scholarly journals An SDN-Based Solution for Horizontal Auto-Scaling and Load Balancing of Transparent VNF Clusters

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8283
Author(s):  
Alejandro Llorens-Carrodeguas ◽  
Irian Leyva-Pupo ◽  
Cristina Cervelló-Pastor ◽  
Luis Piñeiro ◽  
Shuaib Siddiqui
Keyword(s):  
Load Balancing ◽  
Real Time ◽  
Dynamic Scaling ◽  
Quick Response ◽  
Great Flexibility ◽  
Monitoring Strategies ◽  
Network Functions ◽  
Auto Scaling ◽  
Bidirectional Flow ◽  
Scaling Out

This paper studies the problem of the dynamic scaling and load balancing of transparent virtualized network functions (VNFs). It analyzes different particularities of this problem, such as loop avoidance when performing scaling-out actions, and bidirectional flow affinity. To address this problem, a software-defined networking (SDN)-based solution is implemented consisting of two SDN controllers and two OpenFlow switches (OFSs). In this approach, the SDN controllers run the solution logic (i.e., monitoring, scaling, and load-balancing modules). According to the SDN controllers instructions, the OFSs are responsible for redirecting traffic to and from the VNF clusters (i.e., load-balancing strategy). Several experiments were conducted to validate the feasibility of this proposed solution on a real testbed. Through connectivity tests, not only could end-to-end (E2E) traffic be successfully achieved through the VNF cluster, but the bidirectional flow affinity strategy was also found to perform well because it could simultaneously create flow rules in both switches. Moreover, the selected CPU-based load-balancing method guaranteed an average imbalance below 10% while ensuring that new incoming traffic was redirected to the least loaded instance without requiring packet modification. Additionally, the designed monitoring function was able to detect failures in the set of active members in near real-time and active new instances in less than a minute. Likewise, the proposed auto-scaling module had a quick response to traffic changes. Our solution showed that the use of SDN controllers along with OFS provides great flexibility to implement different load-balancing, scaling, and monitoring strategies.

scholarly journals An Auto-Scaling Framework for Analyzing Big Data in the Cloud Environment

2019 ◽  
Vol 9 (7) ◽  
pp. 1417 ◽  
Author(s):  
Rachana Jannapureddy ◽  
Quoc-Tuan Vien ◽  
Purav Shah ◽  
Ramona Trestian
Keyword(s):  
Big Data ◽  
Real Time ◽  
Resource Use ◽  
Scale Up ◽  
Cost Effective ◽  
Dynamic Scaling ◽  
Cloud Environment ◽  
Time Data ◽  
Auto Scaling ◽  
Computing Infrastructure

Processing big data on traditional computing infrastructure is a challenge as the volume of data is large and thus high computational complexity. Recently, Apache Hadoop has emerged as a distributed computing infrastructure to deal with big data. Adopting Hadoop to dynamically adjust its computing resources based on real-time workload is itself a demanding task, thus conventionally a pre-configuration with adequate resources to compute the peak data load is set up. However, this may cause a considerable wastage of computing resources when the usage levels are much lower than the preset load. In consideration of this, this paper investigates an auto-scaling framework on cloud environment aiming to minimise the cost of resource use by automatically adjusting the virtual nodes depending on the real-time data load. A cost-effective auto-scaling (CEAS) framework is first proposed for an Amazon Web Services (AWS) Cloud environment. The proposed CEAS framework allows us to scale the computing resources of Hadoop cluster so as to either reduce the computing resource use when the workload is low or scale-up the computing resources to speed up the data processing and analysis within an adequate time. To validate the effectiveness of the proposed framework, a case study with real-time sentiment analysis on the universities’ tweets is provided to analyse the reviews/tweets of the people posted on social media. Such a dynamic scaling method offers a reference to improving the Twitter data analysis in a more cost-effective and flexible way.

