Bond computing systems: a biologically inspired and high-level dynamics model for pervasive computing

2009 ◽  
Vol 9 (2) ◽  
pp. 347-364
Author(s):  
Linmin Yang ◽  
Zhe Dang ◽  
Oscar H. Ibarra
Keyword(s):  
Pervasive Computing ◽  
Dynamics Model ◽  
Biologically Inspired ◽  
Computing Systems ◽  
High Level

scholarly journals Commonsense Spatial Reasoning: an Informational Perspective

1970 ◽  
Vol 4 (2) ◽  
pp. 187-194
Author(s):  
Stefania Bandini ◽  
Gianluca Colombo ◽  
Alessandro Mosca ◽  
Matteo Palmonari
Keyword(s):  
Pervasive Computing ◽  
Information Sources ◽  
Spatial Reasoning ◽  
Formal Model ◽  
Mathematical Reasoning ◽  
Spatial Knowledge ◽  
Logical Framework ◽  
Computing Systems ◽  
Positive Meaning ◽  
High Level

Pervasive Computing systems are characterized by possibly mobile components distributed in the environment and are devoted to collect, process and manage information in order to support users in different kind of activities. High-level correlation of information in such context can be defined, exploiting a formal model arising from the spatial disposition of information sources, as a form of commonsense spatial reasoning. With respect to this model, a Hybrid Logic to formalize commonsense spatial reasoning in these context has been defined. Here, on the basis of relevant analogies among Pervasive Computing and human practice in handling spatial knowledge, we suggest to provide the term “commonsense” with a positive meaning, showing that our logical framework captures some features of non-mathematical reasoning when spatially qualified information is concerned. The focus on such features and the analogies mentioned above suggest to qualify our approach to (commonsense) spatial reasoning as an informational approach.

scholarly journals Commonsense Spatial Reasoning: an Informational Perspective

1970 ◽  
Vol 4 (2) ◽  
pp. 187-194
Author(s):  
Stefania Bandini ◽  
Gianluca Colombo ◽  
Alessandro Mosca ◽  
Matteo Palmonari
Keyword(s):  
Pervasive Computing ◽  
Information Sources ◽  
Spatial Reasoning ◽  
Formal Model ◽  
Mathematical Reasoning ◽  
Spatial Knowledge ◽  
Logical Framework ◽  
Computing Systems ◽  
Positive Meaning ◽  
High Level

Pervasive Computing systems are characterized by possibly mobile components distributed in the environment and are devoted to collect, process and manage information in order to support users in different kind of activities. High-level correlation of information in such context can be defined, exploiting a formal model arising from the spatial disposition of information sources, as a form of commonsense spatial reasoning. With respect to this model, a Hybrid Logic to formalize commonsense spatial reasoning in these context has been defined. Here, on the basis of relevant analogies among Pervasive Computing and human practice in handling spatial knowledge, we suggest to provide the term “commonsense” with a positive meaning, showing that our logical framework captures some features of non-mathematical reasoning when spatially qualified information is concerned. The focus on such features and the analogies mentioned above suggest to qualify our approach to (commonsense) spatial reasoning as an informational approach.

A Security Architecture Based on Trust Management for Pervasive Computing Systems

2005 ◽  
Author(s):  
Lalana Kagal ◽  
Jeffrey Undercoffer ◽  
Filip Perich ◽  
Anupam Joshi ◽  
Tim Finin
Keyword(s):  
Pervasive Computing ◽  
Trust Management ◽  
Security Architecture ◽  
Computing Systems

scholarly journals Enhanced Round-Robin Algorithm in the Cloud Computing Environment for Optimal Task Scheduling

Computers ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 63
Author(s):  
Fahd Alhaidari ◽  
Taghreed Zayed Balharith
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Critical Role ◽  
Turnaround Time ◽  
Round Robin ◽  
Computing Systems ◽  
Time Quantum ◽  
Dynamic Time ◽  
High Level ◽  
Level Performance

Recently, there has been significant growth in the popularity of cloud computing systems. One of the main issues in building cloud computing systems is task scheduling. It plays a critical role in achieving high-level performance and outstanding throughput by having the greatest benefit from the resources. Therefore, enhancing task scheduling algorithms will enhance the QoS, thus leading to more sustainability of cloud computing systems. This paper introduces a novel technique called the dynamic round-robin heuristic algorithm (DRRHA) by utilizing the round-robin algorithm and tuning its time quantum in a dynamic manner based on the mean of the time quantum. Moreover, we applied the remaining burst time of the task as a factor to decide the continuity of executing the task during the current round. The experimental results obtained using the CloudSim Plus tool showed that the DRRHA significantly outperformed the competition in terms of the average waiting time, turnaround time, and response time compared with several studied algorithms, including IRRVQ, dynamic time slice round-robin, improved RR, and SRDQ algorithms.

