The present disclosure relates to the field of digital information storage. In particular, the present disclosure provides a system and method for optimizing storage of huge volume of digital information using block-chaining.
BACKGROUND
[0002] Background description includes information that may be useful in understanding the present disclosure. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed disclosure, or that any publication specifically or implicitly referenced is prior art. [0003] Internet-of-things applications often involve generation and storage of large volume of digital information from different types of sensing devices, facilitated to measure a plurality of attributes like temperature, humidity, water level and the likes. The massive streaming data is usually stored on a cloud server using block-chain technology for security. Management of storage space due to big size and periodic nature of availability of information is a challenging task in view of secured and fast data retrieval. Therefore there is need in the art to develop a system and method for storage space optimization. [0004] Existing literature includes description of internet-of-things based secure and robust information storage by block-chaining technology. Another disclosure deals with information acquisition from IoT devices and implementation of block-chains by reducing transmission delay. Enhancing predictive accuracy of rapid information transaction using flexible block-chain configurations have been discussed in another literature. Publication on transmission, reception and recording techniques of block-chained information based on internet-of-things is also available. A disclosure dealing with identity authorization system for failsafe authentication and data privacy on block-chain is available in the state-of-the-art. However, none of these literatures disclose an optimized determination of storage space on the block-chain in the cloud servers in response to massive streaming information.

[0005] Hence there is need in the art to develop a system and a method for information storage optimization for IoT based sensor information. The proposed system and method discusses the functional steps of a processing unit enabled to perform data acquisition, compression, encryption and storage on the block-chain and decryption of compressed and encrypted information using a private key. The processing unit is configured to perform storage space optimization based on a set of parameters and select a suitable hashing algorithm from a set of hash functions, prior to processing and transaction of acquired sensor information.
OBJECTS OF THE PRESENT DISCLOSURE
[0006] Some of the objects of the present disclosure, which at least one
embodiment herein satisfies are as listed herein below.
[0007] It is an object of the present disclosure to provide a system for
optimizing information storage, the information pertaining to huge volume of
streaming datasets generated by internet-of-things applications.
[0008] It is an object of the present disclosure to provide a system for
optimizing information storage, the storage pertaining to cloud server.
[0009] It is an object of the present disclosure to provide a system for
optimizing information storage that includes a processing unit communicatively
coupled to one or more cloud servers and one or more sensing devices through a
communication network.
[0010] It is an object of the present disclosure to provide a method for
optimizing information storage, the storage being related to block-chain
technology.
[0011] It is an object of the present disclosure to provide a method for
optimizing information storage that enables the processing unit to extract
information from the one or more sensing devices enabled to periodically measure
a plurality of attributes.
[0012] It is an object of the present disclosure to provide a method for
optimizing information storage that enables the processing unit to compare

performance of a set of hash functions and correspondingly select a suitable hash
algorithm for transaction of received information on to the block-chain.
[0013] It is an object of the present disclosure to provide a method for
optimizing information storage that enables the processing unit to compress the
received information from the one or more sensing devices and encrypt them
using the selected hash function.
[0014] It is an object of the present disclosure to provide a method for
optimizing information storage that enables the processing unit to transmit the
compressed and encrypted data sets to the one or more cloud servers for secure
retrieval using a private decrypting key.
[0015] It is an object of the present disclosure to provide a method for
optimizing information storage that enables the processing unit to determine
optimized storage space associated with the one or more cloud servers.
SUMMARY
[0016] The present disclosure relates to the field of digital information
storage. In particular, the present disclosure provides a system and method for
optimizing storage of huge volume of digital information using block-chaining.
[0017] An aspect of the present disclosure is to provide a system for
optimizing information storage, the information pertaining to huge volume of
streaming datasets that may be generated by one or more sensing devices.
[0018] In an aspect, the information storage may pertain to one or more cloud
servers.
[0019] In an aspect, the system may include a processing unit
communicatively coupled to the one or more cloud servers and the one or more
sensing devices through a communication network.
[0020] In an aspect, the information storage may be related to block-chain
technology.
[0021] In an aspect, the processing unit may be enabled to extract information
from the one or more sensing devices that may be configured to periodically
measure a plurality of attributes.

