Adaptive Future Internet Applications

2012 ◽  
pp. 333-353 ◽  
Author(s):  
Clarissa Cassales Marquezan ◽  
Andreas Metzger ◽  
Klaus Pohl ◽  
Vegard Engen ◽  
Michael Boniface ◽  
...  
Keyword(s):  
Web Services ◽  
Real World ◽  
Network Connectivity ◽  
Future Internet ◽  
Future Research ◽  
Service Provisioning ◽  
Internet Applications ◽  
Research Challenges ◽  
Adaptive Capabilities ◽  
Service Oriented

Adaptive capabilities are essential to guarantee the proper execution of Web services and service-oriented applications once dynamic changes are not exceptions but the rule. The importance of adaptive capabilities significantly increases in the context of Future Internet (FI) applications will have to autonomously adapt to changes on service provisioning, availability of things and content, computing resources, and network connectivity. Current solutions for adaptive Web services and adaptive service-based applications will be challenged in such a setting because they fall short to support essential characteristics of FI applications. This chapter analyzes and justifies the need for the transition from adaptive Web services and service-based applications to adaptive FI applications. Based on two real-world use cases from multimedia and logistics, the authors examine where current solutions fall short to properly address the adaptive needs of FI applications. They propose future research challenges that should be considered in adaptive FI applications.

Adaptive Future Internet Applications

2018 ◽  
pp. 1568-1589 ◽  
Author(s):  
Clarissa Cassales Marquezan ◽  
Andreas Metzger ◽  
Klaus Pohl ◽  
Vegard Engen ◽  
Michael Boniface ◽  
...  
Keyword(s):  
Web Services ◽  
Real World ◽  
Network Connectivity ◽  
Future Internet ◽  
Future Research ◽  
Service Provisioning ◽  
Internet Applications ◽  
Research Challenges ◽  
Adaptive Capabilities ◽  
Service Oriented

Adaptive capabilities are essential to guarantee the proper execution of Web services and service-oriented applications once dynamic changes are not exceptions but the rule. The importance of adaptive capabilities significantly increases in the context of Future Internet (FI) applications will have to autonomously adapt to changes on service provisioning, availability of things and content, computing resources, and network connectivity. Current solutions for adaptive Web services and adaptive service-based applications will be challenged in such a setting because they fall short to support essential characteristics of FI applications. This chapter analyzes and justifies the need for the transition from adaptive Web services and service-based applications to adaptive FI applications. Based on two real-world use cases from multimedia and logistics, the authors examine where current solutions fall short to properly address the adaptive needs of FI applications. They propose future research challenges that should be considered in adaptive FI applications.

Services and Service Composition – An Introduction (Services und Service Komposition – Eine Einführung)

2008 ◽  
Vol 50 (2) ◽  
Author(s):  
Shahram Dustdar ◽  
Mike P. Papazoglou
Keyword(s):  
Web Services ◽  
Service Composition ◽  
Web Applications ◽  
Future Research ◽  
Basic Principles ◽  
Service Oriented Computing ◽  
Research Challenges ◽  
Internet Computing ◽  
The Future ◽  
Service Oriented

SummaryIn this overview paper, we discuss the basic principles underlying service-oriented computing in general, and (Web) services in particular. We discuss the important differences between (Web) services and Web applications and other models in Internet computing. Finally, we discuss where we see the future research challenges in the area of service composition.

Service Provision Evolution in Self-Managed Future Internet Environments

2011 ◽  
pp. 112-140
Author(s):  
Apostolos Kousaridas ◽  
Panagis Madgalinos ◽  
Nancy Alonistioti
Keyword(s):  
Network Management ◽  
Service Provision ◽  
Future Internet ◽  
Future Research ◽  
Ip Multimedia Subsystem ◽  
Service Provisioning ◽  
Research Directions ◽  
Traditional Service ◽  
Future Research Directions ◽  
Internet Networks

Future Internet is based on the concepts of autonomicity and cognition, where each network element is able to monitor its surrounding environment, evaluate the situation, and decide the action that should be applied. In such context, the traditional service provisioning approaches necessitate a paradigm shift so as to incorporate the Cognitive Cycle. Towards this end, in this chapter, we introduce a Cognitive Service Provision framework suitable for Future Internet Networks. The proposed approach supports cognition by modeling a service as an aggregation of software components bundled together through a graph. Consequently, each service is composed by various components and is tailored to the operational context of the requestor. In order to prove the viability and applicability of the proposed approach we also introduce the enhancement of the IP Multimedia Subsystem through our Cognitive Service Provision framework. Finally, based on our work, we discuss future research directions and the link between service and network management.

