C3PO: C loud-based C onfidentiality-preserving C ontinuous Query P r o cessing

With the advent of the Internet of things (IoT), billions of devices are expected to continuously collect and process sensitive data (e.g., location, personal health factors). Due to the limited computational capacity available on IoT devices, the current de facto model for building IoT applications is to send the gathered data to the cloud for computation. While building private cloud infrastructures for handling large amounts of data streams can be expensive, using low-cost public (untrusted) cloud infrastructures for processing continuous queries including sensitive data leads to strong concerns over data confidentiality. This article presents C3PO, a confidentiality-preserving, continuous query processing engine, that leverages the public cloud. The key idea is to intelligently utilize partially homomorphic and property-preserving encryption to perform as many computationally intensive operations as possible—without revealing plaintext—in the untrusted cloud. C3PO provides simple abstractions to the developer to hide the complexities of applying complex cryptographic primitives, reasoning about the performance of such primitives, deciding which computations can be executed in an untrusted tier, and optimizing cloud resource usage. An empirical evaluation with several benchmarks and case studies shows the feasibility of our approach. We consider different classes of IoT devices that differ in their computational and memory resources (from a Raspberry Pi 3 to a very small device with a Cortex-M3 microprocessor) and through the use of optimizations, we demonstrate the feasibility of using partially homomorphic and property-preserving encryption on IoT devices.

Design of Intelligent Voice Acquisition System Based on Cloud Resource Scheduling Model

The existing acquisition system has the problem of imperfect communication link, which leads to the weak signal receiving strength of the system. This paper designs an intelligent voice acquisition system based on cloud resource scheduling model. Hardware: select S3C6410 as hardware platform, optimize audio access port, connect IIS serial bus and other components; Software part: extract the frequency agility characteristics of intelligent voice signal, predict the future sample value, establish the communication link with cloud resource scheduling model, obtain the communication rate information, code and generate digital voice data, set the transmission function of intelligent acquisition system with overlay algorithm. Experimental results: the average signal receiving strength of the designed system and the other two intelligent voice intelligent acquisition systems is 106.40 dBm, 91.33 dBm and 90.23 dBm, which proves that the intelligent acquisition system integrated with cloud resource scheduling model has higher use value.

Community Environmental Detection and Community Outdoor Space Health Promotion Based on Cloud Resource Scheduling Mechanism

In the context of rapid economic growth, people’s living standards are improving day by day, and China’s urbanization process is also gradually accelerating. Urban renewal is a very complex project. The renewal and expansion of most cities in the country usually involve demolishing and rebuilding. This way of urban renewal only pays attention to the renewal efficiency of cities and towns, and ignores the health needs of residents, which will make community residents lack a sense of security, pleasure, comfort, and belonging to the community, and greatly reduce the quality of life and physical fitness of community residents. Building a healthy city is an important goal of today’s society, and community is the basic unit of a city, so it is urgent to build a health-promoting community. We should pay attention to and study the social environment, the external space environment of residential areas, and the interaction between them, so as to make develop them in a healthy direction and create a healthy and positive community. Therefore, it is an urgent task to improve the community residents’ attention to the above problems and build community outdoor space, which has very important practical significance. In this paper, we use the cloud resource scheduling mechanism and the Internet of things to study the healthy role of community outdoor space planning. Through the transplantation of embedded Linux system, the development of communication interface and the external acquisition sensing device, we collect the information of working status and running status, and transmit it to the database built in the cloud through the 4G module on the motherboard. Then, HTML + java script + CSS + JSON + Ajax technology is used to write the display interface and logical relationship, so that the data can be displayed on the mobile terminal and PC, which can provide a useful technical exploration for outdoor space planning. The community Internet of Things technology realizes the intelligent community environment detection, and the community cloud resource scheduling mechanism combined with the community Internet of Things can obtain the residents’ help information in time and allocate the community outdoor resources in real time, which can not only meet the health needs of community members but also be conducive to the sustainable development of a health-promoting community. In addition, the cloud resource scheduling mechanism and the Internet of things also provide new ideas for the study of the health promotion research of community outdoor space planning.

Research on Robot Dynamic Path Planning Based on Multiple Linear Reinforcement Learning

Under the background of digital and intelligent transformation, all walks of life are facing the conflict between internal stability and rapidly changing external needs, and the conflict between stable background and dynamic foreground. To solve these conflicts and problems, it needs to take new means to adjust from multiple dimensions. Draw support from the new info and communication operation support system, it could form a digital Internet info support system with the cloud platform, which can effectively establish fast and flexible front-end utilizations and support the rapid development, agile iteration and on-demand adjustment of related businesses. The Internet backbone network needs to make the info open. The new info communication operation support system based on the Internet can enable the info resources to be transmitted as needed. The research and utilization of cloud resource visualization and controllability has gradually become the key to the development of new Internet communication operation system. On the premise of systematically combing the Internet info and communication operation support system, this paper comprehensively studies the utilization of cloud resources, and analyses the utilization scenarios of cloud resources of the new education communication operation system, in order to better ameliorate the more efficient and secure utilization of cloud resources and communication operation system inside and outside the enterprise.

A Survey on Resource Management Techniques in Cloud Computing

Cloud computing refers to a computer environment in which traditional software systems, installations, and licensing concerns are replaced with comprehensive on demand," pay as you need" internet based services. In this scenario, many cloud customers can request multiple cloud resources at the same time. As a result, there should be a plan in place to ensure that resources must be prepared for the needy customer in proficient way in order complete their needs. In cloud computing systems, resource management is a critical and difficult issue. It must meet numerous service quality requirements and, as a result, reduce SLA violations. This paper survey different resource management technique for cloud infrastructures. Keywords: Cloud, Resource management and techniques

Proposal and Investigation of a Convolutional and LSTM Neural Network for the Cost-Aware Resource Prediction in Softwarized Networks

Resource prediction algorithms have been recently proposed in Network Function Virtualization architectures. A prediction-based resource allocation is characterized by higher operation costs due to: (i) Resource underestimate that leads to quality of service degradation; (ii) used cloud resource over allocation when a resource overestimate occurs. To reduce such a cost, we propose a cost-aware prediction algorithm able to minimize the sum of the two cost components. The proposed prediction solution is based on a convolutional and Long Short Term Memory neural network to handle the spatial and temporal correlations of the need processing capacities. We compare in a real network and traffic scenario the proposed technique to a traditional one in which the aim is to exactly predict the needed processing capacity. We show how the proposed solution allows for cost advantages in the order of 20%.

JUSUF: Modular Tier-2 Supercomputing and Cloud Infrastructure at Jülich Supercomputing Centre

JUSUF is a petaflop supercomputer operated by Jülich Supercomputing Centre at Forschungszentrum Jülich as a European supercomputing and cloud resource. JUSUF was funded via the ICEI project and especially serves the Human Brain Project and PRACE via ICEI and the Fenix Research Infrastructure. The system consists of two parts, an HPC cluster partition and an Infrastructure-as-a-Service cloud partition. The system entered production phase in spring 2020. It is based on the Bull X400 product family with AMD Rome processors, partially accelerated by Nvidia V100 GPUs, and Nvidia Mellanox HDR InfiniBand.