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Blockchain technology is getting more and more pertinent to solve most of the digital problems that we face today. Blockchain is notable for its prominent features like immutability, decentralization, consensus, privacy, and security. However, blockchain is still suffering from different barriers like quantum attacks, scalability problems, integration problems, incompetence to face bigdata, storage problems, and so on. The main aim of this study was to find out the scope, various problems raised, and the applicability of blockchain technology when integrated with different computing paradigms like cloud computing, edge computing, fog computing, osmotic computing, big data computing, and quantum computing. To conduct this study, we have surveyed different research articles in the combination of blockchain technology and computing paradigms. Based on this survey, we have mentioned the contemporary research works, challenges, and a list of possible research opportunities and solutions.
blockchain, access control, computing paradigms, cloud, security
As a part of the Bitcoin cryptocurrency, "Satoshi Nakamoto" introduced the concept of blockchain 1.0. In the year 2015, with the advent of smart contracts in the Ethereum blockchain platform made blockchain 2.0 unconfined to the Bitcoin cryptocurrency. Later, many top MNC companies like Google, IBM, Microsoft, FedEx, Facebook, etc. started investments in developing blockchain solutions.
At present, blockchain helps to solve many digital problems that we face in our daily lives. To understand the proliferation of blockchain, in the paper [1], we have listed nine application categories with a total of 88 identified different blockchain applications.
In that paper [1], we have identified that 88 applications were implemented in one of the computing paradigms like cloud, edge, fog, osmotic, bigdata, and quantum computing paradigms. So we started our literature survey by identifying the implications of adopting blockchain along with different computing paradigms.
To write this survey paper, we have almost referred to 147 research articles published in the combination of computing paradigms and the blockchain. Here Figure 1 represents the time order of the literature survey, and Figure 2 represents the number of journals and conference articles referred.
As a summary of Figure 1 and Figure 2, we can understand that research on integrating computing paradigms with the blockchain and its applications is gaining more interest in the research community, but still there are so many research gaps.
The main aim of writing this survey paper is to highlight contemporary research works, challenges, and to list out the research gaps and possible research opportunities regarding blockchain appositeness in computing paradigms.
Figure 1. The time order of the literature survey
Figure 2. Number of journals and conference papers referred
In every section, we are going to mention contemporary research works, challenges, and list possible research opportunities. In Section 3, we have listed out different research works on the integration of the cloud and its services with blockchain. In Section 4, we have listed out some research works on the integration of edge computing with the blockchain framework. In Section 5, we discuss the feasibility of integrating blockchain with the fog computing concept. Section 6 is about combining osmotic computing with blockchain. In Section 7, we have listed out different research works on combining blockchain with big computing. In Section 8, we have listed out some research works on combining blockchain with quantum computing and quantum attacks on blockchain. In Section 9, we explain the blockchain inappropriateness in particular cases. Section 10 includes the survey analysis. Finally, Section 11 is about future work and the conclusion.
The comprehensive representation of blockchain applications in cloud computing are shown in Figure 3.
Figure 3. Comprehensive representation of blockchain applications in the cloud
When integrating blockchain with cloud, it is possible to overcome different cloud-related challenges like downtime, identifying data corruption, data security, limited access control, trust management issues, data sharing problems, and data privacy concerns.
