Leveraging Genetic Algorithm to Compose Web Services in a Context-Aware Environment

2013 ◽  
Author(s):  
Zhichao Zhang ◽  
Shaoqiu Zheng ◽  
Weiping Li ◽  
Ying Tan ◽  
Zhonghai Wu ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Web Services ◽  
Context Aware

A POWER CONSUMPTION ACTIVITY BASED HETEROGENEOUS SOA FRAMEWORK FOR CONTEXT-AWARE HOME SERVICES

2011 ◽  
Vol 20 (07) ◽  
pp. 1211-1230 ◽  
Author(s):  
HYUN SANG CHO ◽  
TAKEKAZU KATO ◽  
TATSUYA YAMAZAKI ◽  
MINSOO HAHN
Keyword(s):  
Web Services ◽  
Power Consumption ◽  
Service Oriented Architecture ◽  
Control Function ◽  
Home Network ◽  
Network System ◽  
Context Aware ◽  
Flexible Architecture ◽  
And Control ◽  
Monitor And Control

The home network is one of the emerging areas from the last century. However, the growth of the home network market is stationary at present. This paper describes the limitations of the home network system and the requirements for overcoming the current limitations. Also described is a new home network service system known as COWS and its easy installation and scalable operation. COWS consists of power consumption monitor and control devices along with a service server that is a complementary combination of Open Service Gateway initiative (OSGi) and web services. A home network system has a dynamic, heterogeneous, distributed, and scalable topology. Service Oriented Architecture (SOA) has been proposed as a solution that satisfies the requirement of a home network, and OSGi and web services are two successful SOA-based frameworks. An included service server has a flexible architecture that consists of a core and extendable service packages. A power consumption monitor and control function provides useful context information for activity-based context-aware services and optimizes the power consumption. The system can be installed easily into existing and new houses to solve the current barrier of the popularization of home network services.

A Recommendation Model for Energy-Efficient Data Mining Services Based on Data Properties

2021 ◽  
Author(s):  
Zainab Al-Zanbouri
Keyword(s):  
Data Mining ◽  
Energy Consumption ◽  
Web Services ◽  
Recommender System ◽  
Energy Efficient ◽  
Contextual Information ◽  
Three Dimensions ◽  
Context Aware ◽  
Rating Data ◽  
Recommendation Accuracy

Currently, there is a big increase in the usage of data analytics applications and services because of the growth in the data produced from different sources. The QoS properties such as response time and latency of these services are important factors to decide which services to select. As a result of IT expansion, energy consumption has become a big issue. Therefore, establishing a QoS-based web service recommender system that considers energy consumption as one of the essential QoS properties represents a significant step towards selecting the energy efficient web services. This dissertation presents an experimental study on energy consumption levels and latency behavior collected from a set of data mining web services running on different datasets. Our study shows that there is a strong relation between the dataset properties and the QoS properties. Based on the findings from this study, a recommender system is built which considers three dimensions (user, service, dataset). The energy consumption values of candidate services invoked by specific users can be predicted for a given dataset. Afterwards, these services can be ranked according to their predicted energy values and presented to users. We propose three approaches to build our recommender system and we treat it as a context-aware recommendation problem. The dataset is considered as contextual information and we use a context-aware matrix factorization model to predict energy values. In the first approach, we adopt the pre-filtering model where the contextual information serves as a query for filtering relevant rating data. In the second approach, we propose a new method for the pre-filtering implementation. Finally, in the last approach, we adopt the contextual modeling method and we explore different ways of representing dataset information as contextual factors to investigate their impacts on the recommendation accuracy. We compare the proposed approaches with the baseline approaches and the results show the effectiveness of the proposed ones. Also, we compare the performance of the three approaches to discover the best-fit approach when being measured using different metrics. Both prediction and recommendation accuracy of the proposed approaches are significantly better than the baseline models.

Consumer Privacy Enforcement in Context-Aware Web Services

2013 ◽  
Vol 10 (3) ◽  
pp. 24-41 ◽  
Author(s):  
Georgia M. Kapitsaki
Keyword(s):  
Web Services ◽  
Information Needs ◽  
Consumer Preferences ◽  
End Users ◽  
Sensitive Information ◽  
Context Aware ◽  
Human Right ◽  
Consumer Privacy ◽  
Privacy Preferences ◽  
The One

Privacy protection constitutes a genuine human right reflected both in the legislation and in different aspects of software engineering. Sensitive information needs to be protected in end-users interaction with Web Services especially in cases, where context-aware features are included. In this work the authors address the inclusion of consumer privacy preferences in the provision of context-aware Web Services. To achieve this the authors propose, on the one hand, a preferences language, where end-users can specify their privacy options, namely Consumer Privacy Language, and, on the other hand, a seamless enforcement mechanism that considers consumer preferences by intercepting and modifying appropriately Simple Object Access Protocol request and response messages. The enforcement approach has been evaluated based on various execution metrics for an example use case consisting of various Web Services and for different users configurations demonstrating the usefulness of the approach assisting towards the provision of privacy-aware environments.

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