On-demand Storage Research Articles

Frequency-multiplexed on-demand storage in five modes of atomic frequency comb through simultaneous application of control pulses.

In quantum communication with quantum repeaters, multiplexed quantum memory is expected to enhance communication rates. When using an atomic frequency comb (AFC) for on-demand storage, the frequency mode number is often limited by the optical power of the control pulses. Here, using a space-coupled waveguide electro-optic modulator, we increased the output power, allowing us to apply control pulses to multiple modes simultaneously. Further, through enhancement of an experimental setup that increases power density, we increased the number of modes. Consequently, we pioneered, to the best of our knowledge, on-demand storage using five modes of AFC. This technology is a significant achievement toward frequency-multiplexed on-demand quantum memory.

Enhancing Cloud Security Integrating Deep Learning & Data Mining: A Comprehensive Review

Cloud computing plays a pivotal role in data storage and online services, offering benefits such as easy access, on-demand storage, scalability, and cost-efficiency. Its rapidly evolving technologies can enhance the security of the Internet of Things (IoT) and Cyber-Physical Systems (CPS) against cyber threats. Given the increasing prevalence of sophisticated malware, traditional detection methods are often inadequate due to advanced evasion techniques. This article provides a comprehensive review of cloud-based malware detection technologies and explores the use of cloud computing in safeguarding IoT and critical infrastructure. It evaluates the pros and cons of cloud environments for malware detection and introduces a deep learning and data extraction methodology for detecting cloud-based malware. Additionally, it discusses recent research on malware propagation issues and compares various detection approaches, identifying their strengths and weaknesses. The study's findings offer valuable insights for addressing current challenges in malware research.

A Review Paper on Integration of Deep Learning & Data Mining Strategies

Cloud computing plays a crucial role in data storage and online services, offering advantages such as easy access, on-demand storage, scalability, and cost efficiency. Its rapidly advancing technologies can improve the security of the Internet of Things (IoT) and Cyber-Physical Systems (CPS) against cyber threats. With the rise of sophisticated malware, traditional detection methods are often insufficient due to advanced evasion techniques. This article presents a comprehensive review of cloud-based malware detection technologies and examines the use of cloud computing to protect IoT and critical infrastructure. It assesses the benefits and drawbacks of cloud environments for malware detection and introduces a deep learning and data extraction methodology for identifying cloud-based malware. Additionally, it discusses recent research on malware propagation issues and compares various detection methods, highlighting their strengths and weaknesses. The study's findings provide valuable insights for addressing current challenges in malware research.

Resource Management in Cloud and Cloud-influenced Technologies for Internet of Things Applications

The trend of adopting Internet of Things (IoT) in healthcare, smart cities, Industry 4.0, and so on is increasing by means of cloud computing, which provides on-demand storage and computation facilities over the Internet. To meet specific requirements of IoT applications, the cloud has also shifted its service offering platform to its next-generation models, such as fog, mist, and dew computing. As a result, the cloud and IoT have become part and parcel of smart applications that play significant roles in improving the quality of human life. In addition to the inherent advantages of advanced cloud models, to improve the performance of IoT applications further, it is essential to understand how the resources in the cloud and cloud-influenced platforms are managed to support various phases in the end-to-end IoT deployment. Considering this importance, in this article, we provide a brief description, a systematic review, and possible research directions on every aspect of resource management tasks, such as workload modeling, resource provisioning, workload scheduling, resource allocation, load balancing, energy management, and resource heterogeneity in such advanced platforms, from a cloud perspective. The primary objective of this article is to help early researchers gain insight into the underlying concepts of resource management tasks in the cloud for IoT applications.

On-Demand Storage of Photonic Qubits at Telecom Wavelengths.

Quantum memories at telecom wavelengths are crucial for the construction of large-scale quantum networks based on existing fiber networks. On-demand storage of telecom photonic qubits is an essential request for such networking applications but yet to be demonstrated. Here we demonstrate the storage and on-demand retrieval of telecom photonic qubits using a laser-written waveguide fabricated in an ^{167}Er^{3+}:Y_{2}SiO_{5} crystal. Both ends of the waveguide memory are directly connected with fiber arrays with a fiber-to-fiber efficiency of 51%. Storage fidelity of 98.3(1)% can be obtained for time-bin qubits encoded with single-photon-level coherent pulses, which is far beyond the maximal fidelity that can be achieved with a classical measure and prepared strategy. This device features high reliability and easy scalability, and it can be directly integrated into fiber networks, which could play an essential role in fiber-based quantum networks.

