BRIDGING THE SNMP GAP: SIMPLE NETWORK MONITORING THE INTERNET OF THINGS

Things that form Internet of Things can vary in every imaginable aspect. From simplest devices with barely any processing and memory resources, with communication handled by networking devices like switches and routers to powerful servers that provide needed back-end resources in cloud environments, all are needed for real world implementations of Internet of Things. Monitoring of the network and server parts of the infrastructure is a well known area with numerous approaches that enable efficient monitoring. Most prevalent technology used is SNMP that forms the part of the IP stack and is as such universally supported. On the other hand, “things” domain is evolving very fast with a number of competing technologies used for communication and monitoring. When discussing small, constrained devices, the two most promising protocols are CoAP and MQTT. Combined, they cover wide area of communication needs for resource constrained devices, from simple messaging system to one that enables connecting to RESTful world. In this paper we present a possible solution to bridge the gap in monitoring by enabling SNMP access to monitoring data obtained from constrained devices that cannot feasibly support SNMP or are not intended to be used in such a manner

Monitoring self-adaptive applications within edge computing frameworks: A state-of-the-art review

Recently, a promising trend has evolved from previous centralized computation to decentralized edge computing in the proximity of end-users to provide cloud applications. To ensure the Quality of Service (QoS) of such applications and Quality of Experience (QoE) for the end-users, it is necessary to employ a comprehensive monitoring approach. Requirement analysis is a key software engineering task in the whole lifecycle of applications; however, the requirements for monitoring systems within edge computing scenarios are not yet fully established. The goal of the present survey study is therefore threefold: to identify the main challenges in the field of monitoring edge computing applications that are as yet not fully solved; to present a new taxonomy of monitoring requirements for adaptive applications orchestrated upon edge computing frameworks; and to discuss and compare the use of widely-used cloud monitoring technologies to assure the performance of these applications. Our analysis shows that none of existing widely-used cloud monitoring tools yet provides an integrated monitoring solution within edge computing frameworks. Moreover, some monitoring requirements have not been thoroughly met by any of them