Battery Swapping Station

State-of-the-art research to solve the grid congestion due to EVs is focused on smart charging and using (centralized, de-centralized, vehicle-to-grid) stationery energy storage as a buffer between times of peak and off-peak demand. On the other hand, the charging of EVs introduces new challenges and opportunities. This can prove to be beneficial for the EV aggregator as well as to consumers, regarding the economy. Also, EV as distributed storage makes the grid more steady, secure, and resilient by regulating frequency and the spinning reserve as backup power. However, the charging time and range anxiety lead to peak challenges for the use of EVs. In this chapter battery swapping station (BSS) as solution to the EV charging station is discussed.

Rectangular, range, and restricted AONTs: Three generalizations of all-or-nothing transforms

<p style='text-indent:20px;'>All-or-nothing transforms (AONTs) were originally defined by Rivest [<xref ref-type="bibr" rid="b14">14</xref>] as bijections from <inline-formula><tex-math id="M1">\begin{document}$ s $\end{document}</tex-math></inline-formula> input blocks to <inline-formula><tex-math id="M2">\begin{document}$ s $\end{document}</tex-math></inline-formula> output blocks such that no information can be obtained about any input block in the absence of any output block. Numerous generalizations and extensions of all-or-nothing transforms have been discussed in recent years, many of which are motivated by diverse applications in cryptography, information security, secure distributed storage, etc. In particular, <inline-formula><tex-math id="M3">\begin{document}$ t $\end{document}</tex-math></inline-formula>-AONTs, in which no information can be obtained about any <inline-formula><tex-math id="M4">\begin{document}$ t $\end{document}</tex-math></inline-formula> input blocks in the absence of any <inline-formula><tex-math id="M5">\begin{document}$ t $\end{document}</tex-math></inline-formula> output blocks, have received considerable study.</p><p style='text-indent:20px;'>In this paper, we study three generalizations of AONTs that are motivated by applications due to Pham et al. [<xref ref-type="bibr" rid="b13">13</xref>] and Oliveira et al. [<xref ref-type="bibr" rid="b12">12</xref>]. We term these generalizations rectangular, range, and restricted AONTs. Briefly, in a rectangular AONT, the number of outputs is greater than the number of inputs. A range AONT satisfies the <inline-formula><tex-math id="M6">\begin{document}$ t $\end{document}</tex-math></inline-formula>-AONT property for a range of consecutive values of <inline-formula><tex-math id="M7">\begin{document}$ t $\end{document}</tex-math></inline-formula>. Finally, in a restricted AONT, the unknown outputs are assumed to occur within a specified set of "secure" output blocks. We study existence and non-existence and provide examples and constructions for these generalizations. We also demonstrate interesting connections with combinatorial structures such as orthogonal arrays, split orthogonal arrays, MDS codes and difference matrices.</p>

The interplay of different metrics for the construction of constant dimension codes

<p style='text-indent:20px;'>A basic problem for constant dimension codes is to determine the maximum possible size <inline-formula><tex-math id="M1">\begin{document}$ A_q(n,d;k) $\end{document}</tex-math></inline-formula> of a set of <inline-formula><tex-math id="M2">\begin{document}$ k $\end{document}</tex-math></inline-formula>-dimensional subspaces in <inline-formula><tex-math id="M3">\begin{document}$ \mathbb{F}_q^n $\end{document}</tex-math></inline-formula>, called codewords, such that the subspace distance satisfies <inline-formula><tex-math id="M4">\begin{document}$ d_S(U,W): = 2k-2\dim(U\cap W)\ge d $\end{document}</tex-math></inline-formula> for all pairs of different codewords <inline-formula><tex-math id="M5">\begin{document}$ U $\end{document}</tex-math></inline-formula>, <inline-formula><tex-math id="M6">\begin{document}$ W $\end{document}</tex-math></inline-formula>. Constant dimension codes have applications in e.g. random linear network coding, cryptography, and distributed storage. Bounds for <inline-formula><tex-math id="M7">\begin{document}$ A_q(n,d;k) $\end{document}</tex-math></inline-formula> are the topic of many recent research papers. Providing a general framework we survey many of the latest constructions and show the potential for further improvements. As examples we give improved constructions for the cases <inline-formula><tex-math id="M8">\begin{document}$ A_q(10,4;5) $\end{document}</tex-math></inline-formula>, <inline-formula><tex-math id="M9">\begin{document}$ A_q(11,4;4) $\end{document}</tex-math></inline-formula>, <inline-formula><tex-math id="M10">\begin{document}$ A_q(12,6;6) $\end{document}</tex-math></inline-formula>, and <inline-formula><tex-math id="M11">\begin{document}$ A_q(15,4;4) $\end{document}</tex-math></inline-formula>. We also derive general upper bounds for subcodes arising in those constructions.</p>

The development of the system for arc nordugrid based grid-computing organization using virtual environments of the docker platform

