Research on Mobile Internet Mobile Agent System Dynamic Trust Model for Cloud Computing

This paper analyzes the reasons for the formation of security problems in mobile agent systems, and analyzes and compares the security mechanisms and security technologies of existing mobile agent systems from the perspective of blocking attacks. On this basis, the host protection mobile agent protection technology is selected, and a method to enhance the security protection of mobile agents (referred to as IEOP method) is proposed. The method first encrypts the mobile agent code using the encryption function, and then encapsulates the encrypted mobile agent with the improved EOP protocol IEOP, and then traces the suspicious execution result. Experiments show that using this method can block most malicious attacks on mobile agents, and can protect the integrity and confidentiality of mobile agents, but the increment of mobile agent tour time is not large.

A Novel Load Balancing Strategy of Software-Defined Cloud/Fog Networking in the Internet of Vehicles

The Internet of Vehicles(IoV)has been widely researched in recent years,and cloud computing has been one of the key technologies in the IoV.Although cloud computing provides high performance compute,storage and networking services,the IoV still suffers with high processing latency,less mobility support and location awareness.In this paper,we integrate fog computing and software defined networking(SDN) to address those problems.Fog computing extends computing and storing to the edge of the network,which could decrease latency remarkably in addition to enable mobility support and location awareness.Meanwhile,SDN provides flexible centralized control and global knowledge to the network.In order to apply the software defined cloud/fog networking(SDCFN) architecture in the IoV effectively,we propose a novel SDN-based modified constrained optimization particle swarm optimization(MPSO-CO) algorithm which uses the reverse of the flight of mutation particles and linear decrease inertia weight to enhance the performance of constrained optimization particle swarm optimization(PSO-CO).The simulation results indicate that the SDN-based MPSO-CO algorithm could effectively decrease the latency and improve the quality of service(QoS) in the SDCFN architecture.

Cloud-Processing Platform for Traffic Flow Based on Internet of Car

Internet of Car, resulting from the Internet of Things, is a key point for the forthcoming smart city. In this article, GPS technology, 3G wireless technology and cloud-processing technology are employed to construct a cloud-processing network platform based on the Internet of Car. By this platform, positions and velocity of the running cars, information of traffic flow from fixed monitoring points and transportation videos are combined to be a virtual traffic flow data platform, which is a parallel system with real traffic flow and is able to supply basic data for analysis and decision of intelligent transportation system.

Internet of Things Cloud Framework for Smart Homes

Smart appliances and renewable energy resources are becoming an integral part of smart homes. Nowadays, home appliances are communicating with each other with home short-range home area gateways, using existing network communication protocols such as ZigBee, Bluetooth, RFID, and WiFi. A Gateway allows homeowners and utilities to communicate remotely with the appliances via long-range communication networks such as GPRS, WiMax, LTE, and power liner carrier. This paper utilizes the Internet of Things （IoT） concepts to monitor and control home appliances. Moreover, this paper proposes a framework that enables the integration and the coordination of Human-to-Appliance, Utility-to- Appliance, and Appliance-to-Appliance. Utilizing the concepts of Internet of Things leads to one standard communication protocols, TCP/IPV6, which overcomes the many diverse home area networks and neighborhood area networks protocols. This work proposes a cloud based framework that enables the IoTs integration and supports the coordination between devices, as well as with device-human interaction. A prototype is designed, implemented, and tested to validate the proposed solution.

Resource Load Prediction of Internet of Vehicles Mobile Cloud Computing

Load-time series data in mobile cloud computing of Internet of Vehicles(IoV)usually have linear and nonlinear composite characteristics.In order to accurately describe the dynamic change trend of such loads,this study designs a load prediction method by using the resource scheduling model for mobile cloud computing of IoV.Firstly,a chaotic analysis algorithm is implemented to process the load-time series,while some learning samples of load prediction are constructed.Secondly,a support vector machine(SVM)is used to establish a load prediction model,and an improved artificial bee colony(IABC)function is designed to enhance the learning ability of the SVM.Finally,a CloudSim simulation platform is created to select the perminute CPU load history data in the mobile cloud computing system,which is composed of 50 vehicles as the data set;and a comparison experiment is conducted by using a grey model,a back propagation neural network,a radial basis function(RBF)neural network and a RBF kernel function of SVM.As shown in the experimental results,the prediction accuracy of the method proposed in this study is significantly higher than other models,with a significantly reduced real-time prediction error for resource loading in mobile cloud environments.Compared with single-prediction models,the prediction method proposed can build up multidimensional time series in capturing complex load time series,fit and describe the load change trends,approximate the load time variability more precisely,and deliver strong generalization ability to load prediction models for mobile cloud computing resources.