[0022] An aspect of the present disclosure is to provide a method for
optimizing information storage that may enable the processing unit to compare
performance of a set of hash functions and correspondingly select a suitable hash
algorithm for transaction of received information on to the block-chain.
[0023] In an aspect, the processing unit may be configured to compress the
received information from the one or more sensing devices and encrypt them
using the selected hash function.
[0024] In an aspect, the processing unit may be configured to transmit the
compressed and encrypted data sets to the one or more cloud servers for secure
retrieval using a private decrypting key.
[0025] In an aspect, the processing unit may be enabled to determine
optimized storage space associated with the one or more cloud servers.
BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS
[0026] The accompanying drawings are included to provide a further understanding of the present disclosure, and are incorporated in and constitute a part of this specification. The drawings illustrate exemplary embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure.
[0027] The diagrams described herein are for illustration only, which thus are not limitations of the present disclosure, and wherein:
[0028] FIG. 1 illustrates exemplary network architecture (100) of the proposed system for information storage optimization, to elaborate upon its working in accordance with an embodiment of the present disclosure. [0029] FIG. 2 illustrates exemplary functional components (200) of a processing unit (102) of the proposed system for information storage optimization, in accordance with an embodiment of the present disclosure. [0030] FIG. 3A-3C illustrates exemplary functional steps (300) of the proposed method for information storage optimization to elaborate upon its working in accordance with an embodiment of the present disclosure.

[0031] FIG. 4 illustrates exemplary steps (400) of the proposed method of information storage optimization, in accordance with an embodiment of the present disclosure.
DETAILED DESCRIPTION
[0032] In the following description, numerous specific details are set forth in
order to provide a thorough understanding of embodiments of the present
invention. It will be apparent to one skilled in the art that embodiments of the
present invention may be practiced without some of these specific details.
[0033] If the specification states a component or feature "may", "can",
"could", or "might" be included or have a characteristic, that particular component
or feature is not required to be included or have the characteristic.
[0034] As used in the description herein and throughout the claims that
follow, the meaning of "a," "an," and "the" includes plural reference unless the
context clearly dictates otherwise. Also, as used in the description herein, the
meaning of "in" includes "in" and "on" unless the context clearly dictates
otherwise.
[0035] While embodiments of the present invention have been illustrated and
described in the accompanying drawings, the embodiments are offered only in as
much detail as to clearly communicate the disclosure and are not intended to limit
the numerous equivalents, changes, variations, substitutions and modifications
falling within the spirit and scope of the present disclosure as defined by the
appended claims.
[0036] The present disclosure relates to the field of digital information
storage. In particular, the present disclosure provides a system and method for
optimizing storage of huge volume of digital information using block-chaining.
[0037] FIG. 1 illustrates exemplary network architecture (100) of the
proposed system for information storage optimization, to elaborate upon its
working in accordance with an embodiment of the present disclosure.
[0038] In an embodiment, the system for information storage optimization
(100) (interchangeably known as the system (100), herein) may include a

processing unit (102) communicatively coupled to one or more cloud servers (104) and one or more sensing devices (108-1,108-2,...,108-N) (collectively referred to as sensing devices (108), and individually referred to as sensing device (108), herein) associated with internet-of-things applications through a communication network (106).
[0039] In an embodiment, the one or more cloud servers (104) may include a computing device, a computer a laptop, an industrial asset, a mainframe and the likes associated with storage or memory and an application program for user interaction. By way of example, the one or more cloud servers (104) may correspond to sensor databases for critical monitoring of time-lapse applications. [0040] In an embodiment, the one or more sensing devices (108) may be enabled to measure and monitor a plurality of attributes pertaining to any or a combination of air quality, humidity, temperature, water level, voltage level, dust concentration and the likes. The plurality of attributes may be measured independent of each other and under predefined environmental conditions. In an embodiment, the one or more sensing devices (108) may include a thermocouple, a magnetic float sensor, a resistance temperature detector, an infrared sensor, a voltmeter, a potential transformer, an energy meter, a power meter, a current transformer, a hygrometer, a barometer, a photometer and the likes. [0041] In an embodiment, the network (106) for communication may include any or a combination of Wireless local area network (WLAN), Wide area network (WAN), Wireless fidelity (Wi-fi), Worldwide interoperability for microwave access (WiMAX), cellular communication network, Internet, and the likes. The communication network (106) may be a wireless network, a wired network or a combination thereof that may be implemented as one of the different types of networks, such as Intranet, Local Area Network (LAN), Wide Area Network (WAN), Internet, and the likes. Further, the communication network (106) may either be a dedicated network or a shared network. The shared network may represent an association of the different types of networks that may use variety of protocols, for example, Hypertext Transfer Protocol (HTTP), Transmission