Before integrating blockchain into the cloud, one should think of its characteristics and then decide its applicability to the cloud applications. Chan et al. [2] has given ten different characteristics and different requirement questions on the blockchain that can help anyone to decide about integration. These characteristics are immutable, data transparency, trust by smart contracts, individual identity, distribution of data, transactional system, permanent history of records, suitable for ecosystems and not for particular software, single backward-linked list, decentralized workflow architecture. But still, a few problems need to be addressed by research, among them
3.1 Blockchain combined with cloud storage
Centralized cloud storage is not secure and reliable for outsourced user data. Using a blockchain along with cloud storage will guarantee the security of user outsourced data. From the cloud storage perspective, blockchain is applied in different ways
Multiple data blocks with the same indexes will be considered as duplicates and removed from the cloud storage. But still, a few problems need to be addressed regarding the association of cloud storage along with blockchain, among them
3.2 Access control policies using blockchain
Controlling access to cloud assets is possible by defining the policies. There is a chance that a hostile cloud resource administrator or manager may tamper with these policies to grant illegitimate access and to pose unusual restrictions on legitimate users. Therefore, it is a dire need to protect these policies from such activities. Recently, the blockchain has emerged as a solution to protect these policies. Where policies are directly written into the blockchain. Some of the works on policy management using blockchain are listed below.
Apart from the above-mentioned methods, the research against the access control policy mechanism using the blockchain is still in the infancy.
3.3 Secure data sharing using blockchain
Data sharing through a cloud service provider is not entirely reliable and leads to different user privacy and quality issues. Choosing a blockchain is a considerable option to share data without the involvement of malicious third parties. Recent works that incorporated blockchain to share cloud data are
3.4 Achieving clouds data security using blockchain
Blockchain technology has become a promising alternative to confront different cloud data security issues because of features like immutability, distributed consensus algorithms, decentralized open ledger, using a hashing function. In this section, we are going to discuss a list of recent works that had incorporated blockchain for cloud data security:
It was reckoned that the number of connected IoT devices would be increased to 25 billion by the end of the year 2030. Almost 130 new IoT devices per second are connected to the internet. As the velocity of data is increasing, the quantities of data that need to be processed and transferred are also increasing. Conventional centralized cloud servers can be used to store and process data originating from IoT devices. Using a centralized cloud server creates different problems.
To overcome these problems, we can realize the distributed computing paradigm called “Edge computing”. In edge computing, instead of entirely relying on cloud services, most of the data storage and computing operations are moved and performed in the proximity of the IoT device or in the IoT device itself. When combined with the blockchain, we can even solve more problems related to edge computing. In this section, we are going to list out a few recent works on edge computing in the combination of blockchain:
In their model, computationally intensive tasks are offloaded to edge devices provided with storage and computational resources. Additionally, they have introduced the concept of dynamic block size to handle different requirements of video transcoding.
The synopsis of the above-mentioned recent works are listed in the Table 1.
Table 1. Recent works on Edge computing with Blockchain
Author |
Purpose |
Synopsis |
Varghese et al. [27] |
Integration Challenges |
|
Li et al. [30] |
|
|
Xiong et al. [33] |
|
|
Felix Freitag et al. [28] |
Resource sharing and utilization |
|
Xu. et al. [35] |
|
|
Zhang et al. [29]. |
Intensive computational problems |
|
Liu et al. [31] |
|
|
Liu et al. [32] |
Improving the performance of blockchain |
|
J. Zheng et al. [34] |
|
|
Seike et al. [38] |
|
|
Rahman et al. [36] |
Improving the Security |
|
Xu et al. [37] |
|
|
Ali Gauhar et al. [40] |
|
|
Kang et al. [38] |
Data sharing |
|
Fog computing is like a better version of edge computing. In edge computing, the storage and computational operations are carried out directly on edge devices. Edge computing has different cons like
Some of these problems can be solved using fog computing. Fog computing performs storage and computational operations on separate LAN-connected computers called Fog nodes. Fog nodes are equipped with more storage capacity and processing power when compared to edge devices. In turn, the fog node is connected to the cloud. Figure 4 explains the concept of Fog Computing.
Figure 4. Fog and Edge computing
Fog computing is a solution provided by the CISCO company. Its name is given like that because fog lies just below the cloud and nearer to the ground (edge devices). When combined with blockchain we can overcome security and privacy-related challenges. In the following section, we are going to list out a few recent works on the combination of fog computing and blockchain.
