MEMORY ANALYSIS FOR IPFS IMPLEMENTATION ON ETHEREUM SMART CONTRACT

Abstract. Smart contract is an agreement between two entities established in the program code. All Smart contract transactions are stored on the Blockchain. But storing large data on the Blockchain is expensive, so many developers are currently creating a DApp (Decentralized Application) that integrates IPFS on smart contract Ethereum. Files will be stored on IPFS while the Blockchain only stores hash files from IPFS to access them again. Blockchain & IPFS are distributed peer-to-peer technologies for storing and distributing digital data supported by the confidentiality, integrity and authenticity of the data. The study was conducted to measure memory usage to run the DApp web that integrates IPFS on smart contract Ethereum and find out the effect of the file size uploaded via the web DApp and the number of nodes connected in the network. The memory usage test results will be used as a standard for the memory capacity planning to implement a DApp web system that integrates IPFS on smart contract Ethereum in an organization. Based on the research result, to run a web DApp that integrates IPFS on a smart contract requires 774MB of memory. The result proves that IPFS is suitable for handling large files. The efficiency of DApp's web performance that integrates IPFS on the smart contract Ethereum are obtained by a small file size and a large number of nodes connected in a network. The smaller the file size, the less memory usage. The more nodes that are connected in the network, the less memory usage.Keywords: Decentralized Application, IPFS, Smart Contract Ethereum, Blockchain, Memory Usage

ANALYSIS AND IMPLEMENTATION OF NODES COMMUNICATION BETWEEN INTERPLANETARY FILE SYSTEM (IPFS) IN SMART CONTRACT ETHEREUM

Abstract. At present all business activities are bound to contracts or agreements. A written contract has several weaknesses, the contract can be lost and damaged, it is not cost effective and one party can commit fraud. The solution for that is to use the smart contract Ethereum. Smart contract Ethereum is a computer protocol that functions to facilitate, verify, or enforce digital negotiations written through the program code. Smart contract works without going through a third party and has a credible transaction process so that it cannot be tracked or changed. But Blockchain technology is not suitable for storing large amounts of data and expensive costs, the authors combine IPFS technology on Ethereum Blockchain. So the Ethereum Blockchain only stores the hash of the file, then the hash of this file can be connected to the file on IPFS to access it. In this study a web-based DApp (Decentralized applications) system was built that implemented IPFS on the smart contract Ethereum. The final result of this study is a discussion of data integrity and Quality of Service (QoS) communication between IPFS nodes on the smart contract Ethereum as a reference for implementation of the company. With the results of the implementation it  was found that the data integrity possessed by IPFS was very good by fulfilling aspects of information security and having Quality of Service with average throughput values of56.41 Kbps, 65.81 Kbps and 79.68 Kbps, for average packet loss values of 1.92%, 1.58% and 1.06%, while the average value of delay is 24.79 ms, 25.87 ms and 17.30 ms with the average value of the Quality of Service index which is 3 which meets the "Satisfying" category based on THIPON standards.Keywords: Blockchain, Smart Contract Ethereum, IPFS, Data Integrity, Quality of  Service (QoS

An improved back propagation leaning algorithm using second order methods with gain parameter

Back Propagation (BP) algorithm is one of the oldest learning techniques used by Artificial Neural Networks (ANN). It has successfully been implemented in various practical problems. However, the algorithm still faces some drawbacks such as getting easily stuck at local minima and needs longer time to converge on an acceptable solution. Recently, the introduction of Second Order Methods has shown a significant improvement on the learning in BP but it still has some drawbacks such as slow convergence and complexity. To overcome these limitations, this research proposed a modified approach for BP by introducing the Conjugate Gradient and QuasiNewton which were Second Order methods together with ‘gain’ parameter. The performances of the proposed approach is evaluated in terms of lowest number of epochs, lowest CPU time and highest accuracy on five benchmark classification datasets such as Glass, Horse, 7Bit Parity, Indian Liver Patient and Lung Cancer. The results show that the proposed Second Order methods with ‘gain’ performed better than the BP algorithm