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.

scholarly journals Real-Time Compression for Tactile Internet Data Streams

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1924
Author(s):  
Patrick Seeling ◽  
Martin Reisslein ◽  
Frank H. P. Fitzek
Keyword(s):  
Real Time ◽  
Data Streams ◽  
Control Loop ◽  
Real World Data ◽  
Perceptual Coding ◽  
Great Flexibility ◽  
Broad Application ◽  
Time Compression ◽  
Perceptual Threshold ◽  
Selection Of

The Tactile Internet will require ultra-low latencies for combining machines and humans in systems where humans are in the control loop. Real-time and perceptual coding in these systems commonly require content-specific approaches. We present a generic approach based on deliberately reduced number accuracy and evaluate the trade-off between savings achieved and errors introduced with real-world data for kinesthetic movement and tele-surgery. Our combination of bitplane-level accuracy adaptability with perceptual threshold-based limits allows for great flexibility in broad application scenarios. Combining the attainable savings with the relatively small introduced errors enables the optimal selection of a working point for the method in actual implementations.

XERIS/APEX

2021 ◽  
Vol 40 (2) ◽  
pp. 65-69
Author(s):  
Richard Wai
Keyword(s):  
Distributed Systems ◽  
Real Time ◽  
Distributed System ◽  
Dynamic Scaling ◽  
Distributed Application ◽  
Heavy Weight ◽  
System Models ◽  
In The Wild ◽  
On Line ◽  
Language Technologies

Modern day cloud native applications have become broadly representative of distributed systems in the wild. However, unlike traditional distributed system models with conceptually static designs, cloud-native systems emphasize dynamic scaling and on-line iteration (CI/CD). Cloud-native systems tend to be architected around a networked collection of distinct programs ("microservices") that can be added, removed, and updated in real-time. Typically, distinct containerized programs constitute individual microservices that then communicate among the larger distributed application through heavy-weight protocols. Common communication stacks exchange JSON or XML objects over HTTP, via TCP/TLS, and incur significant overhead, particularly when using small size message sizes. Additionally, interpreted/JIT/VM-based languages such as Javascript (NodeJS/Deno), Java, and Python are dominant in modern microservice programs. These language technologies, along with the high-overhead messaging, can impose superlinear cost increases (hardware demands) on scale-out, particularly towards hyperscale and/or with latency-sensitive workloads.

scholarly journals Perancangan Aplikasi Validasi Absensi Ujian Akhir Semester Mahasiswa Menggunakan Quick Response (QR) Code

2020 ◽  
Vol 1 (01) ◽  
Author(s):  
Ambar Safaatun ◽  
Ambar Tri Hapsari ◽  
Aswin Fitriansyah
Keyword(s):  
Real Time ◽  
Qr Code ◽  
Quick Response

Tujuan sistem validasi kehadiran mahasiswa dalam ujian akhir semester menggunakan Quick Response (QR) Code adalahmengembangkan sistem validasi kehadiran Mahasiswa pada saat Ujian Akhir Semester (UAS). Dengan menggunakan Quick Response (QR) Code dapat meningkatkan akurasi kehadiran dan mengurangi kecurangan dengan memanfaatkan jasa orang lain untuk mengerjakan ujian dan menyamar sebagai peserta ujian yang sebenarnya dengan menerima imbalan uang (joki). Dan harapan Peneliti juga untuk mempermudah pengawas ujian dalam melakukan validasi kehadiran mahasiswa pada saat Ujian Akhir Semester (UAS). Metode penelitian yang digunakan untuk menganalisis proses validasi kehadiran peserta Ujian Akhir Semester (UAS) ini adalah metode observasi, studi literature dan wawancara. Peneliti juga menggunakan pendekatan struktural dalam menyusun langkah-langkah pengembangan sistem. Setelah peneliti menganalisis masalah yang terjadi pada saat pelaksanaan Ujian Akhir Semester (UAS) di Universitas Terbuka, akhirnya peneliti menarik simpulan dengan adanya sistem ini, masalah pelanggaran tata tertib dalam pelaksanaan Ujian Akhir Semester (UAS) dengan meningkatkan akurasi kehadiran sehingga mengurangi celah kecurangan tersebut. Masalah mahasiswa tidak membawa kartu identitas yang menyulitkan proses validasi peserta ujian pada saat pelaksanaan Ujian Akhir Semester (UAS) teratasi dengan adanya Quick Response (QR) Code serta mempermudah pengawas ujian dalam melakukan validasi kehadiran mahasiswa saat Ujian Akhir Semester (UAS) beserta presensi secara real time