Control Protocol/Internet Protocol (TCP/IP), Wireless Application Protocol (WAP) and the likes.
[0042] In an embodiment the system (100) may include a processing unit (102) that may be configured to receive sensor information from one or more sensing devices (108). The sensor information may be extracted, compressed and encrypted using a suitable secure hash algorithm by the processing unit (102). The processing unit (102) may be enabled to generate a decryption key for decrypting the encrypted sensor datasets by an authorized user. The encrypted datasets may be stored on the block-chain and further transmitted to one or more cloud servers (104) through the communication network (106).
[0043] FIG. 2 illustrates exemplary functional components (200) of a processing unit (102) of the proposed system for information storage optimization, in accordance with an embodiment of the present disclosure. [0044] In an embodiment, the processing unit (102) may include one or more processor(s) (202). The one or more processor(s) (202) may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that manipulate data based on operational instructions. Among other capabilities, the one or more processor(s) (202) may be configured to fetch and execute computer-readable instructions stored in a memory (204) of the processing unit (102). The memory (204) may store one or more computer-readable instructions or routines, which may be fetched and executed to create or share the data units over a network service. The memory (204) may comprise any non-transitory storage device including, for example, volatile memory such as RAM, or non-volatile memory such as EPROM, flash memory, and the like.
[0045] In an embodiment, the processing unit (102) may also comprise an interface(s) (206). The interface(s) (206) may comprise a variety of interfaces, for example, interfaces for data input and output devices, referred to as I/O devices, storage devices, and the like. The interface(s) (206) may facilitate communication of the processing unit (102) with various components coupled to the system (100) such as the one or more electoral servers (108), the one or more unique

identification servers (104), the one or more user devices (110) through the communication network (106). The interface(s) (206) may also provide a communication pathway for one or more components of the processing unit (102). Examples of such components include, but are not limited to, memory (204) and the database (222).
[0046] In an embodiment, the processing engine(s) (208) of the processing unit (102) may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the first processing engine(s) (208). In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processing engine(s) (208) may be processor-executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processing engine(s) (208) may comprise a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the processing engine(s) (208). In such examples, the processing unit (102) may comprise the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to the processing unit (102) and the processing resource. In other examples, the processing engine(s) (208) may be implemented by electronic circuitry. [0047] In an embodiment, the processing engine (208) may include a data acquisition unit (210) that may be configured to receive sensor information from one or more sensing devices (108) associated with internet-of-things applications. The data acquisition unit (210) may be enabled to extract a first set of data packets from the received sensor information. The first set of data packets may pertain to the plurality of attributes measured and monitored by the one or more sensing devices (108). By way of example, the data acquisition unit (210) may have one or more channels for parallel reception of sensor information. Each of the reception channels may be configured to receive the first set of data packets