Towards Attaining Reliable and Efficient Green Cloud Computing Using Micro-Smart Grids to Power Internet Data Center

Energy generation and consumption are the main aspects of social life due to the fact that modern people’s necessity for energy is a crucial ingredient for existence. Therefore, energy efficiency is regarded as the best economical approach to provide safer and affordable energy for both utilities and consumers, through the enhancement of energy security and reduction of energy emissions. One of the problems of cloud computing service providers is the high rise in the cost of energy, efficiency together with carbon emission with regards to the running of their internet data centres (IDCs). In order to mitigate these issues, smart micro-grid was found to be suitable in increasing the energy efficiency, sustainability together with the reliability of electrical services for the IDCs. Therefore, this paper presents idea on how smart micro-grids can bring down the disturbing cost of energy, carbon emission by the IDCs with some level of energy efficiency all in an effort to attain green cloud computing services from the service providers. In specific term, we aim at achieving green information and communication technology (ICT) in the field of cloud computing in relations to energy efficiency, cost-effectiveness and carbon emission reduction from cloud data center’s perspective.

Quantum-Edge Cloud Computing for IoT: Bridging the Gap between Cloud, Edge, and Quantum Technologies

The rapid expansion of the Internet of Things (IoT) has driven the need for advanced computational frameworks capable of handling the complex data processing and security challenges that modern IoT applications demand. However, traditional cloud computing frameworks face significant latency, scalability, and security issues. Quantum-Edge Cloud Computing (QECC) offers an innovative solution by integrating the computational power of quantum computing with the low-latency advantages of edge computing and the scalability of cloud computing resources. This study is grounded in an extensive literature review, performance improvements, and metrics data from Bangladesh, focusing on smart city infrastructure, healthcare monitoring, and the industrial IoT sector. The discussion covers vital elements, including integrating quantum cryptography to enhance data security, the critical role of edge computing in reducing response times, and cloud computing’s ability to support large-scale IoT networks with its extensive resources. Through case studies such as the application of quantum sensors in autonomous vehicles, the practical impact of QECC is demonstrated. Additionally, the paper outlines future research opportunities, including developing quantum-resistant encryption techniques and optimizing quantum algorithms for edge computing. The convergence of these technologies in QECC has the potential to overcome the current limitations of IoT frameworks, setting a new standard for future IoT applications.

基于Cloud Card的个人学习空间云架构

"互联网+"时代,信息技术与教育教学深度融合,泛在学习、翻转课堂、联通教育等颠覆性教育创新不断涌现。在此背景下,面向未来教育的个人学习空间建设需要面向个人、面向智慧、开放生态、连接一切。该文首先从学习生态圈和学习操控台两个视角对个人学习空间进行了全新解读,进而聚焦于Cloud Card技术支持下的个人学习空间建设,论述了两者结合的理论与技术基础,提出了云平台系统架构下构建个人学习空间的具体方案。云平台利用云计算技术,将资源、数据和服务汇聚到基础服务平台上进行统一规划与管理,并通过核心应用中心,围绕服务于个体的成长发展,从资源、活动、评价三个维度提供个性化、情境性、自适应的学习服务,最终以面向个体和公众的多样化终端加以呈现。研究最后对Cloud Card理念下个人学习空间中学习活动的设计与组织进行初步探索,提出了原子级学习活动和学习样式模板,为个人学习空间的建设提供了新的技术路线和实现方案,但后续仍需要从学习分析与挖掘实现、数据规范制定、学习样式模板设计等方面进行更加深入的研究。

