Deep Reinforcement Learning-Based Task Offloading and Service Migrating Policies in Service Caching-Assisted Mobile Edge Computing

Emerging mobile edge computing(MEC)is considered a feasible solution for offloading the computation-intensive request tasks generated from mobile wireless equipment(MWE)with limited computational resources and energy.Due to the homogeneity of request tasks from one MWE during a longterm time period,it is vital to predeploy the particular service cachings required by the request tasks at the MEC server.In this paper,we model a service caching-assisted MEC framework that takes into account the constraint on the number of service cachings hosted by each edge server and the migration of request tasks from the current edge server to another edge server with service caching required by tasks.Furthermore,we propose a multiagent deep reinforcement learning-based computation offloading and task migrating decision-making scheme(MBOMS)to minimize the long-term average weighted cost.The proposed MBOMS can learn the near-optimal offloading and migrating decision-making policy by centralized training and decentralized execution.Systematic and comprehensive simulation results reveal that our proposed MBOMS can converge well after training and outperforms the other five baseline algorithms.

Quality of Service and Security on Cisco Network Devices, Coupled with the Development of a Mobile Application Prototype Software for Server Room Temperature Monitoring

In an era where digital technology is paramount, higher education institutions like the University of Zambia (UNZA) are employing advanced computer networks to enhance their operational capacity and offer cutting-edge services to their academic fraternity. Spanning across the Great East Road campus, UNZA has established one of the most extensive computer networks in Zambia, serving a burgeoning community of over 20,000 active users through a Metropolitan Area Network (MAN). However, as the digital landscape continues to evolve, it is besieged with burgeoning challenges that threaten the very fabric of network integrity—cyber security threats and the imperatives of maintaining high Quality of Service (QoS). In an effort to mitigate these threats and ensure network efficiency, the development of a mobile application to monitor temperatures in the server room was imperative. According to L. Wei, X. Zeng, and T. Shen, the use of wireless sensory networks to monitor the temperature of train switchgear contact points represents a cost-effective solution. The system is based on wireless communication technology and is detailed in their paper, “A wireless solution for train switchgear contact temperature monitoring and alarming system based on wireless communication technology”, published in the International Journal of Communications, Network and System Sciences, vol. 8, no. 4, pp. 79-87, 2015 [1]. Therefore, in this study, a mobile application technology was explored for monitoring of temperatures in the server room in order to aid Cisco device performance. Additionally, this paper also explores the hardening of Cisco device security and QoS which are the cornerstones of this study.

Edge Cloud Selection in Mobile Edge Computing(MEC)-Aided Applications for Industrial Internet of Things(IIoT)Services

In many IIoT architectures,various devices connect to the edge cloud via gateway systems.For data processing,numerous data are delivered to the edge cloud.Delivering data to an appropriate edge cloud is critical to improve IIoT service efficiency.There are two types of costs for this kind of IoT network:a communication cost and a computing cost.For service efficiency,the communication cost of data transmission should be minimized,and the computing cost in the edge cloud should be also minimized.Therefore,in this paper,the communication cost for data transmission is defined as the delay factor,and the computing cost in the edge cloud is defined as the waiting time of the computing intensity.The proposed method selects an edge cloud that minimizes the total cost of the communication and computing costs.That is,a device chooses a routing path to the selected edge cloud based on the costs.The proposed method controls the data flows in a mesh-structured network and appropriately distributes the data processing load.The performance of the proposed method is validated through extensive computer simulation.When the transition probability from good to bad is 0.3 and the transition probability from bad to good is 0.7 in wireless and edge cloud states,the proposed method reduced both the average delay and the service pause counts to about 25%of the existing method.

基于Web Services和Mobile SVG的移动数学查询系统的设计

文中从方便学习者使用异构移动终端进行数学公式及图形查询的角度出发,设计了一种基于Web Services四层架构的移动数学公式及图形查询系统。该系统的服务端使用J2EE开发,客户端使用J2ME开发,以支持学习者通过不同分辨率、不同操作系统的移动设备查询常用公式、函数及图形,另外,该系统还使用Mobile SVG技术生成矢量数学图形,并将Ajax、gzip等技术用于提升性能,能大大提升查询速度、节省移动客户端的有效存储空间。该系统的架构和所采用的技术克服了目前移动设备访问网络资源速度较慢、存储量较小、分辨率不同等各种影响学习效果的不利因素,因此能为学习者提供更好的移动数学学习支持,具有很好的应用价值。

Bolzano Traffic: An Example of Open ITS Deployment for Advanced Traveller Information Services

This paper aims to present the experience gathered in the Italian alpine city of Bolzano within the project“Bolzano Traffic”whose goal is the introduction of an experimental open ITS platform for local service providers,fostering the diffusion of advanced traveller information services and the future deployment of cooperative mobility systems in the region.Several end-users applications targeted to the needs of different user groups have been developed in collaboration with local companies and research centers;a partnership with the EU Co-Cities project has been activated as well.The implemented services rely on real-time travel and traffic information collected by urban traffic monitoring systems or published by local stakeholders(e.g.public transportation operators).An active involvement of end-users,who have recently started testing these demo applications for free,is actually on-going.