On-demand multimode optical storage in a laser-written on-chip waveguide

Quantum memory is a fundamental building block for large-scale quantum networks. On-demand optical storage with a large bandwidth, a high multimode capacity and an integrated structure simultaneously is crucial for practical application. However, this has not been demonstrated yet. Here, we fabricate an on-chip waveguide in a $\mathrm {^{151}Eu^{3+}:Y_2SiO_5}$ crystal with insertion losses of 0.2 dB, and propose a novel pumping scheme to enable spin-wave atomic frequency comb (AFC) storage with a bandwidth of 11 MHz inside the waveguide. Based on this, we demonstrate the storage of 200 temporal modes using the AFC scheme and conditional on-demand storage of 100 temporal modes using the spin-wave AFC scheme. The interference visibility between the readout light field and the reference light field is $99.0\% \pm 0.6\%$ and $97\% \pm 3\%$ for AFC and spin-wave AFC storage, respectively, indicating the coherent nature of this low-loss, multimode and integrated storage device.

Encryption Techniques for Smart Systems Data Security Offloaded to the Cloud

With technological advancement, cloud computing paradigms are gaining massive popularity in the ever-changing technological advancement. The main objective of the cloud computing system is to provide on-demand storage and computing resources to the users on the pay-per-use policy. It allows small businesses to use top-notch infrastructure at low expense. However, due to the cloud resource sharing property, data privacy and security are significant concerns and barriers for smart systems to constantly transfer generated data to the cloud computing resources, which a third-party provider manages. Many encryption techniques have been proposed to cope with data security issues. In this paper, different existing data protection and encryption techniques based on common parameters have been critically analyzed and their workflows are graphically presented. This survey aims to collect existing data encryption techniques widely presented in the literature for smart system data security offloaded to the cloud computing systems under a single umbrella.

On-Demand Storage and Retrieval of Microwave Photons Using a Superconducting Multiresonator Quantum Memory.

We realize on-demand storage and retrieval of weak coherent microwave photon pulses at the single-photon level. A superconducting multiresonator system which is composed of a set of frequency-tunable coplanar waveguide resonators is implemented as the quantum memory. By dynamically tuning the resonant frequencies of the resonators, we achieve tunable memory bandwidth from 10 to 55MHz, with well preserved phase coherence. We further demonstrate on-demand storage and retrieval of a time-bin flying qubit. This result opens up a prospect to integrate our chip-based quantum memory with the state-of-the-art superconducting quantum circuit technology for quantum information processing.

On-Demand Quantum Storage of Photonic Qubits in an On-Chip Waveguide.

Photonic quantum memory is the core element in quantum information processing (QIP). For the scalable and convenient practical applications, great efforts have been devoted to the integrated quantum memory based on various waveguides fabricated in solids. However, on-demand storage of qubits, which is an essential requirement for QIP, is still challenging to be implemented using such integrated quantum memory. Here we report the on-demand storage of time-bin qubits in an on-chip waveguide memory fabricated on the surface of a ^{151}Eu^{3+}:Y_{2}SiO_{5} crystal, utilizing the Stark-modulated atomic frequency comb protocol. A qubit storage fidelity of 99.3%±0.2% is obtained with single-photon-level coherent pulses, far beyond the highest fidelity achievable using the classical measure-and-prepare strategy. The developed integrated quantum memory with the on-demand retrieval capability represents an important step toward practical applications of integrated quantum nodes in quantum networks.

On-demand storage and release of antimicrobial peptides using Pandora's box-like nanotubes gated with a bacterial infection-responsive polymer.

