Abiotic stress is one of the severe stresses of environment that lowers the growth and yield of any crop even on irrigated land throughout the world. A major phytohormone abscisic acid (ABA) plays an essential part in acting toward varied range of stresses like heavy metal stress, drought, thermal or heat stress, high level of salinity, low temperature, and radiation stress. Its role is also elaborated in various developmental processes including seed germination, seed dormancy, and closure of stomata. ABA acts by modifying the expression level of gene and subsequent analysis of cis-and trans-acting regulatory elements of responsive promoters. It also interacts with the signaling molecules of processes involved in stress response and development of seeds. On the whole, the stress to a plant can be susceptible or tolerant by taking into account the coordinated activities of various stress-responsive genes. Numbers of transcription factor are involved in regulating the expression of ABA responsive genes by acting together with their respective cis-acting elements. Hence, for improvement in stresstolerance capacity of plants, it is necessary to understand the mechanism behind it. On this ground, this article enlightens the importance and role of ABA signaling with regard to various stresses as well as regulation of ABA biosynthetic pathway along with the transcription factors for stress tolerance.

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Large gathering events such as open air rock concerts and religious gatherings require a semipermanent communication and computation infrastructure for providing IoT-based smart solutions. In these places, the installation of wired network is not a cost-effective solution to provide connectivity. Wireless mesh network (WMN) presents itself as a quickly deployable and dismantable solution to provide wireless connectivity to IoT devices. In this paper, we have proposed a "wireless-fog mesh" computing framework for installation of microservices in network devices of WMN. This requires continuous monitoring of residual resources of devices and associated network characteristics. Our proposed fog controller exploits underutilized resources of mesh devices and network metrics for mapping a microservice to a fog node. This controller uses a DHT-based overlay of fog nodes (also acting as distributed MQTT broker) for disseminating resource profiles of fog nodes. The network metrics like path cost, routing loads, number of stations, and delay are used to implement a policy-based FNS algorithm for electing a fog node to run microservice. We have designed and implemented a testbed that consists of 10 OpenWrt-based Raspberry Pi3 node to form a WMN. We have deployed various microservices such as MQTT broker, air quality, web servers, annd video surveillance in fog nodes (mesh routers and access points) to test the FNS algorithm. The results establish that the FNS algorithm significantly outperforms the random node selection (RNS) algorithm and advocates the applicability of our wireless-fog mesh framework for semipermanent use cases.

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