A Quality of Service Based Queueing Policy Ensuring Fairness to Real-Time Data Transfers in Internet

2016 ◽  
Vol 13 (12) ◽  
pp. 9169-9174
Author(s):  
Jyothish K John ◽  
R. V. Siva Balan
Keyword(s):  
Quality Of Service ◽  
Real Time ◽  
Time Data ◽  
Real Time Data ◽  
Data Transfers

Information Transmission with Quality of Service

2010 ◽  
pp. 262-275
Author(s):  
Manjunath Ramachandra
Keyword(s):  
Quality Of Service ◽  
Supply Chain ◽  
Information Transmission ◽  
Real Time ◽  
Data Transfer ◽  
Time Data ◽  
Real Time Data ◽  
Data Transfers ◽  
The Web

The data being transferred over the supply chain has to compete with the increasing applications around the web, throwing open the challenge of meeting the constraint of in-time data transfers with the available resources. It often leads to flooding of resources, resulting in the wastage of time and loss of data. Most of the applications around the customer require real time data transfer over the web to enable right decisions. To make it happen, stringent constraints are required to be imposed on the quality of the transfer. This chapter provides the mechanism for shaping of traffic flows towards sharing the existing infrastructure.

Traffic Controller for Handling Service Quality in Multimedia Network

2010 ◽  
pp. 96-112
Author(s):  
Manjunath Ramachandra ◽  
Vikas Jain
Keyword(s):  
Real Time ◽  
Long Range ◽  
Multimedia Data ◽  
Time Data ◽  
Self Similarity ◽  
Real Time Data ◽  
Data Transfers ◽  
Multimedia Network ◽  
Different Origin

The present day Internet traffic largely caters for the multimedia traffic throwing open new and unthinkable applications such as tele-surgery. The complexity of data transactions increases with a demand for in time and real time data transfers, demanding the limited resources of the network beyond their capabilities. It requires a prioritization of data transfers, controlled dumping of data over the network etc. To make the matter worse, the data from different origin combine together imparting long lasting detrimental features such as self similarity and long range dependency in to the traffic. The multimedia data fortunately is associated with redundancies that may be removed through efficient compression techniques. There exists a provision to control the compression or bitrates based on the availability of resources in the network. The traffic controller or shaper has to optimize the quality of the transferred multimedia data depending up on the state of the network. In this chapter, a novel traffic shaper is introduced considering the adverse properties of the network and counteract with the same.

Model Driven Engineering for Quality of Service Management

2016 ◽  
Vol 27 (4) ◽  
pp. 24-38 ◽  
Author(s):  
Salwa M'barek ◽  
Leila Baccouche ◽  
Henda Ben Ghezala
Keyword(s):  
Quality Of Service ◽  
Real Time ◽  
Service Management ◽  
Software Tool ◽  
Model Driven Engineering ◽  
Time Data ◽  
Arrival Times ◽  
Model Driven ◽  
Real Time Data

Real-time applications managing a large number of real-time data require the use of Real-time Database Management Systems (RTDBMS) to meet temporal constraints of both real-time data and transactions. However, a RTDBMS has a dynamic workload and may be frequently overloaded since the arrival times and workloads of user transactions are unpredictable. Therefore, Quality of Service management solutions have been proposed to guarantee the stability of RTDBMS even during unpredictable overload periods. While effective, the design and reuse of these solutions is challenging because they are not formally modeled and there is no tool neither a methodology that helps us design such solutions. To address these issues, the authors propose a design framework based on the Model-Driven Engineering approach providing a modeling architecture, a strategic methodology and a software tool to support modeling and reusing such solutions. The framework is implemented and tested for a real Qos management solution.

scholarly journals QoS Management for Embedded Databases in Multicore-Based Embedded Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Woochul Kang ◽  
Jaeyong Chung
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Control Method ◽  
Network Connectivity ◽  
Time Data ◽  
Quality Of Data ◽  
Multiple Control ◽  
Data Intensive ◽  
Real Time Data

With ubiquitous deployment of sensors and network connectivity, amounts of real-time data for embedded systems are increasing rapidly and database capability is required for many embedded systems for systematic management of real-time data. In such embedded systems, supporting the timeliness of tasks accessing databases is an important problem. However, recent multicore-based embedded architectures pose a significant challenge for such data-intensive real-time tasks since the response time of accessing data can be significantly affected by potential intercore interferences. In this paper, we propose a novel feedback control scheme that supports the timeliness of data-intensive tasks against unpredictable intercore interferences. In particular, we use multiple inputs/multiple outputs (MIMO) control method that exploits multiple control knobs, for example, CPU frequency and the Quality-of-Data (QoD) to handle highly unpredictable workloads in multicore systems. Experimental results, using actual implementation, show that the proposed approach achieves the target Quality-of-Service (QoS) goals, such as task timeliness and Quality-of-Data (QoD) while consuming less energy compared to baseline approaches.