scholarly journals Robotic Ultrasound Scanning With Real-Time Image-Based Force Adjustment: Quick Response for Enabling Physical Distancing During the COVID-19 Pandemic

2021 ◽  
Vol 8 ◽  
Author(s):  
Mojtaba Akbari ◽  
Jay Carriere ◽  
Tyler Meyer ◽  
Ron Sloboda ◽  
Siraj Husain ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Real Time ◽  
Close Contact ◽  
Image Features ◽  
Svm Classifier ◽  
Quick Response ◽  
Robot Arm ◽  
Noise Characteristics ◽  
The Us

During an ultrasound (US) scan, the sonographer is in close contact with the patient, which puts them at risk of COVID-19 transmission. In this paper, we propose a robot-assisted system that automatically scans tissue, increasing sonographer/patient distance and decreasing contact duration between them. This method is developed as a quick response to the COVID-19 pandemic. It considers the preferences of the sonographers in terms of how US scanning is done and can be trained quickly for different applications. Our proposed system automatically scans the tissue using a dexterous robot arm that holds US probe. The system assesses the quality of the acquired US images in real-time. This US image feedback will be used to automatically adjust the US probe contact force based on the quality of the image frame. The quality assessment algorithm is based on three US image features: correlation, compression and noise characteristics. These US image features are input to the SVM classifier, and the robot arm will adjust the US scanning force based on the SVM output. The proposed system enables the sonographer to maintain a distance from the patient because the sonographer does not have to be holding the probe and pressing against the patient's body for any prolonged time. The SVM was trained using bovine and porcine biological tissue, the system was then tested experimentally on plastisol phantom tissue. The result of the experiments shows us that our proposed quality assessment algorithm successfully maintains US image quality and is fast enough for use in a robotic control loop.

A Novel Feasibility Test for Energy Minimization of Real-Time Mixed Task Sets for DVS-Enabled Uniprocessor System

2021 ◽  
pp. 2250052
Author(s):  
H. T. Manohara ◽  
B. P. Harish
Keyword(s):  
Real Time ◽  
Energy Minimization ◽  
Supply Voltage ◽  
Simultaneous Optimization ◽  
Dynamic Scaling ◽  
Operating Voltage ◽  
Periodic Tasks ◽  
Optimal Operating ◽  
Dynamic Activity ◽  
Task Sets

With advancements in computing and communication technologies on mobile devices, the performance requirements of embedded processors have significantly increased, resulting in a corresponding increase in its energy consumption. Dynamic scaling of operating voltage and operating frequency has a strong correlation to energy minimization in CMOS real-time circuits. Simultaneous optimization of ([Formula: see text], [Formula: see text] pairs under dynamic activity levels is thus extensively investigated over several years. The supply voltage is tuned dynamically during runtime (DVS), with a fixed threshold voltage, to achieve energy minimization. This work addresses the issue of maximizing the energy efficiency of real-time periodic, aperiodic and mixed task sets, in a uniprocessor system, by developing a novel task feasibility methodology, with a novel processor performance-based constraint, to generate the optimal operating supply voltage to the individual task of task sets. The energy minimization of real-time mixed task sets is formulated as Geometric Programming (GP) problem, by varying frequency for periodic tasks sets and keeping fixed frequency for aperiodic tasks set, over a range of task sets and hence computing optimal operating voltages. Simulation experiments show energy savings on the cumulative basis of 50%, 38% and 29% for periodic, aperiodic and mixed task sets, respectively, based on the processing timing constraints of task sets.

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