Auto-Scaling Framework for Enhancing the Quality of Service in the Mobile Cloud Environments

On-demand availability and resource elasticity features of Cloud computing have attracted the focus of various research domains.Mobile cloud computing is one of these domains where complex computation tasks are offloaded to the cloud resources to augment mobile devices’cognitive capacity.However,the flexible provisioning of cloud resources is hindered by uncertain offloading workloads and significant setup time of cloud virtual machines(VMs).Furthermore,any delays at the cloud end would further aggravate the miseries of real-time tasks.To resolve these issues,this paper proposes an auto-scaling framework(ACF)that strives to maintain the quality of service(QoS)for the end users as per the service level agreement(SLA)negotiated assurance level for service availability.In addition,it also provides an innovative solution for dealing with the VM startup overheads without truncating the running tasks.Unlike the waiting cost and service cost tradeoff-based systems or threshold-rule-based systems,it does not require strict tuning in the waiting costs or in the threshold rules for enhancing the QoS.We explored the design space of the ACF system with the CloudSim simulator.The extensive sets of experiments demonstrate the effectiveness of the ACF system in terms of good reduction in energy dissipation at the mobile devices and improvement in the QoS.At the same time,the proposed ACF system also reduces the monetary costs of the service providers.

Research progress on the health status and community management service needs of mobile elderly people

The health status of the floating elderly population and the need of community management services are complex and important problems.Owing to the change of living environment and the insecure medical care,the mobile elderly people have more health and psy-chological problems compared to the rest of the elderly population.Therefore,the community should take a variety of measures to meet their needs and help them to better adapt to the new living environment,and maintain their physical and mental health.This paper aims to summarize recent studies on the physical and emotional health problems of mobile elderly people and related community management service needs.

移动计算中基于Mobile Agent的Web Services订阅调用模型

在分析了移动环境的特点以及传统J2ME应用程序Web Services调用的问题之后,针对传统移动环境下调用Web Ser-vices存在的问题,提出了基于Mobile Agent并结合订阅的Web Services调用模型,讨论了该模型的原理以及方法,提出了简单消息通信模式、代理服务器和订阅机制以及移动代理迁移策略。最后,结合该改进模型在中石化胜利油田中的实际应用,总结了它适用于移动环境的几个特点,比较了改进模型与传统模型调用Web Services的效率,表明了其正确性和适用性。

Empirical Analysis on Continuous Improvement of Mobile Content Services＇ Effects on Continuance Use Intention

With the development of intelligent terminals and mobile applications,the influence of continuous improvement on mobile content services to the continuance use intention is more and more significant.Based on the expectation-confirmation theory and information system continuance use theory,this paper proposes a mobile content continuance use model and puts forward related assumptions under the mobile commerce environment by introducing the continuous improvement variables.Questionnaire data are collected from 219 mobile content service users for research,and the hypothetical model is validated by the structural equation modeling.Results show that the information system continuance use model is still valid under the mobile commerce environment,and the continuous improvement on mobile content services have positive impacts on user's expectations after they have experienced certain mobile content services.

Location Based Services Acceptance and Adoption Evaluation: An Investigation on Mobile Phone Users’ Response to Awareness and Utilization of LBS Technology in Nairobi Kenya

Location Based Navigation System (LBNS) is a specific Location Based Service (LBS) purely for navigational purpose. These systems resolve position of a user by using GNSS/GPS positioning technologies, to which supplementary information on goods and services are tagged. The navigation services have become popular and can be installed on mobile phones to provide route information, location of points of interest and user’s current location. LBS has continued to face challenges which include “communication” process towards user reference. Location Based Service System conveys suitable information through a mobile device for effective decision making and reaction within a given time span. This research was geared at understanding the state of LBS technology acceptance and adoption by users in Nairobi Kenya. To do this a quantitative study was carried out through a questionnaire, to investigate mobile phone users’ response on awareness and use of LBS technology. Testing the growth of this technology in this region compared to predictions in previous studies using Technology Acceptance Model (TAM), it is evident that many users may be aware of GPS functionality in mobile phones but are certainly yet to fully embrace the technology as they rarely use it. This points to some underlying challenges towards this technology within this part of the World, thereby recommending for deliberate monitoring and evaluation of LBS technology for sustenance growth based on user satisfaction and acceptance for improved usability.

