Towards Real-Time Context Awareness for Mobile Users: A Declarative Meta-Programming Approach

2010 ◽  
pp. 89-112
Author(s):  
Seng W. Loke
Keyword(s):  
Real Time ◽  
Context Awareness ◽  
Mobile Users ◽  
Programming Approach ◽  
Meta Programming

Context Awareness on Mobile Devices

2015 ◽  
Vol 743 ◽  
pp. 742-747 ◽  
Author(s):  
Z.A. Pan ◽  
J.X. Zhu
Keyword(s):  
Real Time ◽  
Mobile Devices ◽  
Context Awareness ◽  
Mobile Users ◽  
Context Aware ◽  
Context Aware Computing ◽  
Bayes Net ◽  
Real Time Classification

Context aware computing is important for applications to provide smarter and safer<br />service to mobile users, especially when users’ context changing rapidly or regularly. In this paper,<br />we propose a context aware model for mobile devices based on audio and location. The information<br />can easily obtained from sensors, e.g., microphones and GPS. Thus, exploiting the MFCC features<br />and the location, a Bayes Net is trained and built and will be used for context classifying in the<br />real-time classification. The results of experiments implemented on Android 4.0 platform<br />demonstrate promising performance, which indicates that the model is able to support real<br />applications.

scholarly journals Energy Saving Schemes for Scalable Mobile Computing Networks

2021 ◽  
Author(s):  
Ali Alnoman
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
User Satisfaction ◽  
Virtual Machines ◽  
Base Station ◽  
Data Rate ◽  
Mobile Users ◽  
Task Completion ◽  
Programming Approach ◽  
Network Scalability

With the growing popularity of smart applications that contain computing-intensive tasks, the provision of radio and computing resources with high quality is becoming more and more challenging. Moreover, supporting network scalability is crucial to accommodate the massive numbers of connected devices. In this thesis, we present effective energy saving strategies that consider the utilization of network elements such as base stations and virtual machines, and implement on/off mechanisms taking into account the quality of service (QoS) required by mobile users. Moreover, we investigate the performance of a NOMA-based resource allocation scheme in the context of Internet of Things aiming to improve network scalability and reduce the energy consumption of mobile users. The system model is mainly built upon the M/M/k queueing system that has been widely used in most relevant works. First, the energy saving mechanism is formulated as a 0-1 knapsack problem where the weight and value of each small base station is determined by the utilization and proportion of computing tasks at that base station, respectively. The problem is then solved using the dynamic programming approach which showed significant energy saving performance while maintaining the cloud response time at desired levels. Afterwards, the energy saving mechanism is applied on edge computing to reduce the amount of under-utilized virtual machines in edge devices. Herein, the square-root staffing rule and the Halfin-Whitt function are used to determine the minimum number of virtual machines required to maintain the queueing probability below a threshold value. On the user level, reducing energy consumption can be achieved by maximizing data rate provision to reduce the task completion time, and hence, the transmission energy. Herein, a NOMA-based scheme is introduced, particularly, the sparse code multiple access (SCMA) technique that allows subcarriers to be shared by multiple users. Not only does SCMA help provide higher data rates but also increase the number of accommodated users. In this context, a power optimization and codebook allocation problems are formulated and solved using the water-filling and heuristic approaches, respectively. Results show that SCMA can significantly improve data rate provision and accommodate more mobile users with improved user satisfaction.

Service Discovery Framework for Distributed Embedded Real-Time Systems

2014 ◽  
pp. 126-147 ◽  
Author(s):  
Furkh Zeshan ◽  
Radziah Mohamad ◽  
Mohammad Nazir Ahmad
Keyword(s):  
Web Services ◽  
Real Time ◽  
Context Awareness ◽  
Service Discovery ◽  
Low Cost ◽  
High Volume ◽  
Heterogeneous Environments ◽  
Real Time Systems ◽  
Loosely Coupled ◽  
Time Systems

