A QoS-aware Model for Cloud Storage Environment

Recently the lack of geo-location assurance of data in cloud storage has been identified as one of the main reasons why organizations that deal with sensitive data (e.g., financial data, health related data) cannot adopt a cloud storage solution even if they want to. In this paper, we present a Hardware-based Data geo-Location Assurance Solution (HDLAS), which is suitable for almost all cloud storage applications available today. Trusted Platform Module (TPM) and a cryptographic scheme called Provable Data Possession (PDP) are the basis of our solution. We define a new attack model for HDLAS which seems to be a realistic attack model for the existing cloud storage applications. With the combination of a GPS receiver and TPM, HDLAS is able to offer its clients not only the accurate geo-location of their data but also a hardware-based root of trust for that. Unlike many existing solutions, HDLAS works even if a piece of data is replicated into different storage servers. Furthermore we also illustrate how easily HDLAS can be adopted in existing Cloud Storage Providers such as Microsoft Azure.

Since the popularity of the Internet, more and more people have chosen to look for the information and resources they need on the Internet. People’s lives have gradually been changed by the Internet. Cloud storage brings new development opportunities, and the copyright protection issues involved in cloud storage are gradually emerging. Cloud storage has changed the original pattern among traditional information owners, disseminators and users, causing conflicts among copyright owners, cloud storage servers and information acquirers, and the problem of copyright protection has become increasingly prominent. The rapid development of network file sharing platforms such as cloud storage brings unprecedented challenges to copyright protection. The application and development of cloud storage also challenges the recognition of traditional copyright system, object and content, so we must balance the contribution of cloud storage to the exchange of information resources and protect the legitimate rights and interests of copyright holders.

The development of digital libraries put forward higher requirements for storage, the traditional storage technology has become increasingly unable to meet the needs of library data storage, the emergence of cloud storage technology provides us with new solutions. This paper analyzed the advantages of cloud storage technology, the library different data on the cloud storage has different needs, and cloud storage application in the library problems was studied.

Cloud storage services possess the majority portion of the cloud market. Its exponential growth represents the continuous storage of public and personal information to the remote location over the cloud for on-the-go availability. However, cloud storage services also attract criminals due to low-cost on- demand resources. In the case of SaaS applications, the cloud service providers control all the underlying hardware and execution environment of the application. Forensic investigators must depend upon the cooperation of CSP for evidence identification and collection. This is the reason that forensics of cloud storage application become an obstacle as well as an opportunity for forensic researchers and examiners. In this paper, we focus on the identification of potential forensic artifacts for a single SaaS application: Dropbox

As an application of cloud storage, cloud backup is effective, reliable, extensible, cost-effective and usable, which makes cloud backup having a broad prospect of application. We proposed a reliable cloud backup scheduling algorithm that showing good performance. In this algorithm, data access time and data reliability are introduced. With the cloud state table and cloud resources table, the algorithm determines which cloud storage node will save the data. The simulated experiment shows that the proposed algorithm, guaranteeing the data reliability, gets good data access performance.

Smartphones are a testament to the development of digital technology. At this time, the smartphone is also experiencing growth in storage media, one of which is the Cloud storage media. One cloud storage application is the Dropbox Application. The development of cloud storage media does not rule out the possibility of a negative impact on the use or can be used as a medium for crime, such as storing evidence of criminal transactions and cybercrime. This study uses conversation scenarios for application conditions, including data deletion in applications. Data for each experiment will be taken using the National Institute of Justice (NIJ) Method. The method used in dealing with crime with smartphone media evidence is the National Institute of Justice (NIJ) Method. The conclusion of this study is that the use of the National Institute of Justice (NIJ) method ranks the digital forensic stages, starting with identification, collection, examination, analysis, and reporting very well. This method is widely used in handling digital crime cases. The results of the acquisition will then be analyzed by translating the hex codes resulting from the acquisition to produce evidence that can be understood by the judge later.

