽  
Cell Tower

A significant portion of today's network traffic is due to recurring downloads of a few popular contents. It has been observed that replicating the latter in caches installed at network edges—close to users—can drastically reduce network bandwidth usage and improve content access delay. Such caching architectures are gaining increasing interest in recent years as a way of dealing with the explosive traffic growth, fuelled further by the downward slope in storage space price. In this work, we provide an overview of caching with a particular emphasis on emerging network architectures that enable caching at the radio access network. In this context, novel challenges arise due to the broadcast nature of the wireless medium, which allows simultaneously serving multiple users tuned into a multicast stream, and the mobility of the users who may be frequently handed off from one cell tower to another. Existing results indicate that caching at the wireless edge has a great potential in removing bottlenecks on the wired backbone networks. Taking into consideration the schedule of multicast service and mobility profiles is crucial to extract maximum benefit in network performance.

Binomial Bit-Rate Computation Model Based on Wireless Channel

2012 ◽  
Vol 241-244 ◽  
pp. 2482-2486
Author(s):  
Wei Ming Yang ◽  
Jian Zhang ◽  
Jin Xiang Peng
Keyword(s):  
Solution Method ◽  
Rate Distortion ◽  
Wireless Channel ◽  
Video Communication ◽  
Bit Allocation ◽  
Bit Rate ◽  
Computation Model ◽  
Refresh Rate ◽  
Network Bandwidth ◽  
Inter Frame

For the encoding bit-rate problem in H.264 wireless video communication, the bit-rate computation model and the standard deviation distortion model were analyzed to establish the relation between the quantization parameter of encoding bit-rate and the intra-frame refresh rate of macroblocks, a new proposal of the coding rate thus put forward based on the general binomial computation model theory. Furthermore, this method not only can adaptively adjust the bit allocation and quantization parameters to prevent buffer from overflowing downward or upward under given network bandwidth, but also can apply the rate-distortion to perfect the solution method, control the encoding bits accurately and optimize the allocation between the inter-frame encoding macroblocks.

Constraint-Based Reverse Engineering From Ultrasound Cross-Sections

1997 ◽  
Author(s):  
Jai Menon ◽  
Ranjit Desai ◽  
Jay Buckey
Keyword(s):  
Reverse Engineering ◽  
Cross Sections ◽  
Biomedical Applications ◽  
Engineering Application ◽  
Volume Data ◽  
Cross Sectional ◽  
Reverse Engineer ◽  
Network Bandwidth ◽  
Complex Topology

Abstract This paper extends the “cross-sectional” approach for reverse engineering, used abundantly in biomedical applications, to the mechanical domain. We propose a combination of “projective” and cross-sectional algorithms for handling physical artifacts with complex topology and geometry. In addition, the paper introduces the concept of constraint-based reverse engineering, where the constraint parameters could include one or more of the following: time, storage (memory, disk-space), network bandwidth, Quality of Service (output-resolution), and so forth. We describe a specific reverse-engineering application which uses ultrasound (tilt-echo) imaging to reverse engineer spatial enumeration (volume) representations from cross-sectional data. The constraint here is time, and we summarize how our implementation can satisfy real-time reconstruction for distribution of the volume data on the internet. We present results that show volume representations computed from static objects. Since the algorithms are tuned to satisfy time constraints, this method is extendable to reverse engineer temporally-varying (elastic) objects. The current reverse engineering processing time is constrained by the data-acquisition (tilt-echo imaging) process, and the entire reverse engineering pipeline has been optimized to compute incremental volume representations in the order of 3 seconds on a network of four processors.

Analysis of Learning Techniques for Performance Prediction in Mobile Adhoc Networks

2020 ◽  
Vol 6 (2) ◽  
pp. IS-46-IS-53
Author(s):  
Yusuf Durachman ◽  
Keyword(s):  
Wireless Network ◽  
Ad Hoc ◽  
Prediction Models ◽  
Service Providers ◽  
Strategic Decision ◽  
Gradient Boosting ◽  
Mobile Adhoc Networks ◽  
Network Bandwidth ◽  
Adhoc Networks ◽  
Mobile Ad Hoc

Current advancements in cellular technologies and computing have provided the basis for the unparalleled exponential development of mobile networking and software availability and quality combined with multiple systems or network software. Using wireless technologies and mobile ad-hoc networks, such systems and technology interact and collect information. To achieve the Quality of Service (QoS) criteria, the growing concern in wireless network performance and the availability of mobile users would support a significant rise in wireless applications. Predicting the mobility of wireless users and systems performs an important role in the effective strategic decision making of wireless network bandwidth service providers. Furthermore, related to the defect-proneness, self-organization, and mobility aspect of such networks, new architecture problems occur. This paper proposes to predict and simulate the mobility of specific nodes on a mobile ad-hoc network, gradient boosting devices defined for the system will help. The proposed model not just to outperform previous mobility prediction models using simulated and real-world mobility instances, but provides better predictive accuracy by an enormous margin. The accuracy obtained helps the suggested mobility indicator in Mobile Adhoc Networks to increase the average level of performance.

scholarly journals Energy aware dynamic virtual machine consolidation in cloud data centers

2018 ◽  
Vol 7 (2.8) ◽  
pp. 550 ◽  
Author(s):  
G Anusha ◽  
P Supraja
Keyword(s):  
Energy Consumption ◽  
Virtual Machine ◽  
Data Centers ◽  
Energy Aware ◽  
Large Power ◽  
Complex Tasks ◽  
Cloud Data ◽  
Network Bandwidth ◽  
Virtual Machine Consolidation ◽  
Cloud Data Centers

Cloud computing is a growing technology now-a-days, which provides various resources to perform complex tasks. These complex tasks can be performed with the help of datacenters. Data centers helps the incoming tasks by providing various resources like CPU, storage, network, bandwidth and memory, which has resulted in the increase of the total number of datacenters in the world. These data centers consume large volume of energy for performing the operations and which leads to high operation costs. Resources are the key cause for the power consumption in data centers along with the air and cooling systems. Energy consumption in data centers is comparative to the resource usage. Excessive amount of energy consumption by datacenters falls out in large power bills. There is a necessity to increase the energy efficiency of such data centers. We have proposed an Energy aware dynamic virtual machine consolidation (EADVMC) model which focuses on pm selection, vm selection, vm placement phases, which results in the reduced energy consumption and the Quality of service (QoS) to a considerable level.

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