Table 2. Recent works on Fog computing with blockchain
Author |
Purpose |
Synopsis |
Lei et al. [41] |
Integration Challenges |
|
Baniata et al. [50] |
|
|
Yao et al. [42] |
Authentication Mechanisms |
|
Almadhoun et al. [43] |
|
|
Puthal et al. [53] |
|
|
Debe et al. [45] |
Reputation-based mechanisms |
|
Yu et al. [47] |
|
|
Cinque et al. [56] |
|
|
Alshehri et al. [46] |
Security |
|
George et al. [48] |
|
|
Wu et al. [49] |
|
|
Ziegler et al. [51] |
Simplifying Proof of Work (PoW) |
|
Kumar et al. [52] |
|
|
Lee et al. [54] |
|
|
Memon et al. [44] |
|
|
Yánez et al. [55] |
Data Management |
|
Tuning block parameters like block size, block interval is going to influence blockchain properties like consistency as well as performance. The Blockchain Proof of Work is also heavy for a fog node. These problems still need to be addressed when fog computing is integrated with blockchain
The synopsis of the above-mentioned recent works are listed in the Table 2.
Osmotic computing is a new computing paradigm inspired by the chemical osmosis process. In the chemical osmosis, process molecules move from a highly concentrated solution to a low concentrated solution to equalize the concentration of the entire solution.
Likewise, in osmotic computing micro services will be migrated to resource-constrained edge devices to the highly equipped cloud and vice versa is also possible [57].
Figure 5. Osmotic computing between the edge, cloud
Osmotic computing is used to establish extensively federated and highly distributed environments in the cloud and edge. Micro services are deployed as virtualized containers using container-based technologies e.g Docker. It inherits all challenges and issues related to the edge and cloud environments. Osmotic computing is explained in Figure 5.
The following are the merits possible by integrating blockchain along with osmotic computing:
Buzachis and Villari [58] implemented SDMem like Villari et al. [59] but with a private blockchain to ensure the integrity and ownership of data transferred and processed in micro services. A private blockchain is used to record all transactions related to micro services related to the cloud and edge.
Challenges on integration:
Generally, the blockchain supports linear data with a small size. Recently, many scholars applied blockchain for securing bigdata in different ways like
Abdullah et al. [63] has demonstrated the challenges and requirements necessary for bigdata authentication. The Bigdata tool Apache Hadoop uses Kerberos for the authentication process. Already Kerberos systems are facing different challenges like
Prerequisites of bigdata authentication
This entire list of requirements can be satisfied using a blockchain.
To handle data skewness, the MapReduce-based querying method is replaced with a blockchain based querying method. In this method, the Map phase output is stored in the blockchain and uses caching to render the results.
They have proposed the “Mystiko” blockchain-based storage built over a distributed database called Apache Cassandra. It is capable of handling big data and provides high transaction output.
Table 3. Recent works on Bigdata computing with blockchain
Author |
Purpose |
Synopsis |
Subbiah et al. [64] |
Integration Challenges |
|
Bandara et al. [71] |
|
|
Alexander et al. [65] |
|
|
Smith et al. [72] |
|
|
Preece et al. [73] |
|
|
Zhou et al. [74] |
Security |
|
Elena et al. [70] |
|
|
Zheng et al. [66] |
Data Management and Auditing |
|
Alexander et al. [65] |
Storage and Auditing |
|
Chen et al. [67] |
|
|
Yu et al. [68] |
|
|
Bandara et al. [71] |
|
The synopsis of the above-mentioned recent works are listed in the Table 3.
Quantum computing is rooted in the concept of physics quantum mechanics. In quantum mechanics, particles like a photon have a quality of spin during their travel. The spin, in the vertical position and forward diagonal position, is used to represent the binary bit “1”. And the spin, in horizontal position and backward diagonal position is used to represent the binary bit “0”.
Sometimes the spin position of a photon represents both “1” and “0” at the same time. This position is called “qubit”, and the property is called a “Superposition” of the photon. The same superposition property is used in quantum computing.