Background: Localized delivery of antimicrobial agents such as antimicrobial peptides (AMPs) by a biomaterial should be on-demand. Namely, AMPs should be latent and biocompatible in the absence of bacterial infection, but released in an amount enough to kill bacteria immediately in response to bacterial infection.Methods: To achieve the unmet goal of such on-demand delivery, here we turned a titanium implant with titania nanotubes (Ti-NTs) into a Pandora's box. The box was loaded with AMPs (HHC36 peptides, with a sequence of KRWWKWWRR) inside the nanotubes and “closed” (surface-modified) with a pH-responsive molecular gate, poly(methacrylic acid) (PMAA), which swelled under normal physiological conditions (pH 7.4) but collapsed under bacterial infection (pH ≤ 6.0). Thus, the PMAA-gated Ti-NTs behaved just like a Pandora's box. The box retarded the burst release of AMPs under physiological conditions because the gate swelled to block the nanotubes opening. However, it was opened to release AMPs to kill bacteria immediately when bacterial infection occurred to lowering the pH (and thus made the gate collapse).Results: We demonstrated such smart excellent bactericidal activity against a panel of four clinically important bacteria, including Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, methicillin-resistant Staphylococcus aureus. In addition, this box was biocompatible and could promote the osteogenic differentiation of human mesenchymal stem cells. Both in vitro and in vivo studies confirmed the smart “on-demand” bactericidal activity of the Pandora's box. The molecularly gated Pandora's box design represents a new strategy in smart drug delivery.

Facilitating Secure and Efficient Spatial Query Processing on the Cloud

Database outsourcing is a common cloud computing paradigm that allows data owners to take advantage of its on-demand storage and computational resources. The main challenge is maintaining data confidentiality with respect to untrusted parties i.e., cloud service provider, as well as providing relevant query results in real-time to authenticated users. Existing approaches either compromise confidentiality of the data or suffer from high communication cost between the server and the user. To overcome this problem, we propose a dual transformation and encryption scheme for spatial data, where encrypted queries are executed entirely at the service provider on the encrypted database and encrypted results are returned to the user. The user issues encrypted spatial range queries to the service provider and then uses the encryption key to decrypt the query response returned. This allows a balance between the security of data and efficient query response as the queries are processed on encrypted data at the cloud server. Moreover, we compare with existing approaches on large datasets and show that this approach reduces the average query communication cost between the authorized user and service provider, as only a single round of communication is required by the proposed approach.

Cloud computing

Cloud computing is a mode of acquisition of infrastructure where a cloud service provides on demand computing and on-demand storage, accessible over the web, with a matching business model, namely pay-per-use. Lower cost, sometimes a factor of five, is achieved by automating operations in warehouse-sized data centres, sharing the hefty burden of cooling, physical security, and power backup, and the use of commodity components. As access to storage managed by cloud service providers gained market acceptance, the phrase “the cloud” came into use to refer to the location of information stored with a cloud service provider to be shared (business documents and photos) or copied for backup (against losing a phone or deleting information on a laptop). Security, and to a lesser extent privacy, concerns are the major barriers to the adoption of cloud computing, but the leading cloud service providers have responded to the point that sensitive information, such as medical records and credit-card-holder data, is now held in the cloud.

New Power Technology for Venus Aerial Missions

In-situ exploration of Venus is challenging due to its severe environment, which is benign (25oC) at an altitude of 55 km, but rapidly becoming more hostile at lower altitudes. The temperature increases at ~7oC/km to ~465°C, with the pressure reaching 90 bars at the surface.1 These challenging conditions have limited in-situ exploration missions to high altitude balloons at 55 km (above the clouds) that lasted for 48 h, or even shorter duration surface missions that survived for two hours.2,3 The high-altitude (55-65km) balloon missions are stymied by the opaqueness of the Venusian clouds, which underlines the need for more long-duration in-situ missions for a better understanding of the Venus atmosphere across the cloud layers and below, as recommended by the Venus science community, Venus Exploration Analysis Group (VEXAG).4 Long-duration variable-altitude balloons (VABs) extending below the clouds have gained particular interest. Durable VABs would allow i) long-term measurements across Venus clouds, ii) determination of chemical species and isotopes underneath the clouds, iii) transport to different longitudes on the planet and measure atmospheric flow patterns, especially with the altitude control, iv) probing the interior structure through close-range imaging, and v) investigation of the seismic activity from acoustic measurements at various altitudes. For these missions, conventional power technologies are inadequate. For example, the performance of photovoltaics (PV) is hampered by the decreasing solar flux deeper in the clouds, the selective loss of short wavelength radiation, and the performance loss from the high temperatures.5 An energy storage system tolerant to high temperatures is needed to compensate for the reduced power generation of PVs at low altitudes, and to support nighttime operations for the VABs. In this paper, we will describe a novel ‘Venus Interior Probe using in-situ Power and Propulsion (VIP-INSPR) architecture we have been developing under NASA-NIAC (Novel Innovative and Advanced Concepts) program for sustained Venus atmospheric exploration. The probe concept utilizes: i) PV as a power source to the probe at high altitudes, and to electrolyze water carried from ground using regenerative solid oxide fuel/ electrolysis cell (SOEC), ii) Solid oxide fuel cell (SOFC)6 to provide power at low altitudes, iii) hydrogen storage bed for on-demand storage or release of hydrogen,7 iv) and a balloon filled with hydrogen and with hydrogen buoyancy-based altitude control system. Both H2 and O2 would be regenerated through electrolysis of the water produced in the fuel cell (a closed–system) at high altitudes. Acknowledgments: This work presented here was carried out at the Jet Propulsion Laboratory, California Institute of Technology under a contract with National Aeronautics and Space Administration and supported NASA-NIAC.

