Statistical Quality of Service Guarantee for Temporal Consistency of Real-Time Data Objects

2005 ◽  
Author(s):  
Kam-Yiu Lam ◽  
Ming Xiong ◽  
Bi Yu Liang ◽  
Yang Guo
Keyword(s):  
Quality Of Service ◽  
Real Time ◽  
Temporal Consistency ◽  
Time Data ◽  
Statistical Quality ◽  
Service Guarantee ◽  
Real Time Data ◽  
Data Objects ◽  
Quality Of Service Guarantee

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.

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.

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.

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