Technology Sub-diffusions:Consumptive Motivations for Mobile Phone Calls and Digital Services

Digital services interfaced with mobile phone lines are gradually being regarded as a core product in this modern age due to the high transmission speed of mobile technology.The research in this paper is based on the concept of product inter-dependence and actively explores the different consumptive motivations between the consumers' behavior of phone-call users and those who use digital services.This study also attempts to use a modifi ed diffusion model to estimate the consumers' collective behavior with a longitudinal approach.In this study,it can be inferred that psychological consumer motivations should dominate marketing policies.Thus,it was found that digital service users have more self-motivation and autonomy when adopting a new product because they have significantly higher innovative at-tributes than the segment of phone-call users.With these findings,we claim that we have discovered an unprec-edented concept for marketing managers who welcome the challenges of mobile digital services in the future.

Mobile Cloud for Personalized Any-Media Services

In this paper, we define mobile cloud computing and describe how it can be used for delivering advanced any-media services to both nomadic and mobile users. We focus on service delivery that is localized and personalized and suggest that virtualization and tighter cross-layer communication allows for convergence and seamless transition of services. These are also creating new and never-before seen ways of developing and delivering personalized any-media services. We discuss current paradigms for implementing cloud-based any-media services that generate revenue. Future research topics and requirements for evolving network and service elements are also discussed.

Development of a Smart Technique for Mobile Web Services Discovery

Web service(WS)presents a good solution to the interoperability of different types of systems that aims to reduce the overhead of high processing in a resource-limited environment.With the increasing demand for mobile WS(MWS),the WS discovery process has become a significant challenging point in the WS lifecycle that aims to identify the relevant MWSs that best match the service requests.This discovery process is a resource-consuming task that cannot be performed efficiently in a mobile computing environment due to the limitations of mobile devices.Meanwhile,a cloud computing can provide rich computing resources for mobile environments given its unlimited and easily scalable resources.This paper proposes a semantic WS discovery and invocation framework in mobile environments based on cloud and a relationship-aware matchmaking algorithm.The discovery algorithm enriches MWS and user requests semantically with the functional and non-functional properties of Ontology Web Language for Services,such as Quality of Web Service,device context,and user preferences.The WS repository is filtered based on logical reasoning and a parameter-based matching algorithm to minimize the matching space and improve runtime performance.The cosine similarity between the user request and services repository is then assessed to generate the most relevant WS.The relationships among concepts in the ontology are considered to improve the recall and precision ratio.After the WS discovery process,users can invoke and test these services in a mobile environment through a dynamic user interface.The interface of the invocation process is changed according to the WS description document.An application prototype is also developed to evaluate the framework based on a Cordova cross-mobile development framework.

Design and Implementation of Mobile ServicesEvaluation System

With the development of mobile network technology, mobile Web services have also been more and more attention, but standard Web protocols are not applicable in a mobile environment, so people began to design more efficient, compact and consume less mobile Web services protocol. In the course of research services protocol, a convenient and practical evaluation system will undoubtedly bring great help for the protocol, the paper design of mobile service evaluation system using a graphical way to display a variety of mobile services in the overhead data, system design a lightweight service protocol, and the protocol by the system for evaluation compared with a standard Web.

Scheduling Mobile Data Services in a Bluetooth

Public buses play an important role in public transportation in most parts of the world and it is still the dominant public transportation mode in some regions. Nowadays, as people switch to a mobile lifestyle, they spend significant amount of time on the traveling to work, back and forth. However, not much research has been done on how to provide some on-board service for those commuters in the public bus. This paper presents a Bluetooth-based system which is inexpensive, yet flexible, and scalable to serve commuters in a personalized manner using Bluetooth enabled mobile phones. However, from the Bluetooth specification, one Bluetooth dongle can connect to at most seven other Bluetooth devices. As we expect more than 7 users to use the services provided in the Bluetooth-based system (a full double-deck bus can carry around 100 passengers), we need to work out an effective scheduler to schedule all the private services on the Bluetooth servers in the bus. This paper also describes a scheduling algorithm that exploits the park mode feature of the Bluetooth specification to allow more users to have access to the Bluetooth services on the bus.

