IoT Data Storage Research Articles

Secure transmission and storage of Internet of Things data

The Internet of Everything is the ultimate level form of the Internet of Things. The result of digitizing the objects in life is a huge amount of data that needs to be stored and transmitted. This paper will briefly introduce the IoT and the current status of data processing. Different coding methodologies, Reed Solomon (RS) codes, Low-Density Parity-Check (LDPC) codes, and Low Complexity Parity Check (LCPC) codes will also be explained in detail from their encoding and decoding aspect. Then different codes are specifically analyzed for their usage scenarios in IoT data transmission and storage based on their particular characteristics. In the experimental section, different codes are compared from different perspectives. The main comparisons are made in terms of memory usage, operation time, energy consumption per bit of encoding, and error correction performance. The results of the analysis are RS code is simple but lacks error correction, the LDPC code has good error correction but is more complex, LCPC code strikes a balance between power efficiency and performance.

Data Security Storage and Verification Mechanism Based on Distributed Ledger Technology

Abstract Blockchain, as a secure distributed ledger technology, has received extensive attention from academia and industry for its decentralization, comparability and traceability. This paper proposes a method for verifying data security on blockchain, and a cryptographic uploading and retrieval scheme is combined with IOTA blockchain technology. In this way, an IoT data storage and sharing model is designed to combine blockchain with IPFS. In this paper, it is found that there is a certain delay in operating on Fabric and IOTA compared to the scenarios that do not use blockchain. But Fabric has better performance in upload and download performance than IOTA. In the proposed scheme in this paper, the uploading time is stabilized between 0.8 and 1.2, and the retrieval time is stabilized between 0.43s and 0.76s, which has superior data uploading and retrieval performance than Scheme 1. Furthermore, the time to generate a key for a 50MB file is only around 1800ms, and for a 50MB file split into 6KB blocks, the time to generate a secret key is only around 36s. In this paper, when the file size reaches 5MB, the computational overhead of encryption and decryption is about 1315ms and 1283ms, respectively, and the time overhead of data consistency validation is only about 1095ms when the data block is cut into 6KB for a file of 5MB, indicating that this paper’s scheme has a lower time overhead in the generation of the secret key, encryption and decryption, and the data consistency validation. In summary, the above experiments verify the security and applicability of this paper’s scheme in data storage and verification.

Secure and Distributed IoT Data Storage in Clouds Based on Secret Sharing and Collaborative Blockchain

Secure and Distributed IoT Data Storage in Clouds Based on Secret Sharing and Collaborative Blockchain

IoT Technology in Smart Agriculture

– In recent years, IoT technology has been increasingly used in the agriculture sector, making itsmarter with its usage. This study examines the application areas of IoT technology in the agriculture sector,the advantages it provides, and the necessary equipment for these applications. IoT technology providesadvantages in improving efficiency, reducing production costs, increasing product quality, ensuringsustainability, and facilitating resource management in the agriculture sector. There are various applicationsin agriculture, such as smart greenhouse systems, soil moisture and temperature sensors, automation offarming machinery, animal tracking and health monitoring, plant disease and pest monitoring, grain storagemonitoring, data analysis, and artificial intelligence. The necessary equipment for IoT applications includessensors, actuators, wireless networks, data storage and processing devices, cameras and imaging systems,and GPS devices, allowing farmers to collect real-time data on weather conditions, soil moisture levels,plant diseases, and pests in their fields. This study explains the advantages and application areas of IoTtechnologies in the agriculture sector, demonstrating to researchers and farmers how to use them to increaseefficiency and ensure sustainability in the agriculture sector. Additionally, the study identifies the necessaryresources for the implementation of these technologies, including the required equipment for IoTapplications. Therefore, this study can be beneficial in the decision-making process of researches andindustry leaders who follow innovative applications and technologies in the agriculture sector.

Big Data Precision Marketing Approach under IoT Cloud Platform Information Mining

In this article, an in-depth study and analysis of the precision marketing approach are carried out by building an IoT cloud platform and then using the technology of big data information mining. The cloud platform uses the MySQL database combined with the MongoDB database to store the cloud platform data to ensure the correct storage of data as well as to improve the access speed of data. The storage method of IoT temporal data is optimized, and the way of storing data in time slots is used to improve the efficiency of reading large amounts of data. For the scalability of the IoT data storage system, a MongoDB database clustering scheme is designed to ensure the scalability of data storage and disaster recovery capability. The relevant theories of big data marketing are reviewed and analyzed; secondly, based on the relevant theories, combined with the author's work experience and relevant information, a comprehensive analysis and research on the current situation of big data marketing are conducted, focusing on its macro-, micro-, and industry environment. The service model combines the types of user needs, encapsulates the resources obtained by the alliance through data mining for service products, and publishes and delivers them in the form of data products. From the perspective of the development of the telecommunications industry, in terms of technology, the telecommunications industry has seen the development trend of mobile replacing fixed networks and triple play. The development of emerging technologies represented by the Internet of Things and cloud computing has also led to technological changes in the telecommunications industry. Operators are facing new development opportunities and challenges. It also divides the service mode into self-service and consulting service mode according to the different degrees of users' cognition and understanding of the service, as well as proposes standardized data mining service guarantee from two aspects: after-sales service and operation supervision. A customized data mining service is a kind of data mining service for users' personalized needs. And the intelligent data mining service guarantee is proposed from two aspects of multicase experience integration and group intelligence. In the empirical research part, the big data alliance in Big Data Industry Alliance, which provides data mining service as the main business, is selected as the research object, and the data mining service model of the big data alliance proposed in this article is applied to the actual alliance to verify the scientific and rationality of the data mining service model and improve the data mining service model management system.