The study of modern frameworks and means of using virtualization in a grid environment confirmed the relevance of the task of automated configuration of the environment for performing tasks in a grid environment. Setting up a task execution environment using virtualization requires the implementation of appropriate algorithms for scheduling tasks and distributed storage of images of virtual environments in a grid environment. Existing cloud infrastructure solutions to optimize the process of deploying virtual machines on computing resources do not have integration with the Arc Nordugrid middleware, which is widely used in grid infrastructures. An urgent task is to develop tools for scheduling tasks and placing images of virtual machines on the resources of the grid environment, taking into account the use of virtualization tools. The results of the implementation of services of the framework are presented that allow to design and perform computational tasks in a grid environment based on ARC Nordugrid using the virtual environment of the Docker platform. The presented results of the implementation of services for scheduling tasks in a grid environment using a virtual computing environment are based on the use of a scheduling algorithm based on the dynamic programming method. Evaluations of the effectiveness of the solutions developed on the basis of a complex of simulation models showed that the use of the proposed algorithm for scheduling and replicating virtual images in a grid environment can reduce the execution time of a computational task by 88 %. Such estimates need further refinement; it is predicted that planning efficiency will increase over time with an increase in the number of running tasks due to the redistribution of the storage of virtual images

A Review of Groundwater Management Models with a Focus on IoT-Based Systems

Globally, groundwater is the largest distributed storage of freshwater and plays an important role in an ecosystem&rsquo;s sustainability in addition to aiding human adaptation to both climatic change and variability. However, groundwater resources are dynamic and often change as a result of land usage, abstraction, as well as variation in climate. To solve these challenges, many conventional solutions, such as certain numerical techniques, have been proffered for groundwater modelling. The global evolution of the Internet of Things (IoT) has enhanced the culture of data gathering for the management of groundwater resources. In addition, efficient data-driven groundwater resource management relies hugely on information relating to changes in groundwater resources as well as their availability. At the moment, some studies in the literature reveal that groundwater managers lack an efficient and real-time groundwater management system that is needed to gather the required data. Additionally, the literature reveals that the existing methods of collecting data lack the required efficiency to meet computational model requirements and meet management objectives. Unlike previous surveys, which solely focussed on particular groundwater issues related to simulation and optimisation management methods, this paper seeks to highlight the current groundwater management models as well as the IoT contributions.

En-AR-PRNS: Entropy-Based Reliability for Configurable and Scalable Distributed Storage Systems

Storage-as-a-service offers cost savings, convenience, mobility, scalability, redundant locations with a backup solution, on-demand with just-in-time capacity, syncing and updating, etc. While this type of cloud service has opened many opportunities, there are important considerations. When one uses a cloud provider, their data are no longer on their controllable local storage. Thus, there are the risks of compromised confidentiality and integrity, lack of availability, and technical failures that are difficult to predict in advance. The contribution of this paper can be summarized as follows: (1) We propose a novel mechanism, En-AR-PRNS, for improving reliability in the configurable, scalable, reliable, and secure distribution of data storage that can be incorporated along with storage-as-a-service applications. (2) We introduce a new error correction method based on the entropy (En) paradigm to correct hardware and software malfunctions, integrity violation, malicious intrusions, unexpected and unauthorized data modifications, etc., applying a polynomial residue number system (PRNS). (3) We use the concept of an approximation of the rank (AR) of a polynomial to reduce the computational complexity of the decoding. En-AR-PRNS combines a secret sharing scheme and error correction codes with an improved multiple failure detection/recovery mechanism. (4) We provide a theoretical analysis supporting the dynamic storage configuration to deal with varied user preferences and storage properties to ensure high-quality solutions in a non-stationary environment. (5) We discuss approaches to efficiently exploit parallel processing for security and reliability optimization. (6) We demonstrate that the reliability of En-AR-PRNS is up to 6.2 times higher than that of the classic PRNS.

A Review of Groundwater Management Models with a Focus on IoT-Based Systems

Globally, groundwater is the largest distributed storage of freshwater and plays an important role in an ecosystem’s sustainability in addition to aiding human adaptation to both climatic change and variability. However, groundwater resources are dynamic and often change as a result of land usage, abstraction, as well as variation in climate. To solve these challenges, many conventional solutions, such as certain numerical techniques, have been proffered for groundwater modelling. The global evolution of the Internet of Things (IoT) has enhanced the culture of data gathering for the management of groundwater resources. In addition, efficient data-driven groundwater resource management relies hugely on information relating to changes in groundwater resources as well as their availability. At the moment, some studies in the literature reveal that groundwater managers lack an efficient and real-time groundwater management system which is needed to gather the required data. Additionally, the literature reveals that the existing methods of collecting data lack the required efficiency to meet computational model requirements and meet management objectives. Unlike previous surveys, which solely focussed on particular groundwater issues related to simulation and optimisation management methods, this paper seeks to highlight the current groundwater management models as well as the IoT contributions.