Interactive Context-Aware Services for Mobile Devices

2016 ◽  
pp. 109-152
Keyword(s):  
Mobile Devices ◽  
Context Aware

scholarly journals Flexible computation offloading in a fuzzy-based mobile edge orchestrator for IoT applications

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
VanDung Nguyen ◽  
Tran Trong Khanh ◽  
Tri D. T. Nguyen ◽  
Choong Seon Hong ◽  
Eui-Nam Huh
Keyword(s):  
Cloud Computing ◽  
Augmented Reality ◽  
Mobile Devices ◽  
Computing System ◽  
Mobile User ◽  
Computation Offloading ◽  
Context Aware ◽  
Computing Systems ◽  
Iot Applications ◽  
Service Times

AbstractIn the Internet of Things (IoT) era, the capacity-limited Internet and uncontrollable service delays for various new applications, such as video streaming analysis and augmented reality, are challenges. Cloud computing systems, also known as a solution that offloads energy-consuming computation of IoT applications to a cloud server, cannot meet the delay-sensitive and context-aware service requirements. To address this issue, an edge computing system provides timely and context-aware services by bringing the computations and storage closer to the user. The dynamic flow of requests that can be efficiently processed is a significant challenge for edge and cloud computing systems. To improve the performance of IoT systems, the mobile edge orchestrator (MEO), which is an application placement controller, was designed by integrating end mobile devices with edge and cloud computing systems. In this paper, we propose a flexible computation offloading method in a fuzzy-based MEO for IoT applications in order to improve the efficiency in computational resource management. Considering the network, computation resources, and task requirements, a fuzzy-based MEO allows edge workload orchestration actions to decide whether to offload a mobile user to local edge, neighboring edge, or cloud servers. Additionally, increasing packet sizes will affect the failed-task ratio when the number of mobile devices increases. To reduce failed tasks because of transmission collisions and to improve service times for time-critical tasks, we define a new input crisp value, and a new output decision for a fuzzy-based MEO. Using the EdgeCloudSim simulator, we evaluate our proposal with four benchmark algorithms in augmented reality, healthcare, compute-intensive, and infotainment applications. Simulation results show that our proposal provides better results in terms of WLAN delay, service times, the number of failed tasks, and VM utilization.

scholarly journals Context-Aware Community Construction in Proximity-Based Mobile Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-18 ◽  
Author(s):  
Na Yu ◽  
Qi Han
Keyword(s):  
Social Networking ◽  
Mobile Devices ◽  
Mobile Networks ◽  
Context Aware ◽  
Two Phase ◽  
Space And Time ◽  
Shared Information ◽  
Influence Graph ◽  
Social Applications ◽  
Share Information

Sensor-equipped mobile devices have allowed users to participate in various social networking services. We focus on proximity-based mobile social networking environments where users can share information obtained from different places via their mobile devices when they are in proximity. Since people are more likely to share information if they can benefit from the sharing or if they think the information is of interest to others, there might exist community structures where users who share information more often are grouped together. Communities in proximity-based mobile networks represent social groups where connections are built when people are in proximity. We consider information influence (i.e., specify who shares information with whom) as the connection and the space and time related to the shared information as the contexts. To model the potential information influences, we construct an influence graph by integrating the space and time contexts into the proximity-based contacts of mobile users. Further, we propose a two-phase strategy to detect and track context-aware communities based on the influence graph and show how the context-aware community structure improves the performance of two types of mobile social applications.

A User Context-Aware Advertising Framework for the Mobile Web

2010 ◽  
pp. 1-15
Author(s):  
Nan Jing ◽  
Yong Yao ◽  
Yanbo Ru
Keyword(s):  
Mobile Devices ◽  
Online Advertising ◽  
User Interaction ◽  
Context Aware ◽  
Mobile Platforms ◽  
Social Community ◽  
Mobile Web ◽  
Web Technologies ◽  
Critical Components ◽  
Advertising Content