The availability of large-scale multitasked parallel architectures introduces the following processor assignment problem. We are given a long sequence of data sets, each of which is to undergo processing by a collection of tasks whose intertask data dependencies form a series-parallel partial order. Each individual task is potentially parallelizable, with a known experimentally determined execution signature. Recognizing that data sets can be pipelined through the task structure, the problem is to find a "good" assignment of processors to tasks. Two objectives interest us: minimal response time per data set, given a throughput requirement, and maximal throughput, given a response time requirement. Our approach is to decompose a series-parallel task system into its essential "serial" and "parallel" components; our problem admits the independent solution and recomposition of each such component. We provide algorithms for the series analysis, and use an algorithm due to Krishnamurti and Ma for the parallel analysis. For a p processor system and a series-parallel precedence graph with n constituent tasks, we give a O(np/sup 2/) algorithm that finds the optimal assignment (over a broad class of assignments) for the response time optimization problem; we find the assignment optimizing the constrained throughput in O(np/sup 2/ log p) time. These techniques are applied to a task system in computer vision.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Service composition makes use of existing service-based applications as components to achieve a business goal. In time critical business environments, the response time of a service is crucial, which is also reflected as a clause in service level agreements (SLAs) between service providers and service users. To allow the composite service to fulfill the response time requirement as promised, it is important to find a feasible set of component services, such that their response time could collectively allow the satisfaction of the response time of the composite service. In this work, we propose a fully automated approach to synthesize the response time requirement of component services, in the form of a constraint on the local response times, that guarantees the global response time requirement. Our approach is based on parameter synthesis techniques for real-time systems. It has been implemented and evaluated with real-world case studies.

Electronic commerce has attracted a great deal of attention recently. Among the different types of electronic commerce, business-to-business is the one most widespread in terms of turnover. An important aspect in business-to-business e-commerce scenarios is how to meet the response time and throughput requirements of applications in spite of execution taking place across corporate boundaries and, in the future, via the Internet instead of using leased lines. Given the unpredictable variations of available bandwidth in today's Internet, providing application quality-of-service guarantees for these requirements is a complex task. Due to the current trend to run multimedia applications over the Internet, we assume that the future Internet will not only support best-effort service but also guaranteed service, e.g. via network resource reservation. This allows us to also take advantage of this service for e-commerce applications. The problem remains non-trivial due to the wide variations among application scenarios. As a first step towards implementing a generic solution, this paper proposes a scheme which enables virtual business processes to meet response time and throughput requirements through network resource reservation. The paper describes the application scenarios we have in mind, the WISE (Workflow-based Internet SErvices) system where these ideas are being implemented, and the mechanisms involved in providing quality-of-service guarantees at the application level.

Real-time monitoring of radiation levels at uranium mining sites is mandatory to ensure environmental and human safety. Ionizing radiation like Gamma rays, Alpha particles, Beta particles are likely to be produced during uranium decay have major threats to human health such as lung cancer, tumor, and eventually death. Thus there have been several different means of monitoring uranium mining using radiation survey meters and other radiation detectors. However, frequent traveling to the uranium mining site to measure the radiation level is time-consuming and cost full to the regulatory bodies. Thus this study aims to present a system for real-time monitoring the radiation level at uranium mining sites using internet of things (IoT) technology. The system was programmed by using ESP 32 microcontroller board, through the inbuilt Wi-Fi it was able to send radiation data to the Message Queuing Telemetry Transport (MQTT) broker for cloud data storage. The MQTT protocol facilitated remote visualization of radiation levels from the cloud storage and mobile application. The end-users monitored radiation data in real-time and received the notification message and alarm in case of excess radiation through the mobile application. The ESP 32 microcontroller board and internet of things technology facilitated the system to send the data to the cloud allowing the end-users to visualize and monitor radiation levels anytime and anywhere via the internet.