Ontology-based models in pervasive computing systems

2007 ◽  
Vol 22 (4) ◽  
pp. 315-347 ◽  
Author(s):  
JUAN YE ◽  
LORCAN COYLE ◽  
SIMON DOBSON ◽  
PADDY NIXON
Keyword(s):  
Pervasive Computing ◽  
Information Exchange ◽  
Next Generation ◽  
Computing Systems ◽  
Diverse Range ◽  
Shared Representations ◽  
Pervasive Systems ◽  
Structured Information ◽  
Compare And Contrast

AbstractPervasive computing is by its nature open and extensible, and must integrate the information from a diverse range of sources. This leads to a problem of information exchange, so sub-systems must agree on shared representations. Ontologies potentially provide a well-founded mechanism for the representation and exchange of such structured information. A number of ontologies have been developed specifically for use in pervasive computing, none of which appears to cover adequately the space of concerns applicable to application designers. We compare and contrast the most popular ontologies, evaluating them against the system challenges generally recognized within the pervasive computing community. We identify a number of deficiencies that must be addressed in order to apply the ontological techniques successfully to next-generation pervasive systems.

scholarly journals Visual Behavior Based Bio-Inspired Polarization Techniques in Computer Vision and Robotics

2012 ◽  
pp. 243-272 ◽  
Author(s):  
Abd El Rahman Shabayek ◽  
Olivier Morel ◽  
David Fofi
Keyword(s):  
Computer Vision ◽  
Object Recognition ◽  
Visual Perception ◽  
Polarization Vision ◽  
Visual Behavior ◽  
Biologically Inspired ◽  
Long Time ◽  
Comprehensive Survey ◽  
High Level ◽  
And Robotics

For long time, it was thought that the sensing of polarization by animals is invariably related to their behavior, such as navigation and orientation. Recently, it was found that polarization can be part of a high-level visual perception, permitting a wide area of vision applications. Polarization vision can be used for most tasks of color vision including object recognition, contrast enhancement, camouflage breaking, and signal detection and discrimination. The polarization based visual behavior found in the animal kingdom is briefly covered. Then, the authors go in depth with the bio-inspired applications based on polarization in computer vision and robotics. The aim is to have a comprehensive survey highlighting the key principles of polarization based techniques and how they are biologically inspired.

scholarly journals Context-Aware User Modeling and Semantic Interoperability in Smart Home Environments

2015 ◽  
Vol 7 (3) ◽  
pp. 17-50
Author(s):  
Giorgos Siolas ◽  
George Caridakis ◽  
Phivos Mylonas ◽  
Giorgos Stratogiannis ◽  
Stefanos Kollias ◽  
...  
Keyword(s):  
Pervasive Computing ◽  
Smart Home ◽  
User Modeling ◽  
Collective Intelligence ◽  
Context Modeling ◽  
Home Environments ◽  
Computing Systems ◽  
Knowledge Based ◽  
Context Cues ◽  
Smart Home Environments

The current paper provides an overview on how user modeling, context awareness and content adaptation in Smart Home environments may be handled formally in order to capture the semantics that emerge from a newly introduced user experience: SandS is in fact a complete ecosystem of users within a social network, creating and exchanging content in the form of so-called recipes and developing a collective intelligence which adapts its operation through appropriate feedback provided by the user. The authors will approach SandS from the user's perspective and illustrate how users and their relationships can be modeled through a number of fuzzy stereotypical profiles. Additionally, context modeling in pervasive computing systems and especially in the Smart Home paradigm will be examined through appropriate representation of context cues in the overall interaction. Finally, the authors will investigate how users and system services although using languages of different semantic expressiveness can inter-operate successfully thanks to appropriate knowledge-based expert mappings.

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