through serial transmission, the transmission rate being pre-determined and synced between the one or more processors (202) and the one or more sensing devices (108).
[0048] In an embodiment, the processing engine (208) may include an optimization unit (212) that may be configured to determine optimized storage space pertaining to the one or more cloud servers (104) at the current time, based on any or a combination of a set of secure hash algorithms, types of IoT application, information streaming rate, level of security required and the likes. The one or more processors (022) may be enabled to compare and analyze optimized performance of the set of secure hash functions based on a predefined set of predetermined properties, the set of predetermine properties being computation time, maximum usability of available space, amount of compression, secure decryption and information retrieval, complexity and the likes. In an exemplary embodiment, the one or more processors (202) may be configured to select a secure hash function based on the comparison and analysis. By way of example hash functions like SHA-1, SHA-2, NTLM, LANMAN, MD5, SHA-256 and the likes may be used by the optimization unit (212).
[0049] In an embodiment, the processing engine (208) may include a data compression unit (214) that may be configured to compress the first set of data packets using the selected hash algorithm and correspondingly generate a second set of data packets. The first and the second set of data packets may be in computer readable digital form. Lossless data compression algorithms like but not limited to any or a combination of LZ77, ZSS, DEFLATE, LZMA, LZMA2, CNN, ANN and GAN methods may be used by the data compression unit (214). [0050] In an embodiment, the processing engine (208) may include an encryption-decryption unit (216) that may be configured to encrypt the compressed information for optimized storage and correspondingly generate a third set of data packets. The third set of data packets pertain to encrypted information. The one or more processors may also be enabled to generate a fourth set of data packets pertaining to a decryption key for decrypting the stored encrypted information by an authorized user, the user being provided by a private

decryption key upon authentication. By way of example, the encryption algorithms may include methods like but not limited to Triple DES, RSA, AES, Twofish, Blowfish, IDEA, MD5 and HMAC. The private key for decryption of the stored information may include but may not be limited to private signature key, symmetric authentication key, private authentication key, symmetric data encryption key, symmetric key wrapping key, symmetric master key, private key transport key, private static key and private authorization key. [0051] In an embodiment, the processing engine (208) may include a data transaction unit (218) that may be configured to transmit the third set of data packets pertaining to hashing based compressed and encrypted sensor information to a block-chain database. In an exemplary embodiment, the block-chain may be implemented on the one or more cloud servers (104). The one or more processors (202) may be enabled to retrieve the third and the fourth set of data packets from the one or more cloud servers (104) and transmit the third and the fourth set of data packets to authorized users. The third and the fourth set of data packets may be in computer readable digital form.
[0052] In an embodiment, the processing engine (208) may include other units (220) that may be configured to implement functionalities that supplement actions performed by the one or more processors (202) of the processing unit (102). In an exemplary embodiment, such actions may include noise removal from the extracted sensor information, converting analog sensor readings into computer readable digital form, authenticating users for reception of the decryption key and the likes.
[0053] FIG. 3A-3C illustrates exemplary views and functional steps (300) of the proposed method for information storage optimization to elaborate upon its working in accordance with an embodiment of the present disclosure. [0054] In an illustrative embodiment, FIG. 3A represents exemplary views of the one or more sensing devices (108-1, 108-2,..., 108-6), the one or more sensing devices (108) pertaining to measurement and monitoring of a set of attributes corresponding to one or more IoT applications. In an embodiment in FIG. 3B , at step (302) the one or more processors (not shown) of the processing unit (not

shown) may be enabled to perform data acquisition from the one or more sensing devices (108). At step (304), the one or more processors (not shown) may be configured to determine a secure hash function upon comparison of performance analysis of a set of hash functions based on a predetermined set of properties. At step (306), the one or more processors may be configured to perform compression and encryption of sensor information extracted from the one or more sensing devices using the selected hash algorithm for optimizing storage space of the one or more cloud servers (not shown) communicatively coupled to the one or more processors.
[0055] In an illustrative embodiment in FIG 3C, at step (308) the compressed and encrypted sensor information may be transmitted to a block-chain on one or more cloud servers (not shown). By way of example, at step (310), the one or more processors may be configured to analyze the stored sensor information using application programs such as ThinkSpeak. At step (312), the one or more processors may be enabled to retrieve the stored information from the one or more cloud servers and facilitate decrypting the encrypted information using a private key, the private key being transmitted to the authenticated user. [0056] FIG. 4 illustrates exemplary steps (400) of the proposed method of information storage optimization, in accordance with an embodiment of the present disclosure.
[0057] In an embodiment, the proposed method for information storage optimization may include a step (402) pertaining to extraction of the first set of data packets from the sensor information received from one or more sensing devices (108). The first set of data packets may pertain to a plurality of attributes measured and monitored by the one or more sensing devices (108). By way of example, the plurality of attributes may pertain to any or a combination of air quality, humidity, temperature, water level, voltage level, dust concentration and the likes. The plurality of attributes may be measured independent of each other and in a predefined environmental conditions.
[0058] In an embodiment, the proposed method for information storage optimization may include a step (404) pertaining to comparing and analyzing

