Impact of Evanescence Process on Three-Dimensional Sub-Diffusion-Based Molecular Communication Channel.

In most of the existing works of molecular communication (MC), the standard diffusion environment is taken into account where the mean square displacement (MSD) of an information molecule (IM) scales linearly with time. On the contrary, this work considers the sub-diffusion motion that appears in crowded and complex (porous or fractal) environments (movement of the particles in the living cells) where the particle's MSD scales as a fractional order power law in time. Moreover, we examine an additional evanescence process resulting from which the molecules can degrade before hitting the boundary of the receiver (RX). Thus, in this work, we present a 3D MC system with a point transmitter (TX) and the spherical RX with the sub-diffusive behavior of an IM along with its evanescence. Furthermore, an IM's closed-form expressions for the arrival probability and the first passage time density (FPTD) are emulated in the above context. Additionally, we investigate the performance of MC by using the concentration-based modulation technique in a sub-diffusion channel. Finally, the considered MC channel is exploited in terms of the probability of detection, probability of false alarm, and probability of error for different parameters such as the reaction rate, fractional power, and radius of the RX.

Making drug supply chain secure traceable and efficient: a Blockchain and smart contract based implementation.

The healthcare supply chain involves obtaining resources, managing supplies, and delivering goods and services to patients across multiple teams, stakeholders, and geographical boundaries. With such a complex structure, the healthcare supply chain is vulnerable to fraud, inaccurate data, and lack of transparency. These misdeeds cost businesses money and harm health. To address these issues, the health care supply chain needs an end-to-end decentralized track-and-trace system. Most centralized systems risk drug and data safety. This paper presents an Ethereum blockchain-based solution for a health care supply chain track-and-trace mechanism that uses smart contracts and data immutability. Hash functions store data in a public distributed ledger. This protects and discloses data. Smart contracts automate agreement execution so all parties know the outcome instantly, without an intermediary or time loss. It also outlined decentralized healthcare supply chain application architecture and algorithms. This paper proposes a system to address the lack of transparency and tracking in traditional supply chains. The blockchain-based method proposed in this paper runs on Solidity smart contracts. The system's algorithms and methods are tested against a variety of inputs, and the results are presented as an average gas cost for specific functionality. The proposed system tracks goods' histories (medicine). The average gas cost for all accounts is 18,027.2. Overall, log gas costs 48,118.6 to buy medicine, gas costs 229,607.5, and to log out 14,275.The results of the proposed system are compared to state-of-the-art methods. Thus, the presented work allows a seamless flow of medicines via blockchain and smart contracts without intermediaries. Finally, it addresses building a secure pharma supply chain application for blockchain 4.0.

On Gradient Descent Optimization in Diffusion-Advection Based 3-D Molecular Cooperative Communication.

This work considers a cooperative communication system in 3-D fluid medium in which the flow of molecules is supported by the drift and the diffusion phenomena. To enhance the system performance, the equal gain combining is used at the destination nanomachine (DN) where the molecular signals arriving from the direct and the cooperative paths are combined together by employing equal weights. Using the gradient descent algorithm, the optimum threshold at DN, and the optimal number of molecules transmitted from source and cooperative nanomachines are obtained. For this purpose, the convex constraints are determined using the closed-form expression for the average probability of error at DN. Finally, the accuracy of the analytical results is validated through the particle/ Monte Carlo-based simulations.

Optimal Transmitted Molecules and Decision Threshold for Drift-Induced Diffusive Molecular Channel With Mobile Nanomachines.

We study a drift-induced diffusive mobile molecular communication system where source, destination and cooperative nanomachines follow the one-dimensional Brownian motion. For information exchange from source nanomachine to receiver nanomachine, both direct and decode-forward (DF) relay-assisted cooperative paths are considered. The closed-form expressions for the probabilities of detection and false alarm are derived at the cooperative and destination nanomachines considering the multiple-source interference (MSI) and the inter-symbol-interference (ISI). The closed-form expressions for end-to-end average probability of error, and maximum achievable rate are also obtained. Moreover, to achieve minimum expected probability of error the optimum number of molecules to be transmitted from transmitter and optimal detection threshold in receiver nanomachine are found. The analytical expressions are validated through particle-based and Monte-Carlo simulation methods.