In-Stream Data Processing for Tactical Environments

2011 ◽  
pp. 26-44
Author(s):  
Marco Carvalho
Keyword(s):  
Online Learning ◽  
Data Processing ◽  
Information Management ◽  
Data Dissemination ◽  
Service Availability ◽  
Formal Description ◽  
Stream Data ◽  
Simulation Experiments ◽  
Distributed Information ◽  
New Strategy

Data dissemination and information management technologies for tactical environments are quickly becoming major areas of research for both military and civilian applications. Critical to the problem is the need for fully distributed information management technologies that are efficient, adaptive and resilient. In this paper, we introduce and discuss a new strategy for tactical data dissemination and processing based on distributed online learning. Starting from a formal description of the problem we introduce our proposed solution and its theoretical properties. We also present and discuss a number of simulation experiments for different data dissemination scenarios, and conclude the work with a discussion on how such techniques may be applied to critical e-government environments under different assumptions of service availability and information release policies.

In-Stream Data Processing for Tactical Environments

2009 ◽  
pp. 295-312
Author(s):  
Marco Carvalho
Keyword(s):  
Online Learning ◽  
Data Processing ◽  
Information Management ◽  
Data Dissemination ◽  
Service Availability ◽  
Formal Description ◽  
Stream Data ◽  
Simulation Experiments ◽  
Distributed Information ◽  
New Strategy

Data dissemination and information management technologies for tactical environments are quickly becoming major areas of research for both military and civilian applications. Critical to the problem is the need for fully distributed information management technologies that are efficient, adaptive and resilient. In this paper, we introduce and discuss a new strategy for tactical data dissemination and processing based on distributed online learning. Starting from a formal description of the problem we introduce our proposed solution and its theoretical properties. We also present and discuss a number of simulation experiments for different data dissemination scenarios, and conclude the work with a discussion on how such techniques may be applied to critical e-government environments under different assumptions of service availability and information release policies.

Production Plan of Information Management System for Virtual Industry

2013 ◽  
Vol 765-767 ◽  
pp. 1271-1274
Author(s):  
Jing Su ◽  
Xiao Jing Li
Keyword(s):  
Information Management ◽  
Management System ◽  
Information Management System ◽  
Virtual Enterprises ◽  
Distributed Information ◽  
Planning And Control ◽  
Data Object ◽  
Basic Services ◽  
And Control ◽  
Information Manager

The information management is a crucial mission for a virtual industry in such a competitive market environment. The typical characteristic of information management is distribution, autonomy and co-operation. Based on an on-going ESPRIT project (X-CITTIC), The author presents a distributed information management architecture for production planning and control in a virtual enterprises of semiconductor manufacturing. Object technologies are widely used in its design and implementation. A detailed structure of the components in the architecture, called information managers, is also suggested and introduced. Each information manager has three elements: a data object server, a database and a group of meta-objects. The information management can provide not only basic services (e.g. read and write) but also advanced services (e.g. notification, security control, subscription and data sending). Finally the present X-CITTIC information management system is detailed introduced.

scholarly journals Performance Assay of Big IoT Data Analytics Framework

2019 ◽  
Vol 8 (4) ◽  
pp. 8593-8596
Keyword(s):  
Internet Of Things ◽  
Data Processing ◽  
High Velocity ◽  
Data Analytics ◽  
Real Life ◽  
Global Environment ◽  
Stream Data ◽  
Processing Level ◽  
Stream Analytics ◽  
Apache Storm

Evaluation of Internet of Things (IoT) technologies in real life has scaled the enumeration of data in huge volumes and that too with high velocity, and thus a new issue has come into picture that is of management & analytics of this BIG IOT STREAM data. In order to optimize the performance of the IoT Machines and services provided by the vendors, industry is giving high priority to analyze this big IoT Stream Data for surviving in the competitive global environment. Thses analysis are done through number of applications using various Data Analytics Framework, which require obtaining the valuable information intelligently from a large amount of real-time produced data. This paper, discusses the challenges and issues faced by distributed stream analytics frameworks at the data processing level and tries to recommend a possible a Scalable Framework to adapt with the volume and velocity of Big IoT Stream Data. Experiments focus on evaluating the performance of three Distributed Stream Analytics Here Analytics frameworks, namely Apache Spark, Splunk and Apache Storm are being evaluated over large steam IoT data on latency & throughput as parameters in respect to concurrency. The outcome of the paper is to find the best possible existing framework and recommend a possible scalable framework.

A New Nanorobots Movement Control Strategy for Treating Cancer

2021 ◽  
Vol 12 (4) ◽  
pp. 149-163
Author(s):  
Doaa Ezzat ◽  
Safaa El-Sayed Amin ◽  
Howida A. Shedeed ◽  
Mohamed F. Tolba
Keyword(s):  
Fuzzy Logic ◽  
Cancer Cells ◽  
Control Strategy ◽  
Blood Cells ◽  
Movement Control ◽  
Simulation Experiments ◽  
Swarm Optimization ◽  
New Strategy ◽  
Dynamic Obstacle Avoidance ◽  
Dynamic Obstacle

Nanorobots were proposed to deliver drugs directly into cancer cells to destroy only these cells without harming the surrounding cells. During their journey, the nanorobots may encounter some obstacles such as blood cells which may be resistant to their movement. So, it is necessary to avoid collisions with these obstacles to achieve their goal. This study proposes a new strategy for controlling the nanorobots movement in human body to reach cancer cells. This proposed strategy uses an efficient algorithm based on fuzzy logic for dynamic obstacle avoidance. Also, this proposed strategy uses the directed particle swarm optimization (DPSO) algorithm for delivering nanorobots to cancer cells. Simulation experiments have proved that the proposed control strategy can efficiently deliver nanorobots to their target and also avoid collisions with dynamic obstacles which move in the same direction of the nanorobots or across their direction.

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