Decentralized attribute-based conjunctive keyword search scheme with online/offline encryption and outsource decryption for cloud computing

In recent years, the increasing popularity of cloud computing has led to a trend that data owners prefer to outsource their data to the clouds for the enjoyment of the on-demand storage and computing services. For security and privacy concerns, fine-grained access control and secure data retrieval for the outsourced data is of critical importance. Attribute-based keyword search (ABKS) scheme, as a cryptographic primitive which explores the notion of public key encryption with keyword search (PEKS) into the context of attribute-based encryption (ABE), can enable the data owner to flexibly share his data to a specified group of users satisfying the access policy and meanwhile, maintain the confidentiality and searchable properties of the sensitive data. However, in most of the previous ABKS schemes, the decryption service is not provided, and a fully trusted central authority is required, which is not practical in the scenario that the access policy is written over attributes or credentials issued across different trust domains and organizations. Moreover, the efficiency of storage and computation is also the bottleneck of implementation of ABKS scheme. In this paper, for the first time, we propose a decentralized ABKS scheme with conjunctive keyword search for the cloud storage system. Besides the multi-keyword search in the decentralized setting, our scheme outsources the undesirable costly operations of decryption to the cloud without degrading the user’s privacy. Furthermore, the encryption phase is also divided into two phases, an offline pre-computation phase which is independent with the plaintext message, access policy, and keyword set, and can be performed at any time when the data owner’s device is otherwise not in use, and an online encryption phase which only incurs very little computation costs. Security analysis indicates that our scheme is provably secure in the random oracle model. The asymptotic complexity comparison and simulation results also show that our scheme achieves high computation efficiency.

Generic user revocation systems for attribute-based encryption in cloud storage

Cloud-based storage is a service model for businesses and individual users that involves paid or free storage resources. This service model enables on-demand storage capacity and management to users anywhere via the Internet. Because most cloud storage is provided by third-party service providers, the trust required for the cloud storage providers and the shared multi-tenant environment present special challenges for data protection and access control. Attribute-based encryption (ABE) not only protects data secrecy, but also has ciphertexts or decryption keys associated with fine-grained access policies that are automatically enforced during the decryption process. This enforcement puts data access under control at each data item level. However, ABE schemes have practical limitations on dynamic user revocation. In this paper, we propose two generic user revocation systems for ABE with user privacy protection, user revocation via ciphertext re-encryption (UR-CRE) and user revocation via cloud storage providers (UR-CSP), which work with any type of ABE scheme to dynamically revoke users.

Multiplexed storage and real-time manipulation based on a multiple degree-of-freedom quantum memory

The faithful storage and coherent manipulation of quantum states with matter-systems would enable the realization of large-scale quantum networks based on quantum repeaters. To achieve useful communication rates, highly multimode quantum memories are required to construct a multiplexed quantum repeater. Here, we present a demonstration of on-demand storage of orbital-angular-momentum states with weak coherent pulses at the single-photon-level in a rare-earth-ion-doped crystal. Through the combination of this spatial degree-of-freedom (DOF) with temporal and spectral degrees of freedom, we create a multiple-DOF memory with high multimode capacity. This device can serve as a quantum mode converter with high fidelity, which is a fundamental requirement for the construction of a multiplexed quantum repeater. This device further enables essentially arbitrary spectral and temporal manipulations of spatial-qutrit-encoded photonic pulses in real time. Therefore, the developed quantum memory can serve as a building block for scalable photonic quantum information processing architectures.