performance of a set of secure hash functions based on the predefined set of properties. By way of example, the predefined set of properties may include but may not be limited to maximum usability of available space, amount of compression, secure decryption and information retrieval, complexity and the likes.
[0059] In an embodiment, the proposed method for information storage optimization may include a step (406) pertaining to selecting a secure hash function based on the comparison and analysis corresponding to any or a combination of type of internet-of-things application, storage space available in the one or more cloud servers (104) and level of security required. The selected secure hash algorithm may be applied by the one or more processors (202) to the extracted first set of data packets for transaction of the sensor information on to the block-chain residing in the one or more cloud servers (104). [0060] In an embodiment, the proposed method for information storage optimization may include a step (408) pertaining to compressing the first set of data packets using the selected secure hash algorithm and correspondingly generating a second set of data packets. By way of example, the second set of data packets may be generated without loss of critical information. The second set of data packets may have a predetermined length, the length being dependent on the selected secure hash algorithm and the predetermined length being crucial to storage space optimization.
[0061] In an embodiment, the proposed method for information storage optimization may include a step (410) pertaining to encrypting of the second set of data packets and correspondingly generating a third and a fourth set of data packets. The third set of data packets may pertain to the encrypted information and the fourth set of data packets may pertain to a decrypting key corresponding to the third set of data packets. In an exemplary embodiment, AES and SHA-256 may be used to generate the third set of data packets. The fourth set of data packets may be private key, enabled to decrypt and decompress the compressed and encrypted sensor information.

[0062] In an embodiment, the proposed method for information storage optimization may include a step (412) that may pertain to transmitting of the third set of data packets to the one or more cloud servers (104) using a block-chain. In an exemplary embodiment, the storage may pertain to any or a combination of block-chain networks like public block-chain, private block-chain, consortium block-chain and hybrid block-chain.
[0063] In an embodiment, the proposed method for information storage optimization may include a step (414) pertaining to determination of optimized storage space associated with the one or more cloud servers (104) after the current block-chaining function. Depending on the available storage space and the level of security required one or more secure hash algorithms different from the current selection may be preferred for the next hashing based transaction. [0064] As used herein, and unless the context dictates otherwise, the term "coupled to" is intended to include both direct coupling (in which two elements that are coupled to each other contact each other) and indirect coupling (in which at least one additional element is located between the two elements). Therefore, the terms "coupled to" and "coupled with" are used synonymously. Within the context of this document terms "coupled to" and "coupled with" are also used euphemistically to mean "communicatively coupled with" over a network, where two or more devices are able to exchange data with each other over the network, possibly via one or more intermediary device.
[0065] The terms, descriptions and figures used herein are set forth by way of illustration only. Many variations are possible within the spirit and scope of the subject matter, which is intended to be defined by the following claims and their equivalents in which all terms are meant in their broadest reasonable sense unless otherwise indicated.
[0066] While the foregoing describes various embodiments of the invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof. The scope of the invention is determined by the claims that follow. The invention is not limited to the described embodiments, versions or examples, which are included to enable a person having ordinary skill

in the art to make and use the invention when combined with information and knowledge available to the person having ordinary skill in the art.
ADVANTAGES OF THE INVENTION
[0067] The present disclosure provides for a system for optimizing
information storage, the information pertaining to huge volume of streaming
datasets generated by internet-of-things applications.
[0068] The present disclosure provides for a system for optimizing
information storage, the storage pertaining to cloud server.
[0069] The present disclosure provides for a system for optimizing
information storage that includes a processing unit communicatively coupled to
one or more cloud servers and one or more sensing devices through a
communication network.
[0070] The present disclosure provides for a method for optimizing
information storage, the storage being related to block-chain technology.
[0071] The present disclosure provides for a method for optimizing
information storage that enables one or more processors of the processing unit to
extract information from the one or more sensing devices enabled to periodically
measure a plurality of attributes.
[0072] The present disclosure provides for a method for optimizing
information storage that enables the processing unit to compare performance of a
set of hash functions and correspondingly select a suitable hash algorithm for
transaction of received information on to the block-chain.
[0073] The present disclosure provides for a method for optimizing
information storage that enables the processing unit to compress the received
information from the one or more sensing devices and encrypt them using the
selected hash function.
[0074] The present disclosure provides for a method for optimizing
information storage that enables the processing unit to transmit the compressed
and encrypted data sets to the one or more cloud servers for secure retrieval using
a private decrypting key.