Context-aware advertising is one of the most critical components in the Internet ecosystem today because most WWW publisher’s revenue highly depends on the relevance of the displayed advertisement to the context of the user interaction. Existing research works in context-aware advertising mainly focus on analyzing either the content of the web page (in which it is also called contextual advertising), or the keywords of the user search. However, we have identified the limitations of these works when being extended into mobile web, which has become a major platform for users to access Internet with thanks to the new lightweight web technologies and the development of mobile devices. These mobile devices are equipped with networking capabilities and sensors that provide versatile contexts including physical environment, user internal and social community. These contexts, which are far beyond just page content and search keywords, should be well organized and utilized for online advertising to gain better user experience and reaction. In this chapter, we point out the aforementioned limitations of the existing works in context-aware advertising when being applied for mobile platforms. We also discuss the characteristics of the contexts that are available on mobile devices and clearly describe the challenges of utilizing these contexts to optimize the advertisement on mobile platforms. We then present a context-aware advertising framework that collects and integrates the user contexts to select, generate, and present advertising content. The purpose of this framework is to provide the mobile users with targeted and purposeful advertisement. Finally, we discuss the implementation aspects and one specific application of this framework and outline our future plans.

Mobile Spatial Interaction and Mediated Social Navigation

2011 ◽  
pp. 2604-2608
Author(s):  
Mark Bilandzic ◽  
Marcus Foth
Keyword(s):  
Web 2.0 ◽  
Mobile Devices ◽  
Mobile Networks ◽  
Spatial Interaction ◽  
Value Added ◽  
Handheld Devices ◽  
Context Aware ◽  
Social Navigation ◽  
Global Positioning ◽  
Community Platforms

The increasing ubiquity of location and context-aware mobile devices and applications, geographic information systems (GIS) and sophisticated 3D representations of the physical world accessible by lay users is enabling more people to use and manipulate information relevant to their current surroundings (Scharl & Tochtermann, 2007). The relationship between users, their current geographic location and their devices are summarised by the term “mobile spatial interaction” (MSI), and stands for the emerging opportunities and affordances that location sensitive and Internet capable devices provide to its users. The first major academic event which coined the term in its current usage was a workshop on MSI (see http://msi.ftw.at/) at the CHI 2007 (Fröhlich et al., 2007). Mobile spatial interaction is grounded in a number of technologies that recently started to converge. First, the development of mobile networks and mobile Internet technologies enables people to request and exchange specific information from anywhere at anytime. Using their handheld devices people can, for example, check the latest news, request recent stock exchange values or communicate via mobile instant messaging. The second enabler is global positioning technology. Mobile devices with integrated Global Positioning System (GPS) receivers—soon to be joined by the Russian Global Navigation Satellite System (GLONASS) and the European Galileo system—are aware of their current latitude and longitude coordinates and can use this data as value added information for context-aware services, that is, mobile applications that refer to information relevant to the current location of the user. A possible use scenario for such an information request would be, for example, “find all clubs and pubs in a radius of 500 meters from my current position.” The focus of this work is to enrich the opportunities given by such location aware services with selected Web 2.0 design paradigms (Beer & Burrows, 2007; Kolbitsch & Maurer, 2006) toward mobile social networking services that are bound to specific physical places. User participation, folksonomy and geotagging are three design methods that have become popular in Web 2.0 community-platforms and proven to be effective information management tools for various domains (Casey & Savastinuk, 2007; Courtney, 2007; Macgregor & McCulloch, 2006). Applying such a design approach for a mobile information system creates a new experience of collaboration between mobile users, a step toward what Jaokar refers to as the Mobile Web 2.0 (Jaokar & Fish, 2006), that is, a chance for mediated social navigation in physical spaces.

Context-Awareness and Mobile Devices

2008 ◽  
pp. 205-217 ◽  
Author(s):  
Anind K. Dey ◽  
Jonna Häkkilä
Keyword(s):  
Human Computer Interaction ◽  
Mobile Computing ◽  
Ubiquitous Computing ◽  
Mobile Devices ◽  
Context Awareness ◽  
Design Guidelines ◽  
Context Aware ◽  
Definition Of ◽  
Mobile Context ◽  
Computer Interaction

Context-awareness is a maturing area within the field of ubiquitous computing. It is particularly relevant to the growing sub-field of mobile computing as a user’s context changes more rapidly when a user is mobile, and interacts with more devices and people in a greater number of locations. In this chapter, we present a definition of context and context-awareness and describe its importance to human-computer interaction and mobile computing. We describe some of the difficulties in building context-aware applications and the solutions that have arisen to address these. Despite these solutions, users have difficulties in using and adopting mobile context-aware applications. We discuss these difficulties and present a set of eight design guidelines that can aid application designers in producing more usable and useful mobile context-aware applications.