Cloud computing applications for biomedical science: A perspective.

Biomedical research has become a digital data–intensive endeavor, relying on secure and scalable computing, storage, and network infrastructure, which has traditionally been purchased, supported, and maintained locally. For certain types of biomedical applications, cloud computing has emerged as an alternative to locally maintained traditional computing approaches. Cloud computing offers users pay-as-you-go access to services such as hardware infrastructure, platforms, and software for solving common biomedical computational problems. Cloud computing services offer secure on-demand storage and analysis and are differentiated from traditional high-performance computing by their rapid availability and scalability of services. As such, cloud services are engineered to address big data problems and enhance the likelihood of data and analytics sharing, reproducibility, and reuse. Here, we provide an introductory perspective on cloud computing to help the reader determine its value to their own research.

Lost in the Clouds? Cloud Storage Fits into Media Workflows—Just Not Everywhere

Within the media and entertainment space, the question businesses face with respect to cloud infrastructure is not whether to use it but how best to use it. Public cloud storage provides flexible, on-demand storage capacity and an operating expense financial model. While moving media post-production workflows entirely into “The Cloud” would solve content storage, sharing, and distribution challenges, there are limitations and cost implications. Cloud storage has attributes that make it perfectly suited for some workflow stages and perfectly ill-suited for others. The use of private cloud is adding another dimension to this tiered storage approach, offering many advantages. This paper describes a multitier storage strategy that maximizes the cost, access, and performance benefits of different types of storage with a particular focus on the most appropriate and beneficial uses of private and public cloud. It covers how the right storage and data management technology can aid media companies in making the most of all tiers of storage including cloud infrastructures.

Simple Atomic Quantum Memory Suitable for Semiconductor Quantum Dot Single Photons.

Quantum memories matched to single photon sources will form an important cornerstone of future quantum network technology. We demonstrate such a memory in warm Rb vapor with on-demand storage and retrieval, based on electromagnetically induced transparency. With an acceptance bandwidth of δf=0.66 GHz, the memory is suitable for single photons emitted by semiconductor quantum dots. In this regime, vapor cell memories offer an excellent compromise between storage efficiency, storage time, noise level, and experimental complexity, and atomic collisions have negligible influence on the optical coherences. Operation of the memory is demonstrated using attenuated laser pulses on the single photon level. For a 50ns storage time, we measure η_{e2e}^{50 ns}=3.4(3)% end-to-end efficiency of the fiber-coupled memory, with a total intrinsic efficiency η_{int}=17(3)%. Straightforward technological improvements can boost the end-to-end-efficiency to η_{e2e}≈35%; beyond that, increasing the optical depth and exploiting the Zeeman substructure of the atoms will allow such a memory to approach near unity efficiency. In the present memory, the unconditional read-out noise level of 9×10^{-3} photons is dominated by atomic fluorescence, and for input pulses containing on average μ_{1}=0.27(4) photons, the signal to noise level would be unity.

Fog Computing: The Essential Catalyst for Optimising the True Potential of Cloud-Based Internet of Things

With the rise and accretion of smart devices, particularly mobile phones, wearable gadgets and sensors, it brings us to a new era of computing technology known as Internet of things (IoT) to many. The IoT includes smart machines interacting with other machines, environments and infrastructures, which results massive increase in the volume of digitally generated data. To alleviate the burden of limited storage capacity of a device, cloud computing is considered a growing paradigm, which provides on-demand storage and other services to the end user. However, despite the numerous applications where cloud helps in accelerating the IoT growth around physical world, there are some application scenarios still not getting benefits from this emerging computing platform. Some of cloud computing fundamental problems like unacceptable latency, incapable for location awareness services, lack of mobility support, unnecessary network bandwidth consumption and undefined security issues from third party and others are reasons for its rejection in some interactive and real-time applications. To conquer this issue, Cisco defines a new uprising computing perspective named fog computing, which extends cloud computing to the edge of networks, which create scope for new applications and services for billions of connected devices. This research article is divided into three parts, in the first part, the author has enlighten the concept of IoT and discusses why cloud computing is considered an important success boosting factor behind the popularity of IoT. The second part discusses the concept of fog computing, and its need and motivation along with its main characteristics. In the last part, a general model of fog infrastructure is presented, which explains the types of application that can take benefits from fog computing, and finally, conclusion of the paper is provided.