基于云模型的Internet建模多属性评价方法

借鉴云模型的研究思想及复杂网络的研究成果,提出了基于评价云的Internet模型多属性评价方法.主要工作如下:分析了Internet的建模情况,针对模型的评价现状设计了基于云模型的评价方法,可针对网络多属性进行分别评价,并最终整合成一综合评价值,进而通过比较获得最佳的评价.云模型能够反映模糊性和随机性的关联,因此,该方法能够更加有效地表达语言定性评价信息.最后,通过应用案例证明了该方法的简单性和可行性.

iWork for iCloud云办公平台在高校教学中的应用实践

介绍了利用iWork for iCloud云办公平台在高校教学中构建教学环境的实践,讨论了iWork for iCloud的技术背景、教学应用的准备工作和具体实施方法,包括专用云办公教学平台的构建、课程传授以及课程信息分享和团队协作等。

Adaptive QoS Management for Mobile Cloud Services

The rapid growth of cloud computing and mobile Internet services has triggered the emergence of mobile cloud services. Among many challenges,QoS management is one of the crucial issues for mobile cloud services. However,existing works on QoS management for cloud computing can hardly fit well to the mobile environment. This paper presents a QoS management architecture and an adaptive management process that can predict,assess and ensure QoS of mobile cloud services. Furthermore,we propose an adaptive QoS management model based on Fuzzy Cognitive Maps ( FCM) ,which suitably represents the causal relationships among QoS related properties and cloud service modes. We evaluate the proposed solution and demonstrate its effectiveness and benefits based on simulation work.

Blockchain Platform for Industrial Internet of Things

Internet of Things (IoT) are being adopted for industrial and manufacturing applications such as manufacturing automation, remote machine diagnostics, prognostic health management of industrial machines and supply chain management. Cloud-Based Manufacturing is a recent on-demand model of manufacturing that is leveraging IoT technologies. While Cloud-Based Manufacturing enables on-demand access to manufacturing resources, a trusted intermediary is required for transactions between the users who wish to avail manufacturing services. We present a decentralized, peer-to-peer platform called BPIIoT for Industrial Internet of Things based on the Block chain technology. With the use of Blockchain technology, the BPIIoT platform enables peers in a decentralized, trustless, peer-to-peer network to interact with each other without the need for a trusted intermediary.

High-Performance Multipath Routing Algorithm Using CPEGASIS Protocol in Wireless Sensor Cloud Environment

The current IT cloud computing is playing a vital role in most of the areas such as Education, Research, Health care, etc. The cloud computing technology involving in sensor networks embedded system and IOT (Internet of Things). At present scenario, the sensors collected the information from the particular environment, where the sensors are fixed and transfer the collected information to cloud storage, here the challenge is the data transmission i.e. data that traverse from sensor to cloud environment are the big issue and maximum number of data loss is very high especially in dynamic routing environment. If data loss is identified in any routing path then automatically the information will transfer to alternate routing path. In this paper, we introduce a new algorithm for automatic routing path selection that can be integrated with cloud technology. This algorithm supports when data loss is found in the particular path of a network, then it selects an alternate route to transfer the data. The proposed model is comparatively more efficient than the prior methodologies. The implementation of the proposed work is done on NS3 simulator, and the performance metric is analyzed.

Mobile-agent-based energy-efficient scheduling with dynamic channel acquisition in mobile cloud computing

Mobile cloud computing（MCC） combines mobile Internet and cloud computing to improve the performance of mobile applications. However, MCC faces the problem of energy efficiency because of randomly varying channels. A scheduling algorithm is proposed by introducing the Lyapunov optimization, which can dynamically choose users to transmit data based on queue backlog and channel statistics. The Lyapunov analysis shows that the proposed scheduling algorithm can make a tradeoff between queue backlog and energy consumption in the channel-aware mobile cloud computing system. The simulation results verify the effectiveness of the proposed algorithm.