Towards Blockchain-Based Secure Storage and Trusted Data Sharing Scheme for IoT Environment

Nowadays, cloud-based storage systems play a vital role in IoT data storage, processing, and sharing. Despite its contribution, the current cloud-based architecture may cause severe data leakage or jeopardize user privacy. Meanwhile, the cloud-based architecture heavily relies on a trusted third-party auditor (TPA) and runs in a centralized control manner. However, the TPA may not be a completely trustworthy entity, and a single point of failure might cause the centralized system to collapse. Fortunately, with the advent of blockchain technology, the decentralized storage model has gained popularity. A decentralized storage system successfully eradicates the rule of TPA, solves the problem of a single point of failure, and has many advantages over a centralized control architecture, such as low storage prices and high throughput. This study offers a blockchain-based decentralized distributed storage and sharing scheme that provides end-to-end encryption and fine-grained access control. In our proposed IoTChain model, fine-grained permission is based on attribute-based access control (A-BAC) policy by employing the Ethereum blockchain as an auditable access control layer. Smart contracts are tailored for the IoTChain model, which combines the Ethereum blockchain and the interplanetary file system (IPFS). We used an advanced encryption standard (AES) for encryption and the elliptic curve Diffie-Hellman key exchange protocol for secret key sharing between data owners and users. Also, the proof-of-work (PoW) consensus mechanism is replaced with a proof-of-authority (PoA) to minimize system transaction cost and boost system throughput. Additionally, our solution has been tested on the Ethereum official test network Rinkeby, and the results demonstrate that our approach is realistic and economical on the IoT data.

Evaluation of efficiency of Database Systems Used for IoT Applications-Review

The data put away in IoT databases increments as the IoT applications stretch out all through smart city appliances, industry, and agriculture. New database systems should handle tremendous measures of tactile and actuator data progressively or intuitively. Confronting this first rush of IoT unrest, database management step by step to acquire a piece of the overall industry, grow new capacities and endeavor to defeat past discharges' weaknesses while giving highlights to the IoT. There are two well-known database types: The Relational Database Management Systems and NoSQL databases, with NoSQL making progress on IoT data storage. With regards to this paper, these two sorts are inspected. Zeroing in on open source databases, the creators investigate IoT data sets and represent an answer to the inquiry that one performs better than the next.

Космічна інфраструктура інтернету речей. Стан та перспективи розвитку

We present an overview of possibilities for existing Satellite Communication Systems utilization to provide Internet of Things Services. It is shown that existing Satellite Communication Systems provide traffic transmission for IoT Systems with Cloud Architecture. The proposals are explicated on the possibility of using Fog and Edge Computing for Satellite Communication Systems. The implementation of Fog and Edge computing in IoT Systems requires the modernization of the Low-Earth Orbit (LEO) and Geostationary Orbit (GEO) Satellite Communication Systems, and we show the ways of their enhancement. To increase the efficiency of IoT data processing and the reliability of IoT Data Storage, we propose to construct an Orbital Cloud Data Storage in GEO, which consists of several GEO Satellites - Cloud Computing Data Centers. Such a structure would require the development of methods of access providing to the Orbital Cloud Data Storage. For these purposes, our propositions include using GEO High-Throughput Satellites and satellites from the structure of LEO Satellite Communication. The issues of interaction between Orbital Cloud Data Storage and ground-based Cloud Data Processing and Storage Infrastructure are briefly considered. The orbital slots in GEO are proposed for the location of GEO Satellites - Cloud Computing Data Centers.

Cloud-based Middleware for Syntactical Interoperability in Internet of Things

Heterogeneity of protocol communications, data formats, data structure, and hardware specifications on the Internet of things can lead to an Interoperability problem. The solution provides middleware that capable to work in heterogeneity communications, data formats, etc. This paper proposed. A cloud-based middleware that provides a communication interface to receive data from sensor nodes based on Restful and CoAP. Received data then stored in heterogenous IoT data storage based on the NoSQL database. From experiment and testing, interoperability testing methodology was used. The result shows proposed middleware can receive data from both protocols. The received data could store based on structure data or unstructured data on IoT data storage.