This paper presents the design and development of low-cost Internet of Things (IoT) system for remote monitoring of agriculture ecosystem. The aims of the research are to evaluate the accuracy and reliability of data collected and transmitted with developed IoT system and access from remote location. These data are then compared with the readings of the conventional stand-alone sensors or meters. The system is set in the laboratory and utilises low cost microcontroller, sensors, Wi-Fi network communication, cloud storage, mobile and web application. Microcontroller Arduino Uno ATMega328P is used with ESP8266 Wi-Fi module to enable the device to be connected to the Internet. The sensors used in this system are selected base on the plant’s growth factor. All data collected from the sensors are sent to the Cloud platform such as ThingSpeak and Blynk. Periodical monitoring is carried out on laptop and mobile phone. The results showed that the data taken from the soil moisture, soil temperature, light intensity, surrounding temperature and humidity are accurate and reliable.

Adherence to prescribed medication affects global clinical practice especially on chronic disease management resulting in adverse medical and economic burden. Reliable standard and practice in measuring adherence among patient is yet to be established clinically although aspects from user behavioural, clinical needs and technology-assisted devices design have been studied. Lack of real-time monitoring and inefficient method of medication consumption validation has been identified as the challenges in monitoring patient medication consumption’s pattern. The aim of this study is to design and deploy an IoT driven medication adherence manager. The proposed IoT architecture enabled by real time monitoring through a multi-sensor alert option in medicinal compartment to ensure adherence integrity. The reliability of the proposed device further enhanced with the mobile application and cloud storage and usage analytic support application. The medication adherence manager expected to digitize the medication consumption process thus improving the patient health and well-being at the same time reduce pharmaceutical wastage due to nonadherence.

This paper focuses on studying cloud storage data protection model and implementing encrypted storage of user data in double-key form. User data are encrypted with symmetric encryption algorithm and this secret key is encrypted with asymmetric encryption algorithm. The private key is managed and controlled by users. In this way, users guarantee the security of their own data with the sole private key. Providing effective protection for uploading and downloading of user data and good data storage and transmission support for cloud storage application through the data protection mechanism deployed at client, thus solving the biggest obstacle, i.e. security of cloud data in the application of cloud storage enterprises currently to a certain extent.

With the rapid development of cloud storage technology, the cloud storage platform has gradually been used to store data. However, the privacy protection strategy provided by public cloud storage platform is hard to be trust by users. Moreover, they are unable to customize their own storage strategy according to their demands. This study proposed a consistency-availability-partition tolerance (CAP) theory -based data privacy protection strategy, which firstly employed CAP theory to provide privacy data protection for users and then offer users with choice to select corresponding privacy strategy to store data. Moreover, a total of three privacy protection strategies were put forward, focusing on the balance between data consistency and response time, data consistency and data availability, as well as response time and availability respectively.

Most people nowadays are always occupied with their mobile devices. Mobile devices were utilized not just as a means of communication but also to launch applications installed to aid routine activities. The deployment of cloud storage applications to access cloud storage accounts is one of the most popular uses. Consumers have rapidly adopted cloud storage services from mobile devices, often available over the internet. However, this situation allows criminals to engage in illegal acts such as child pornography and violence. Since cloud services are virtual, non-local, and primarily proprietary technologies, digital forensics investigators encounter a significant challenge in resolving such issues. For investigators, data from mobile devices is vital. It will be stored on the mobile device and provide an overview of the user's cloud storage contents. This study focuses on Android devices and employs the MediaFire and Sync.com applications along with 20 data sets in various formats as samples. The mobile device will then be extracted using MSAB XRY under various circumstances (after the process of file modification, data cleanup, cache clearance, and application removal). The study contributes to the design of a data extraction framework guided by NIST 800–101 rev 1 and SWGDE Best Practices, as well as the documentation of the extraction procedure, as a step in ensuring that the data extraction process adheres to digital forensics standards. This research is projected to offer a fundamental reference for conducting digital forensic investigations of mobile cloud storage services.