Predicting End-User Adoption to Mobile Services

It is no doubt that the sub-field of Artificial Intelligence, which uses the tenets of Machine learning and data mining has progressively gained popularity in the past years to become one of fundamental yet revolutionary technologies. It is the basis of systems that can learn and improve using algorithms and big data with minimal programming or none. It is envisaged that mobile computing will empower end-users to seamlessly access and consume digital content services regardless of spatial or temporal orientations. Such are already the features of smart phones that at production are bundled with trending and necessary services. Of the many capabilities that advancement in technology have actualized in smart devices, gaming, video streaming, online library access, and m-commerce access services are the commonly among smart device owners. Given the near-exponential growth in ownership of smart devices, there is a need to identify and prioritize mobile services, and such was focus of this study. In specific, the study used Decision Tree, a popular machine learning algorithm, to predict the adoption of mobile services among smart device owners. Besides this purpose, the study identified the core uses of smart phones, and data used in the study was from an open source and was retrieved from Pew Research Centre Internet and Technology website. The dataset had 140 variables and 2001 themes, from which only the key attributes were selected for analysis. The study established that the level of education was the significant predictor of the mobile phones usage while race of the user emerged as the least predictor of smart device usage. The findings indicated that smart mobile phones were mostly used for entertainment, getting locations, direction and for recommendation purposes.

Services and Applications Based on Mobile User’s Location Detection and Prediction

Many wireless applications are deployed and available to customers via their mobile phones. Variety of these applications and services are based on determination of the current or future location of mobile user. Location based services (LBS) are one of the vital applications which are subdivided into two main categories: economical category and public category. Economic applications include mobile marketing, entertainment and tracking applications. Whereas, emergency cases, safety, traffic management, Muslims’ applications and public information applications are sort of public applications. The first part of the paper presents a new proposed system with developed procedure to recreate public and economic applications with high positioning accuracy and good authentication of users’ data. The developed system is created to enhance both location based services and network allocation resources within mobile network platform using either normal or GPS supported mobile equipment. The second part of the paper introduces future location prediction of mobile user dependent applications. New algorithm is developed depending on utilizing both intra-cell Movement Pattern algorithm (ICMP) [1] and hybrid uplink time Difference of Arrival and Assisted GPS technique (UTDOA_AGPS) [2]. It has been noticed that ICMP algorithm outperforms other future location prediction algorithms with high precision and within suitable time (less than 220) msec. However, UTDOA_AGPS guarantees high precession of mobile user independent of the surrounding environment. The proposed technique is used to enhance reliability and efficiency of location based services using cellular network platform.

H.264/AVC error resilience tools suitable for 3G mobile video services

The emergence of third generation mobile system (3G) makes video transmission in wireless environment possible, and the latest 3GPP/3GPP2 standards require 3G terminals support H.264/AVC. Due to high packet loss rate in wireless envi- ronment, error resilience for 3G terminals is necessary. Moreover, because of the hardware restrictions, 3G mobile terminals support only part of H.264/AVC error resilience tool. This paper analyzes various error resilience tools and their functions, and presents 2 error resilience strategies for 3G mobile streaming video services and mobile conversational services. Performances of the proposed error resilience strategies were tested using off-line common test conditions. Experiments showed that the proposed error resilience strategies can yield reasonably satisfactory results.

Global Development of Mobile Value Added Services

With the increasing demand for VAS from the subscribers, mobile operators are making efforts to create more services to promote the continuous development of the non-voice service application. The following three mobile VASes are becoming the development focus of operators.

Consumer Risk Perceptions in Mobile Health Services Adoption: Do They Matter?

The purpose of this study is to investigate empirically the role of consumer perceived risks in the adoption of mobile health services. A theoretical model including the perceived risk associated with the activity targeted by a mobile health service and the perceived risk associated with the mobile service itself was developed and tested empirically in the context of an application supporting smoking cessation. The model was validated in a cross-sectional experiment conducted with 422 consumers in the UK and Canada. Findings show that while risk triggered by the nature of a health promotion activity is a strong driver of the adoption of the supporting mobile health service, risk related to the actual application targeting that activity is a comparatively weaker obstacle. The two contrasting risk perspectives are highly significant as they together explain over 31% of the variance in consumer intention to use the mobile health service, independently from other adoption factors. Overall, this study demonstrates that consumer risk perceptions alone are a multifaceted and meaningful component in mobile health services adoption, and that this element should not be overlooked in more complex research models.