A Network Coding Based Information Spreading Approach for Permissioned Blockchain in IoT Settings

Cebe, Mumin; Kaplan, Berkay; Akkaya, Kemal

doi:10.1145/3286978.3286984

Cited by 13 publications

(6 citation statements)

References 8 publications

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“…Zhang et al [97] proposed a similar approach, although not in a clustered network. Cebe et al [98] also used a coding technique to minimize the size of blocks before it is transmitted to other peers in the network. The authors, first of all, split a block into chunks.…”

Section: Data Layermentioning

confidence: 99%

A Survey on Network Optimization Techniques for Blockchain Systems

et al. 2022

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The increase of the Internet of Things (IoT) calls for secure solutions for industrial applications. The security of IoT can be potentially improved by blockchain. However, blockchain technology suffers scalability issues which hinders integration with IoT. Solutions to blockchain’s scalability issues, such as minimizing the computational complexity of consensus algorithms or blockchain storage requirements, have received attention. However, to realize the full potential of blockchain in IoT, the inefficiencies of its inter-peer communication must also be addressed. For example, blockchain uses a flooding technique to share blocks, resulting in duplicates and inefficient bandwidth usage. Moreover, blockchain peers use a random neighbor selection (RNS) technique to decide on other peers with whom to exchange blockchain data. As a result, the peer-to-peer (P2P) topology formation limits the effective achievable throughput. This paper provides a survey on the state-of-the-art network structures and communication mechanisms used in blockchain and establishes the need for network-based optimization. Additionally, it discusses the blockchain architecture and its layers categorizes existing literature into the layers and provides a survey on the state-of-the-art optimization frameworks, analyzing their effectiveness and ability to scale. Finally, this paper presents recommendations for future work.

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Section: Data Layermentioning

confidence: 99%

A Survey on Network Optimization Techniques for Blockchain Systems

et al. 2022

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“…The encoding process continues until certain stopping criteria are reached (e.g., feedback from other nodes or time out). There are quite a few papers on applying network coding for consensus; see [ 44 , 45 ]. Since there is no significant difference between the consensus process of the global variables of ADMM or other types of messages, interested readers are referred to these papers for further reading.…”

Section: Coding For Admmmentioning

confidence: 99%

Coding for Large-Scale Distributed Machine Learning

Xiao

Skoglund

2022

Entropy

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This article aims to give a comprehensive and rigorous review of the principles and recent development of coding for large-scale distributed machine learning (DML). With increasing data volumes and the pervasive deployment of sensors and computing machines, machine learning has become more distributed. Moreover, the involved computing nodes and data volumes for learning tasks have also increased significantly. For large-scale distributed learning systems, significant challenges have appeared in terms of delay, errors, efficiency, etc. To address the problems, various error-control or performance-boosting schemes have been proposed recently for different aspects, such as the duplication of computing nodes. More recently, error-control coding has been investigated for DML to improve reliability and efficiency. The benefits of coding for DML include high-efficiency, low complexity, etc. Despite the benefits and recent progress, however, there is still a lack of comprehensive survey on this topic, especially for large-scale learning. This paper seeks to introduce the theories and algorithms of coding for DML. For primal-based DML schemes, we first discuss the gradient coding with the optimal code distance. Then, we introduce random coding for gradient-based DML. For primal–dual-based DML, i.e., ADMM (alternating direction method of multipliers), we propose a separate coding method for two steps of distributed optimization. Then coding schemes for different steps are discussed. Finally, a few potential directions for future works are also given.

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“…Cebe et al proposed a method of applying network coding to transmit sensing data using blockchain technology in the IoT environment. In the proposed scheme, blockchain technology has a large amount of computation and blocks, and the overhead of a long time delay is involved, whereas network coding technology transmits data packets by combining them, which helps to solve the problem of blockchain by increasing throughput [19].…”

Section: Related Workmentioning

confidence: 99%

Attack Detection Using Network Coding in IoT Environment

Yong¹,

Lee

2020

Sensors

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Network coding is a reasonable way to increase network efficiency in response to an increase of sensed data in the Internet of Things (IoT). In network coding, intermediate nodes combine packets received from neighboring nodes, transform, and transmit encoded packets that can be decoded at the destination. This scheme is based on trust among nodes. If any malicious node joins the network, it can act as an intermediate node that could fabricate encoded packets. It might be more difficult to identify the authenticity of such encoded packets since packets that are received at the destination might not originate from a single source, but be combined with several other packets originating from multiple sources. In this paper, we propose a scheme on how to detect attacked packets among the received packets at a destination and how to recover the original message from the packets including the attacked “look-like-valid” packets. This scheme shows that a destination could recover the valid message with just the received packets including some attacked packets and will result in a quite efficient performance in network coding.

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A Network Coding Based Information Spreading Approach for Permissioned Blockchain in IoT Settings

Cited by 13 publications

References 8 publications

A Survey on Network Optimization Techniques for Blockchain Systems

A Survey on Network Optimization Techniques for Blockchain Systems

Coding for Large-Scale Distributed Machine Learning

Attack Detection Using Network Coding in IoT Environment

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