[0075] The present disclosure provides for a method for optimizing information storage that enables the processing unit to determine optimized storage space associated with the one or more cloud servers.

We Claim:

1. A system for storage optimization (100) of information generated by internet-of-things, the system comprising :
one or more processing units (102), communicatively coupled to one or more cloud servers (104) and one or more sensing devices (108) through a network (106), wherein the one or more processing units (102) comprise one or more processors (202) associated with a memory (204), the memory storing instructions executable by the one or more processors (202) and configured to:
extract, a first set of data packets from the one or more sensing devices (108), the first set of data packets pertaining to a plurality of attributes measured and monitored by the one or more sensing devices (108) ;
compare and analyze performance of a set of secure hash functions based on a predefined set of properties;
select a secure hash function based on the comparison and analysis corresponding to any or a combination of type of internet-of-things application, storage space available in the one or more cloud servers (104) and level of security required ;
compress the first set of data packets using the selected secure hash algorithm and correspondingly generate a second set of data packets;
encrypt the second set of data packets and correspondingly generate a third and a fourth set of data packets, wherein the third set of data packets pertain to encrypted information and wherein the fourth set of data packets pertain to a decrypting key corresponding to the third set of data packets;

transmit the third set of data packets to one or more cloud servers (104) using a block-chain;
determine optimized storage space associated with the one or more cloud servers (104).
2. The system (100) as claimed in claim 1, wherein the first set of data packets are generated periodically at a predetermined rate by the one or more sensing devices (108), wherein the first set of data packets are generated in a predefined sequence and wherein the first set of data packets are required to be stored in the one or more cloud servers (104), wherein storing the first set of data packets are done through block-chaining.
3. The system (100) as claimed in claim 1, wherein the plurality of attributes measured and monitored by the one or more sensing devices (108) pertain to any or a combination of air quality, humidity, temperature, water level, voltage level, dust concentration and the likes, wherein the plurality of attributes are measured independent of each other and in a predefined environmental conditions.
4. A method for storage optimization (100) of information generated by internet-of-things, the method comprising steps of:
extracting at one or more processors (202), a first set of data packets from the one or more sensing devices (108), the first set of data packets pertaining to a plurality of attributes measured and monitored by the one or more sensing devices (108) ;
comparing at the one or more processors (202) and analyzing performance of a set of secure hash functions based on a predefined set of properties;
selecting at the one or more processors (202), a secure hash function based on the comparison and analysis corresponding to any or a combination of type of internet-

of-things application, storage space available in the one or more cloud servers (104) and level of security required ;
compressing at the one or more processors (202), the first set of data packets using the selected secure hash algorithm and correspondingly generating a second set of data packets;
encrypting at the one or more processors (202), the second set of data packets and correspondingly generating a third and a fourth set of data packets, wherein the third set of data packets pertain to encrypted information and wherein the fourth set of data packets pertain to a decrypting key corresponding to the third set of data packets;
transmitting by the one or more processors (202), the third set of data packets to one or more cloud servers (104) using a block-chain;
determining at the one or more processors (202),
optimized storage space associated with the one or more
cloud servers (104).
5. The method as claimed in claim 4, wherein the fourth set of data packets
pertain to a private key, wherein the private key is transmitted to one or
more authorized entities, wherein the one or more authorized entities are
enabled to receive the third set of data packets from the one or more cloud
servers (104) and wherein the private key is utilized to decrypt the third set
of data packets by the one or more processors of the processing unit (102).