A Contribution to the Sensor Network Management for Context Awareness in Ubicomp

2014 ◽  
Author(s):  
Rodrigo Santos de Souza ◽  
João Ladislau Barbará Lopes ◽  
Claudio Fernando Resin Geyer ◽  
Ana Marilza Pernas Fleischmann ◽  
Adenauer Correa Yamin ◽  
...  
Keyword(s):  
Network Management ◽  
Sensor Network ◽  
Context Awareness

scholarly journals CONTEXT STORAGE USING CLOUD-BASED MONGODB WITH RULE-BASED RETE ALGORITHM

2021 ◽  
Vol 9 (2) ◽  
pp. 1022-1030
Author(s):  
Shivakumar. C, Et. al.
Keyword(s):  
Sensor Network ◽  
Context Awareness ◽  
Research Work ◽  
Context Aware ◽  
The Novel ◽  
Rule Based ◽  
Smart System ◽  
Context Aware Computing ◽  
Context Data ◽  
Day By Day

In this Context-aware computing era, everything is being automated and because of this, smart system’s count been incrementing day by day.  The smart system is all about context awareness, which is a synergy with the objects in the system. The result of the interaction between the users and the sensors is nothing but the repository of the vast amount of context data. Now the challenging task is to represent, store, and retrieve context data. So, in this research work, we have provided solutions to context storage. Since the data generated from the sensor network is dynamic, we have represented data using Context dimension tree, stored the data in cloud-based ‘MongoDB’, which is a NoSQL. It provides dynamic schema and reasoning data using If-Then rules with RETE algorithm. The Novel research work is the integration of NoSQL cloud-based MongoDB, rule-based RETE algorithm and CLIPS tool architecture. This integration helps us to represent, store, retrieve and derive inferences from the context data efficiently..                       

scholarly journals Integrating Context Awareness and SDN for a Lightweight Approach to Adaptive Networking

2021 ◽  
Author(s):  
José C. F. M. Júnior ◽  
David C. P. da Cunha ◽  
Carlos A. G. Ferraz
Keyword(s):  
Network Management ◽  
Context Awareness ◽  
Traffic Congestion ◽  
Response Times ◽  
Management Approach ◽  
Human Intervention ◽  
Human Errors ◽  
Research Challenges ◽  
Challenges And Opportunities ◽  
Complex Cases

With computer networks everywhere, managing them is becoming increasingly complex, leading to higher costs, longer response times, and more human errors in decision making. Given that, the search for a Smart Network Management, with less human intervention and more automation, becomes indispensable. Several technologies have been proposed to enable “Smart Management,” including machine learning, notably for more complex cases. The Software-Defined Networking (SDN) paradigm is one of the most promising. Literature shows, however, that there are still several research challenges and opportunities for the automation of many network management tasks. This paper proposes to combine context awareness with SDN in a lightweight approach to Smart Management, or Adaptive Networking, to handle in a simplified way everyday events such as link-down and traffic congestion. A comparative analysis shows that the management approach combining context awareness with SDN is between 40% and 73% faster than the support of SDN to a human-driven management.

Using Physical-level Context Awareness to Improve Service Ranking in Wireless Sensor Network

2012 ◽  
Vol 7 (6) ◽  
Author(s):  
Jun Lei ◽  
XingHua Yang ◽  
YinLong Liu ◽  
YiFang Qin ◽  
Hui Tang ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Context Awareness ◽  
Wireless Sensor ◽  
Physical Level ◽  
Service Ranking
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