Traditional computers represent any data only by using 1’s and 0’s, whereas quantum computers represent data using 1, 0, and qubit. If we have “N” qubits, then we can represent 2N bits. For example, if we have 300 qubits, then we can represent 2300 bits that are almost equal to the number of particles in the world.
This property makes quantum computers and quantum computing very powerful. We can use quantum computers to solve so many complex problems in polynomial time.
8.1 Quantum attacks towards Blockchain
Attacks carried out using quantum computers are called quantum attacks. The majority of the cryptographic primitives employed inside the blockchain are vulnerable to quantum attacks because they depend upon the “Finite Abelian Group” methods like factorization of integers and discrete logarithms e.g. The RSA and Elliptical curve based signatures. Those methods can be resolved in polynomial time on quantum computers by implementing Fourier transformations (Table 4).
8.2 Safeguard mechanisms towards quantum attacks
To safeguard blockchain against quantum attacks, it is essential to re-equip the blockchain with quantum-resistant cryptography mechanisms. In this segment, we are going to list out some of the research involved in developing anti-quantum methodologies.
At present, lattice-based cryptography algorithms are mainly used as post-quantum cryptography to resist quantum attacks. At present, there are many variants of lattice-based signatures, like
In their paper, they have created a lightweight wallet based on bonsai trees and generated several private keys using a seed key.
In their paper, they have described a quantum-resistant parametric hash function algorithm that generates hashes using a large number of parameters.
Table 4. Recent works on integrating blockchain with quantum computing
Author |
Purpose |
Synopsis |
Peter Shor.[75] |
Quantum attacks on blockchain |
|
Grover. [76] |
|
|
Suhail et al. [77] |
|
|
Chao-Yang et al. [78] |
|
|
Kiktenko et al. [80], Nanda et al. [81] |
Quantum Key Distribution |
|
Jin et al. [82] |
Quantum Hashing |
|
Fernández-Caramés and Fraga-Lamas [84] |
|
|
Krendelev et al. [86] |
|
|
Yin et al. [79] |
Signature Based methods |
|
Yin et al. [83] |
|
|
Chalkias et al. [85] |
|
|
Suhail et al. [77] |
|
|
Ma and Jiang [87] |
|
Even though quantum computers are not real for now, by the year 2035, quantum computers may come into existence. By using quantum computers, one can fabricate and initiate different types of quantum attacks on cryptographic primitives belonging to the blockchain.
So there is a dire need for post-quantum cryptographic algorithms and techniques to prevent quantum attacks on the blockchain. Currently, there are very few works available on making blockchain quantum resistant.
One should not prefer blockchain because of its hype or due to its prominent features like immutability. One should understand its appositeness from different functional requirements of the application.
In this section, we are going to list out possible scenarios where the blockchain is not appropriate [88, 89].
Blockchain is not suitable for applications where validation of collected data is critical. Because using blockchain, we can make data immutable, but it doesn’t guarantee the correctness of data.
Based on the recent works mentioned in this survey paper, we have taken synopsis points from Figure 3 and synopsis points from Tables 1-4 of different computing paradigms to identify the most appropriate computing paradigm with the blockchain
Figure 6. Mapping Computing paradigms with blockchain
Therefore, from Figure 6. We can identify that most of the research innovation of blockchain technology is done along with cloud, Edge, and fog computing paradigms. It is also identified that the suitability of inducing blockchain with different computing paradigms depends upon the context of the application and the type of framework we have selected to implement blockchain.
The main focal point of this survey paper is to identify the scope of the blockchain and its appropriateness and inappropriateness. In this paper, as a part of a literature survey, we have identified challenges and possible research opportunities involved in the integration of blockchain with different computing paradigms. In future work, further, we want to survey the role of blockchain in data management, access control policies and we want to address some of the challenges that we have mentioned in this survey paper.
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