Today, fog and cloud computing environments can be used to further develop the Internet of Things (IoT). In such environments, task scheduling is very efficient for executing user requests, and the optimal scheduling of IoT task requests increases the productivity of the IoT-fog-cloud system. In this paper, a hybrid meta-heuristic (MH) algorithm is developed to schedule the IoT requests in IoT-fog-cloud networks using the Aquila Optimizer (AO) and African Vultures Optimization Algorithm (AVOA) called AO_AVOA. In AO_AVOA, the exploration phase of AVOA is improved by using AO operators to obtain the best solution during the process of finding the optimal scheduling solution. A comparison between AO_AVOA and methods of AVOA, AO, Firefly Algorithm (FA), particle swarm optimization (PSO), and Harris Hawks Optimization (HHO) according to performance metrics such as makespan and throughput shows the high ability of AO_AVOA to solve the scheduling problem in IoT-fog-cloud networks.

In this work, we provide a comprehensive survey of smart contract upgradability patterns using proxies. A primary characteristic of smart contracts on the Ethereum blockchain is that they are immutable once implemented, no changes can be made. Taking human error into account, as well as technology improvements and newly discovered vulnerabilities, there has been a need to upgrade these smart contracts, which may hold enormous amounts of Ether and hence become the target of attacks. Several such attacks have caused tremendous losses in the past, as well as millions of dollars in Ether which has been locked away in broken contracts. Thus far we have collected many upgradable proxy patterns and studied their features to build a comprehensive catalog of patterns. We present a summary of these upgradable proxy patterns which we collected and studied. We scraped the source code for approximately 100000 verified contracts from Etherscan.io, the most popular block explorer for Ethereum, out of which we extracted around 64k unique files - most containing multiple contracts. We have begun to automate the analysis of these contracts using the popular static analysis tool Slither, while at the same time implementing much more robust detection of upgradable proxies using this framework. Comparing the results of the original implementation to our own, we have found that approximately 70 percent of the contracts which were initially flagged as upgradeable proxies are false positives which we have eliminated.