240 laying birds were procured and distributed randomly into four treatments and four replicate (15 birds each) which was fed one of the following experimental diets containing different levels of probiotics (Biomin IMBO) for seven weeks. 1-Basel diet (control groups), 2-Basel diet + 250 g/t, 3-Basel diet +500 g/t, 4-Basel diet +750 g/t feed respectively. As results was revealed, feed efficiency were improved significantly throughout the production periods (p < 0.01). Supplementations of diet with probiotics at 750 g/t feed improved feed efficiency during experimental periods significantly as compared to control groups (p < 0.01). Feed intake was kept constant at the levels of110g/day/hen throughout the experimental period. Egg production and Egg mass weight (g/hen/day) was shown an increasing trend during 2nd phase production by increasing the dietary levels of probiotics (p < 0.01). Nevertheless, egg production at 10th week remained non significant. Egg quality and quantity as well as blood cholesterol were not influenced by dietary supplementations of probiotics.
In this paper, using edge processing in IoT network ,a method to decide on task offloading to edge devices and improve management of consuming energy in network of edge devices is introduced. First, by defining the problem of maximizing utility and then by decomposing it based on the status of task offloading from end devices to smart gateway with the lowest battery consumption and the possible lowest use of the communication bandwidth, independent optimal models are obtained and then combining. Then the general problem of maximizing the usefulness and increasing the lifetime of the end devices with restrictions of processing time and energy resources will be obtained. Due to the unknown environment of the problem and how the end devices and the edge of the network, an iterative reinforcement learning algorithm is used to generate the optimal answer in order to maximize the utility gain.The results show the existence of processing overhead and network load with increasing number of devices. The proposed method, while improving energy consumption in existence of a small number of devices in end of edge, reduces latency and increases processing speed and maximizes system performance compared to the central cloud system. The operating efficiency of the whole system is improved by 36% and the energy consumption at the edge of the network is optimized by 12.5%. It should be noted that, with the addition of a large number of end devices, our method outperforms similar works.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.