Session and Network Support for Autonomous Context-Aware Multiparty Communications in Heterogeneous Mobile Systems

2010 ◽  
Vol 1 (4) ◽  
pp. 1-24 ◽  
Author(s):  
Josephina Antoniou ◽  
Christophoros Christophorou ◽  
Augusto Neto ◽  
Susana Sargento ◽  
Filipe Pinto ◽  
...  
Keyword(s):  
Mobile Devices ◽  
Performance Optimization ◽  
Network Performance ◽  
Future Internet ◽  
Mobile Systems ◽  
Context Aware ◽  
Network Support ◽  
Different Types ◽  
Optimization Schemes ◽  
Service Groups

The increase of networking complexity requires the design of new performance optimization schemes for delivering different types of sessions to users under different conditions. In this regard, special attention is given to multi-homed environments, where mobile devices cross areas with overlapping access technologies (Wi-Fi, 3G, WiMax). In such a scenario, efficient multiparty delivery depends upon the grouping operation, which must be done based on several parameters. In this paper, the authors propose context-aware sub-grouping of content-based service groups so that the same service session can be delivered using different codings of the same content, adapting to current network, users, session, and environment context. The context-aware information is used to improve the sub-grouping process. This paper aims to describe these sub-grouping techniques, and in particular how they improve network performance and user experience in the future Internet by focusing on the improved network-level and session-level mechanisms.

Context-Awareness and Mobile Devices

2009 ◽  
pp. 3222-3235 ◽  
Author(s):  
Anind K. Dey ◽  
Jonna Häkkilä
Keyword(s):  
Human Computer Interaction ◽  
Mobile Computing ◽  
Ubiquitous Computing ◽  
Mobile Devices ◽  
Context Awareness ◽  
Design Guidelines ◽  
Context Aware ◽  
Definition Of ◽  
Mobile Context ◽  
Computer Interaction

Context-awareness is a maturing area within the field of ubiquitous computing. It is particularly relevant to the growing sub-field of mobile computing as a user’s context changes more rapidly when a user is mobile, and interacts with more devices and people in a greater number of locations. In this chapter, we present a definition of context and context-awareness and describe its importance to human-computer interaction and mobile computing. We describe some of the dif- ficulties in building context-aware applications and the solutions that have arisen to address these. Despite these solutions, users have difficulties in using and adopting mobile context-aware applications. We discuss these difficulties and present a set of eight design guidelines that can aid application designers in producing more usable and useful mobile context-aware applications.

Context-Aware Recommender System for Location-Based Advertising

2011 ◽  
Vol 467-469 ◽  
pp. 2091-2096 ◽  
Author(s):  
Hyun Chul Ahn ◽  
Kyoung Jae Kim
Keyword(s):  
Mobile Devices ◽  
Recommender System ◽  
Service Industries ◽  
Classification Rule ◽  
Mobile Service ◽  
Context Aware ◽  
Good Market ◽  
Proposed Model ◽  
Market Opportunities ◽  
Marketing Tool

Demand for context-aware systems continues to grow due to the diffusion of mobile devices. This trend may represent good market opportunities for mobile service industries. Thus, context-aware or location-based advertising (LBA) has been an interesting marketing tool for many companies. However, some studies reported that the performance of context-aware marketing or advertising has been quite disappointing. In this study, we propose a novel context-aware recommender system for LBA. Our proposed model is designed to apply a modified collaborative filtering (CF) algorithm with regard to the several dimensions for the personalization of mobile devices – location, time and the user’s needs type. In particular, we employ a classification rule to understand user’s needs type using a decision tree algorithm. We empirically validated the effectiveness of the proposed model by using a real-world dataset. Experimental results show that our model makes more accurate and satisfactory advertisements than comparative systems.

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