scholarly journals Urban Planning and Smart City Decision Management Empowered by Real-Time Data Processing Using Big Data Analytics

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2994 ◽  
Author(s):  
Bhagya Silva ◽  
Murad Khan ◽  
Changsu Jung ◽  
Jihun Seo ◽  
Diyan Muhammad ◽  
...  
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Real Time ◽  
Smart City ◽  
Data Analytics ◽  
Smart Cities ◽  
Big Data Analytics ◽  
Time Data ◽  
Real Time Data

The Internet of Things (IoT), inspired by the tremendous growth of connected heterogeneous devices, has pioneered the notion of smart city. Various components, i.e., smart transportation, smart community, smart healthcare, smart grid, etc. which are integrated within smart city architecture aims to enrich the quality of life (QoL) of urban citizens. However, real-time processing requirements and exponential data growth withhold smart city realization. Therefore, herein we propose a Big Data analytics (BDA)-embedded experimental architecture for smart cities. Two major aspects are served by the BDA-embedded smart city. Firstly, it facilitates exploitation of urban Big Data (UBD) in planning, designing, and maintaining smart cities. Secondly, it occupies BDA to manage and process voluminous UBD to enhance the quality of urban services. Three tiers of the proposed architecture are liable for data aggregation, real-time data management, and service provisioning. Moreover, offline and online data processing tasks are further expedited by integrating data normalizing and data filtering techniques to the proposed work. By analyzing authenticated datasets, we obtained the threshold values required for urban planning and city operation management. Performance metrics in terms of online and offline data processing for the proposed dual-node Hadoop cluster is obtained using aforementioned authentic datasets. Throughput and processing time analysis performed with regard to existing works guarantee the performance superiority of the proposed work. Hence, we can claim the applicability and reliability of implementing proposed BDA-embedded smart city architecture in the real world.

scholarly journals Iso-Quality of Service: Fairly Ranking Servers for Real-Time Data Analytics

2015 ◽  
Vol 25 (03) ◽  
pp. 1541004 ◽  
Author(s):  
Giorgis Georgakoudis ◽  
Charles Gillan ◽  
Ahmed Sayed ◽  
Ivor Spence ◽  
Richard Faloon ◽  
...  
Keyword(s):  
Quality Of Service ◽  
Real Time ◽  
Energy Efficient ◽  
High Performance ◽  
Real Life ◽  
Evaluation Methodology ◽  
Time Data ◽  
Output Quality ◽  
Qos Evaluation

We present a mathematically rigorous iso-Quality-of-Service (QoS) metric which relates the achievable quality of service (QoS) for a real-time analytics service with workload specific and use case specific performance and output quality requirements to the energy cost of offering the service by different server architectures. Using a new iso-QoS evaluation methodology, we scale server resources to meet QoS targets and directly rank the servers in terms of their energy-efficiency and by extension cost of ownership. Our metric and method are platform-independent and enable fair comparison of datacenter compute servers with significant architectural diversity, including micro-servers. We deploy our metric and methodology to compare three servers running financial option pricing workloads on real-life market data. We find that server ranking is sensitive to data inputs and desired QoS level and that although scale-out micro-servers can be up to two times more energy-efficient than conventional heavyweight servers for the same target QoS, they are still six times less energy efficient than high-performance computational accelerators.

scholarly journals Influence of load balancing on quality of real time data transmission

2009 ◽  
Vol 6 (3) ◽  
pp. 515-524 ◽  
Author(s):  
Natasa Maksic ◽  
Petar Knezevic ◽  
Marija Antic ◽  
Aleksandra Smiljanic
Keyword(s):  
Load Balancing ◽  
Real Time ◽  
Data Transmission ◽  
Routing Algorithm ◽  
Network Throughput ◽  
Time Data ◽  
Real Time Data ◽  
The Difference

The routing algorithm with load balancing presented in [1] represents the modification of OSPF protocol, which enables the optimization to achieve higher network throughput. In the case of routing with load balancing, packets belonging to the same stream use different paths in the network. This paper analyzes the influence of the difference in packet propagation times on the quality of real-time data transmission. The proposed algorithm was implemented and the simulation network was formed to measure the jitter. .

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