Learning From Imbalanced Data

2018 ◽  
pp. 1825-1834 ◽  
Author(s):  
Lincy Mathews ◽  
Seetha Hari
Keyword(s):  
Real World ◽  
Imbalanced Data ◽  
Misclassification Rate ◽  
Future Research ◽  
Data Sets ◽  
Real World Data ◽  
Imbalanced Data Sets ◽  
Challenging Issue ◽  
Research Challenges ◽  
Balanced Distribution

A very challenging issue in real world data is that in many domains like medicine, finance, marketing, web, telecommunication, management etc., the distribution of data among classes is inherently imbalanced. A widely accepted researched issue is that the traditional classifier algorithms assume a balanced distribution among the classes. Data imbalance is evident when the number of instances representing the class of concern is much lesser than other classes. Hence, the classifiers tend to bias towards the well-represented class. This leads to a higher misclassification rate among the lesser represented class. Hence, there is a need of efficient learners to classify imbalanced data. This chapter aims to address the need, challenges, existing methods and evaluation metrics identified when learning from imbalanced data sets. Future research challenges and directions are highlighted.

A Stitch in Time Saves Nine: Early Improving Code-First Web Services Discoverability

2015 ◽  
Vol 24 (02) ◽  
pp. 1550004 ◽  
Author(s):  
Cristian Mateos ◽  
Marco Crasso ◽  
Alejandro Zunino ◽  
José Luis Ordiales Coscia
Keyword(s):  
Web Services ◽  
Web Service ◽  
Real World ◽  
Service Discovery ◽  
Statistical Correlation ◽  
Web Service Discovery ◽  
Computing Paradigm ◽  
Service Oriented ◽  
Wsdl Documents ◽  
Pattern Occurrences

Web Services represent a number of standard technologies and methodologies that allow developers to build applications under the Service-Oriented Computing paradigm. Within these, the WSDL language is used for representing Web Service interfaces, while code-first remains the de facto standard for building such interfaces. Previous studies with contract-first Web Services have shown that avoiding a specific catalog of bad WSDL specification practices, or anti-patterns, can reward Web Service publishers as service understandability and discoverability are considerably improved. In this paper, we study a number of simple and well-known code service refactorings that early reduce anti-pattern occurrences in WSDL documents. This relationship relies upon a statistical correlation between common OO metrics taken on a service's code and the anti-pattern occurrences in the generated WSDL document. We quantify the effects of the refactorings — which directly modify OO metric values and indirectly alter anti-pattern occurrences — on service discovery. All in all, we show that by applying the studied refactorings, anti-patterns are reduced and Web Service discovery is significantly improved. For the experiments, a dataset of real-world Web Services and an academic service registry have been employed.

Evaluating Mobile Applications in Virtual Environments

2013 ◽  
Vol 5 (4) ◽  
pp. 1-19 ◽  
Author(s):  
Ioannis Delikostidis ◽  
Thore Fechner ◽  
Holger Fritze ◽  
Ahmed Mahmoud AbdelMouty ◽  
Christian Kray
Keyword(s):  
Virtual Environments ◽  
Real World ◽  
Mobile Applications ◽  
Future Research ◽  
Context Aware ◽  
Middle Ground ◽  
Selection Strategies ◽  
Research Challenges ◽  
Evaluation Approaches ◽  
Specific Evaluation

Context plays a central role in mobile applications but is very difficult to control, and therefore, the evaluation of context-aware applications can be challenging. Traditionally, researchers had to choose either field-based or lab-based studies but recently, virtual environments have been proposed as a middle-ground between those two methods. In this paper, the authors review previous work on using virtual environments to evaluate mobile applications. the authors identify and classify different approaches to simulate specific aspects of the real world, and analyse their relative properties with respect to evaluating different facets of context-aware mobile applications. Based on this analysis, the authors derive criteria and selection strategies that can help researchers in picking specific evaluation approaches. The authors also point out a number of research challenges in this area as well as a number of promising areas for future research.