A Hybrid Algorithm for Improving the Quality of Service in MANET

A mobile ad-hoc network (MANET) exhibits a dynamic topology with flexible infrastructure. The MANET nodes may serve as both host and router functionalities. The routing feature of the MANET is a stand-alone multi-hop mobile network that can be utilized in many real-time applications. Therefore, identifying paths that ensure high Quality of Service (QoS), such as their topology and applications is a vital issue in MANET. A QoS-aware protocol in MANETs aims to find more efficient paths between the source and destination nodes of the network and, hence, the requirements of the QoS. This paper proposes a different hybrid algorithm that combines Cellular Automata (CA) with the African Buffalo Optimization (ABO), CAABO, to improve the QoS of MANETs. The CAABO optimizes the path selection in the ad-hoc on-demand distance vector (AODV) routing protocol. The test results show that with the aid of the CAABO, the AODV manifests energy and delay-aware routing protocol

VANETs Multipath Video Data Streaming Considering Road Features

Multipath video streaming in Vehicular Ad-hoc Networks (VANETs) is an evolving research topic. The adoption of video transmission in VANETs communication has become essential due to the comprehensiveness and applicability of video data for on-road advertisement and infotainment. Meanwhile, several research studies have considered how to apply and improve the transmission of the video quality. Due to this, the concurrent multipath transmission has been employed in order to achieve load balancing and path diversity, because of the high data rate of the video data.  However, the main nature of the road, which is the pathway for VANET nodes has not been considered explicitly. In this paper, the road features are considered for VANETs multipath video streaming based on the greedy geographical routing protocol. Thus, VANETs Multipath Video Streaming based on Road Features (VMVS-RF) protocol has been proposed. The protocol was compared with an ordinary Multipath Video Streaming (MVS). The result demonstrates that the proposed VMVS-RF protocol outperforms the MVS in terms of Data Receiving Rate (DRR), Structural Similarity (SSIM) index and Packet Loss Ratio (PLR)

An Improved Back Propagation Leaning Algorithm using Second Order Methods with Gain Parameter

Back Propagation (BP) algorithm is one of the oldest learning techniques used by artificial neural networks (ANN). It has successfully been implemented in various practical problems. However, the algorithm still faces some drawbacks such as getting easily stuck at local minima and needs longer time to converge on an acceptable solution. Recently, the introduction of Second Order Methods has shown a significant improvement on the learning in BP but it still has some drawbacks such as slow convergence and complexity. To overcome these limitations, this research proposed a modified approach for BP by introducing the Conjugate Gradient and Quasi-Newton which were Second Order methods together with ‘gain’ parameter. The performances of the proposed approach is evaluated in terms of lowest number of epochs, lowest CPU time and highest accuracy on five benchmark classification datasets such as Glass, Horse, 7Bit Parity, Indian Liver Patient and Lung Cancer. The results show that the proposed Second Order methods with ‘gain’ performed better than the BP algorithm

Performance evaluation of AODV and OLSR routing protocols in MANET environment

Mobile Ad-hoc Networks (MANETs) are self-sufficient networks that can work without the need for centralized controls, pre-configuration to the routes or advance infrastructures. The nodes of a MANET are autonomously controlled, which allow them to act freely in a random manner within the MANET. The nodes can leave their MANET and join other MANETs at any time. These characteristics, however, might negatively affect the performance of the routing protocols and the overall topology of the networks. Subsequently, MANETs comprise specially designed routing protocols that reactively and proactively perform the routing. This paper evaluates and compares the performance of two routing protocols which are Ad-Hoc On-Demand Distance Vector (AODV) and Optimized Link State Routing (OLSR) in MANET environment. The study includes implementing a simulation to examine the performance of the routing protocols based on the variables of the nodes’ number and network size. The evaluation results show that the AODV outperforms the OLSR in most of the simulated cases. The results further show that the number of nodes and network size has a great impact on the Throughput (TH), Packet Delivery Ratio (PDR), and End-to-End delay (E2E) of the network

A hybrid algorithm for improving the quality of service in MANET

A mobile ad-hoc network (MANET) exhibits a dynamic topology with flexible infrastructure. The MANET nodes may serve as both host and router functionalities. The routing feature of the MANET is a stand-alone multi-hop mobile network that can be utilized in many real-time applications. Therefore, identifying paths that ensure high Quality of Service (QoS), such as their topology and applications is a vital issue in MANET. A QoS-aware protocol in MANETs aims to find more efficient paths between the source and destination nodes of the network and, hence, the requirements of the QoS. This paper proposes a different hybrid algorithm that combines Cellular Automata (CA) with the African Buffalo Optimization (ABO), CAABO, to improve the QoS of MANETs. The CAABO optimizes the path selection in the ad-hoc on-demand distance vector (AODV) routing protocol. The test results show that with the aid of the CAABO, the AODV manifests energy and delay-aware routing protocol