Embedded systems are supporting the trend of moving away from centralised, high-cost products towards low-cost and high-volume products; yet, the non-functional constraints and the device heterogeneity can lead to system complexity. In this regard, Service-Oriented Architecture (SOA) is the best methodology for developing a loosely coupled, dynamic, flexible, distributed, and cost-effective application. SOA relies heavily on services, and the Semantic Web, as the advanced form of the Web, handles the application complexity and heterogeneity with the help of ontology. With an ever-increasing number of similar Web services in UDDI, a functional description of Web services is not sufficient for the discovery process. It is also difficult to rank the similar services based on their functionality. Therefore, the Quality of Service (QoS) description of Web services plays an important role in ranking services within many similar functional services. Context-awareness has been widely studied in embedded and real-time systems and can also play an important role in service ranking as an additional set of criteria. In addition, it can enhance human-computer interaction with the help of ontologies in distributed and heterogeneous environments. In order to address the issues involved in ranking similar services based on the QoS and context-awareness, the authors propose a service discovery framework for distributed embedded real-time systems in this chapter. The proposed framework considers user priorities, QoS, and the context-awareness to enable the user to select the best service among many functional similar services.

IoT-based real time intelligent routing for emergent crowd evacuation

2019 ◽  
Vol 37 (3) ◽  
pp. 604-624
Author(s):  
Yanlan Mei ◽  
Ping Gui ◽  
Xianfeng Luo ◽  
Benbu Liang ◽  
Liuliu Fu ◽  
...  
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Programming Model ◽  
Emergency Evacuation ◽  
Guidance System ◽  
Programming Approach ◽  
Metro Station ◽  
Content Type ◽  
Crowd Evacuation ◽  
Evacuation Route

Purpose The purpose of this paper is to take advantage of Internet of Things (IoT) for intelligent route programming of crowd emergency evacuation in metro station. It is a novel approach to ensure the crowd safety and reduce the casualties in the emergency context. An evacuation route programming model is constructed to select a suitable evacuation route and support the emergency decision maker of metro station. Design/methodology/approach The IoT technology is employed to collect and screen information, and to construct an expert decision model to support the metro station manager to make decision. As a feasible way to solve the multiple criteria decision-making problem, an improved multi-attributive border approximation area comparison (MABAC) approach is introduced. Findings The case study indicates that the model provides valuable suggestions for evacuation route programming and offers practical support for the design of an evacuation route guidance system. Moreover, IoT plays an important role in the process of intelligent route programming of crowd emergency evacuation in metro station. A library has similar structure and crowd characteristics of a metro station, thus the intelligent route programming approach can be applied to the library crowd evacuation. Originality/value The highlights of this paper are listed as followings: the accuracy and accessibility of the metro station’s real-time information are improved by integrating IoT technology with the intelligent route programming of crowd emergency evacuation. An improved MABAC approach is introduced to the expert support model. It promotes the applicability and reliability of decision making for emergency evacuation route selection in metro station. It is a novel way to combine the decision-making methods with practice.

scholarly journals ZONE-Based Multi-Access Edge Computing Scheme for User Device Mobility Management

2019 ◽  
Vol 9 (11) ◽  
pp. 2308 ◽  
Author(s):  
Juyong Lee ◽  
Daeyoub Kim ◽  
Jihoon Lee
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Mobility Management ◽  
Mobile Network ◽  
Edge Computing ◽  
Mobile Users ◽  
Long Distance ◽  
Cloud Server ◽  
Multi Access ◽  
User Device

Recently, new mobile applications and services have appeared thanks to the rapid development of mobile devices and mobile network technology. Cloud computing has played an important role over the past decades, providing powerful computing capabilities and high-capacity storage space to efficiently deliver these mobile services to mobile users. Nevertheless, existing cloud computing delegates computing to a cloud server located at a relatively long distance, resulting in significant delays due to additional time to return processing results from a cloud server. These unnecessary delays are inconvenient for mobile users because they are not suitable for applications that require a real-time service environment. To cope with these problems, a new computing concept called Multi-Access Edge Computing (MEC) has emerged. Instead of sending all requests to the central cloud to handle mobile users’ requests, the MEC brings computing power and storage resources to the edge of the mobile network. It enables the mobile user device to run the real-time applications that are sensitive to latency to meet the strict requirements. However, there is a lack of research on the efficient utilization of computing resources and mobility support when mobile users move in the MEC environment. In this paper, we propose the MEC-based mobility management scheme that arranges MEC server (MECS) as the concept of Zone so that mobile users can continue to receive content and use server resources efficiently even when they move. The results show that the proposed scheme reduce the average service delay compared to the existing MEC scheme. In addition, the proposed scheme outperforms the existing MEC scheme because mobile users can continuously receive services, even when they move frequently.

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