Learning From Imbalanced Data

2019 ◽  
pp. 403-414 ◽  
Author(s):  
Lincy Mathews ◽  
Seetha Hari
Keyword(s):  
Real World ◽  
Imbalanced Data ◽  
Misclassification Rate ◽  
Future Research ◽  
Data Sets ◽  
Real World Data ◽  
Imbalanced Data Sets ◽  
Challenging Issue ◽  
Research Challenges ◽  
Balanced Distribution

A very challenging issue in real-world data is that in many domains like medicine, finance, marketing, web, telecommunication, management, etc. the distribution of data among classes is inherently imbalanced. A widely accepted researched issue is that the traditional classifier algorithms assume a balanced distribution among the classes. Data imbalance is evident when the number of instances representing the class of concern is much lesser than other classes. Hence, the classifiers tend to bias towards the well-represented class. This leads to a higher misclassification rate among the lesser represented class. Hence, there is a need of efficient learners to classify imbalanced data. This chapter aims to address the need, challenges, existing methods, and evaluation metrics identified when learning from imbalanced data sets. Future research challenges and directions are highlighted.

Optimal Fault Tolerance Strategy Selection for Web Services

2010 ◽  
Vol 7 (4) ◽  
pp. 21-40 ◽  
Author(s):  
Zibin Zheng ◽  
Michael R. Lyu
Keyword(s):  
Fault Tolerance ◽  
Web Services ◽  
Real World ◽  
Evaluation Framework ◽  
Strategy Selection ◽  
Tolerance Strategy ◽  
Strategy Evaluation ◽  
Service Oriented ◽  
Selection Framework ◽  
Qos Performance

Service-oriented systems are usually composed by heterogeneous Web services, which are distributed across the Internet and provided by organizations. Building highly reliable service-oriented systems is a challenge due to the highly dynamic nature of Web services. In this paper, the authors apply software fault tolerance techniques for Web services, where the component failures are handled by fault tolerance strategies. In this paper, a distributed fault tolerance strategy evaluation and selection framework is proposed based on versatile fault tolerance techniques. The authors provide a systematic comparison of various fault tolerance strategies by theoretical formulas, as well as real-world experiments. This paper also presents the optimal fault tolerance strategy selection algorithm, which employs both the QoS performance of Web services and the requirements of service users for selecting optimal fault tolerance strategy. A prototype is implemented and real-world experiments are conducted to illustrate the advantages of the evaluation framework. In these experiments, users from six different locations perform evaluation of Web services distributed in six countries, where over 1,000,000 test cases are executed in a collaborative manner to demonstrate the effectiveness of this approach.

Robot Planning in the Real World: Research Challenges and Opportunities

AI Magazine ◽  
2016 ◽  
Vol 37 (2) ◽  
pp. 76-84 ◽  
Author(s):  
Ron Alterovitz ◽  
Sven Koenig ◽  
Maxim Likhachev
Keyword(s):  
Technical Progress ◽  
Real World ◽  
National Science Foundation ◽  
Future Research ◽  
The Real ◽  
Research Challenges ◽  
Challenging Tasks ◽  
National Science ◽  
Simple Rules ◽  
Challenges And Opportunities

Recent years have seen significant technical progress on robot planning, enabling robots to compute actions and motions to accomplish challenging tasks involving driving, flying, walking, or manipulating objects. However, robots that have been commercially deployed in the real world typically have no or minimal planning capability. These robots are often manually programmed, teleoperated, or programmed to follow simple rules. Although these robots are highly successful in their respective niches, a lack of planning capabilities limits the range of tasks for which currently deployed robots can be used. In this article, we highlight key conclusions from a workshop sponsored by the National Science Foundation in October 2013 that summarize opportunities and key challenges in robot planning and include challenge problems identified in the workshop that can help guide future research towards making robot planning more deployable in the real world.

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