Efficient Use of Cloud Computing in Medical Science

Technology has grown rapidly with scientific advancement over the world in recent decades. Therefore, there is a need to redesign the medical system to meet their better needs .With the advent of cloud computing the doctors can keep their information about their critical diseases, critical cases and sophisticated problem they phased .cloud computing has made it possible to solve many complex problems very fast and at a lower cost in less time. Almost all doctors in various disciplines uses cloud computing to solve their problems. In this paper, attention is given to possible implementation of Cloud computing technology in the medical field, especially in hospitals where there is intensive need of computers for better cure for the diseases.

基于OneNET云平台的智慧消防远程监控系统的设计

针对传统消防监控系统存在开发成本高、误警率高、实时监控不便的问题,提出一种基于物联网云平台的智慧消防远程监控系统。采用STM32单片机作为中枢控制芯片,经多传感器采集温度、湿度、烟雾、火焰等环境数据,通过窄带物联网(NB-IoT,Narrow Band Internet of Things)上传至OneNET云平台。经数据分析后以可视化方式呈现,对异常数据触发报警实时响应。通过手机APP实现数据实时监测及一键处置。经测试,监控系统报警准确率高于97.2%,数据延迟低于50 ms,表明该系统能够实现消防火警的无线远程监控,并做出快速反应,满足中小微企业和普通家庭用户的消防监控需要。

Observing Network Performance and Congestion on Managing Assets with RFID and Cloud Computing

Today, we observe that more and more, radio frequency identification (RFID) technology has been used to identify and track objects in enterprises and institutions. In addition, we also perceive the growing adoption of cloud computing, either public or private, to process and store data from the objects. In this context, the literature does not present an initiative that looks into the network on enterprise-cloud interactions, so neglecting network performance and congestion information when transmitting data to the cloud. Thus, we are presenting a model named ACMA—Automatic Control and Management of Assets. ACMA employs context awareness to control and monitor corporate assets in companies with multiple units. ACMA provides a centralized point of access in the cloud in which interested actors can get online data about each corporate asset. In particular, our scientific contribution consists in considering network congestion to control dynamically the data updating interval from sensors to the cloud. The idea is to search for reliability and integrity of operations, without losing or corrupting data when updating the information to cloud. Thus, this article describes the ACMA model, its architecture, algorithms and features. In addition, we describe the evaluation methodology and the results obtained through experiments and simulations based on the developed prototype.

我国智慧林业关键技术研究进展

我国林业信息化已经进入智慧林业阶段,新一代信息技术在智慧林业建设中发挥着重要的作用。本文围绕智慧林业的内涵和发展路径,提出智慧林业建设体系架构,分析智慧林业中物联网、3S和北斗导航、云计算、大数据、移动互联网等关键技术的研究现状,剖析存在的主要问题,探讨未来发展趋势及研究重点。研究表明,我国智慧林业关键技术研究存在基础设施不完善、技术成本较高、技术标准不统一、信息互联互通不强、数据质量不稳定、数据挖掘不深、技术融合集成不足和专业技术人才匮乏等主要问题。研究认为,林业数据挖掘与深层应用、林业云遥感大数据研究、林业块数据研究以及林业物联网、云计算和移动互联网的深度融合是我国智慧林业关键技术未来的发展趋势和研究重点。

An Integrated Cloud-Based Wireless Sensor Network for Monitoring Industrial Wastewater Discharged into Water Sources

This paper presents a prototype of an Integrated Cloud-Based Wireless Sensor Network (WSN) developed to monitor pH, conductivity and dissolved oxygen parameters from wastewater discharged into water sources. To provide realtime online monitoring and Internet of Things (IoT) capability, the system collects and uploads sensor data to ThingSpeak cloud via GPRS internet connectivity with the help of AT commands in combination with HTTP GET method. Moreover, the system sends message alert to the responsible organ through GSM/GPRS network and an SMS gateway service implemented by Telerivet mobile messaging platform. In this prototype, Telerivet messaging platform gives surrounding communities a means of reporting observed or identified water pollution events via SMS notifications.

物联网技术在智慧城市中的应用

阐述智慧城市的发展背景,智慧城市建设面临的挑战。分析物联网技术在智慧城市建设中的应用,包括智慧物流、智慧交通、智慧医疗、智慧养老。探讨物联网技术赋能的智慧城市建设意义。