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... used the Grafana tool in Bluemix to monitor the resource consumption concerning CPU, memory and network usage. The results with median values can be seen in Figure 4. For the third case in the diagram we reset the message generation interval to 0.5 seconds, therefore we got 900 (denoted by 450x2) messages in every second. ...
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... There are several motivations to improve resource management in these federations, including serving more customers at once, improving service quality, increasing rental revenue, and lowering energy use and CO2 emissions. Although achieving low latency is the major objective, there are also new hurdles in real-time analytics, stream processing, power consumption, and security [12]. ...
This paper surveys the current state of data management in the Internet of Things (IoT). It begins by outlining the challenges and opportunities that data management in IoT presents. Firstly, data management deals with the technical challenges and solutions related to data management in IoT, including data acquisition, storage, and integration. The paper concludes with a set of recommendations for the development of effective data management strategies in the context of IoT. Secondly, the requirement of IoT for data management extends offline storage, query processing, and transaction management activities into online-offline communication and storage dual operations, and the idea of data management is broadened. This is accomplished by IPv6, as well as IoT-specific capabilities and protocols including CoAP, HTTP, and WebSocket. Users may track, monitor, and manage devices with Internet of Things (IoT) device management, ensuring that they operate effectively and securely after deployment. Finally, the paper discusses the various applications of IoT based on the concept of data management in IoT. Numerous more objects, including wearables, medical equipment, houses, cities, farms, industries, and workplaces, are being interacted with by billions of sensors. The IoT platforms assist in establishing and maintaining criteria to enhance and preserve data appropriately. The paper concludes with a set of recommendations for the development of effective data management strategies in the context of IoT. Smart gadgets automate processes so we may save time by controlling the environment. The most valuable data is protected by edge devices for data management, which also lowers bandwidth costs. These also offer excellent performance, data ownership, and cheap maintenance costs.
... There are several motivations to improve resource management in these federations, including serving more customers at once, improving service quality, increasing rental revenue, and lowering energy use and CO2 emissions. Although achieving low latency is the major objective, there are also new hurdles in real-time analytics, stream processing, power consumption, and security [12]. ...
This paper surveys the current state of data management in the Internet of Things (IoT). It begins by outlining the challenges and opportunities that data management in IoT presents. Firstly, data management deals with the technical challenges and solutions related to data management in IoT, including data acquisition, storage, and integration. The paper concludes with a set of recommendations for the development of effective data management strategies in the context of IoT. Secondly, the requirement of IoT for data management extends offline storage, query processing, and transaction management activities into online-offline communication and storage dual operations, and the idea of data management is broadened. This is accomplished by IPv6, as well as IoT-specific capabilities and protocols including CoAP, HTTP, and WebSocket. Users may track, monitor, and manage devices with Internet of Things (IoT) device management, ensuring that they operate effectively and securely after deployment. Finally, the paper discusses the various applications of IoT based on the concept of data management in IoT. Numerous more objects, including wearables, medical equipment, houses, cities, farms, industries, and workplaces, are being interacted with by billions of sensors. The IoT platforms assist in establishing and maintaining criteria to enhance and preserve data appropriately. The paper concludes with a set of recommendations for the development of effective data management strategies in the context of IoT. Smart gadgets automate processes so we may save time by controlling the environment. The most valuable data is protected by edge devices for data management, which also lowers bandwidth costs. These also offer excellent performance, data ownership, and cheap maintenance costs.
... Initially, we validated the SlowITe attack against Eclipse Mosquitto [63] MQTT server, for both plain text and SSL ports. Then, we tested the attack against other MQTT services such as ActiveMQ [65], HiveMQ [66] and VerneMQ [67], comparing obtained results in terms of efficacy and bandwidth requirements. ...
... Indeed, since the aim of SlowITe is to target the MQTT protocol, instead of a single software supporting such protocol, we executed the threat on different services. Particularly, as previously mentioned, we targeted ActiveMQ [65], HiveMQ [66] and VerneMQ [67], running on their default settings. ...
... We tested the attack on a real network, targeting real MQTT services based on Eclipse Mosquitto [63], ActiveMQ [65], HiveMQ [66] and VerneMQ [67] with an low-powerful node represented by a Raspberry PI. Tests were executed by first analyzing the behavior of the server on a single connection, in order to identify the potential exploitation of SlowITe, hence perpetrating real DoS attacks, based on plain text communication and encrypted communications as well. ...
Security of the Internet of Things is a crucial topic, due to the criticality of the networks and the sensitivity of exchanged data. In this paper, we target the Message Queue Telemetry Transport (MQTT) protocol used in IoT environments for communication between IoT devices. We exploit a specific weakness of MQTT which was identified during our research, allowing the client to configure the behavior of the server. In order to validate the possibility to exploit such vulnerability, we propose SlowITe, a novel low-rate denial of service attack aimed to target MQTT through low-rate techniques. We validate SlowITe against real MQTT services, considering both plain text and encrypted communications and comparing the effects of the threat when targeting different daemons. Results show that the attack is successful and it is able to exploit the identified vulnerability to lead a DoS on the victim with limited attack resources.
... After this initial version we continuously revised and improved it with additional features, and developed additional supporting tools, such as the trace archive and private gateways. The initial version of a private gateway to manage sensor data was presented in a conference [7] in the beginning of 2018. Since then we improved its device management features and scalability. ...
... ("Internet of Living Things"). This paper is a revised and extended version of the conference papers presented in [6] and [7]. This paper described the behavior and features of MobIoT-Sim version 1.3. ...
The Internet of Things (IoT) is the latest trend of the current ICT evolution, represented by a huge amount of powerful smart devices that have started to appear on the Internet. By responding to this new trend, many cloud providers have started to offer services for IoT management. Recent advances have already shown that cloud computing can be used to serve IoT needs by performing data generation, processing and visualization tasks. In this currently forming ecosystem, IoT system developers need to purchase, connect and configure these devices, and they also have to choose the right infrastructure provider offering the combination of protocols and data structures fitting their applications. In this paper, we propose a complex, semi-simulation environment that aims to provide a solution for these IoT challenges. Our main contribution is the the design of an Android-based, mobile IoT device simulator called MobIoTSim. We also propose a customizable cloud gateway to manage these devices by receiving, processing and visualizing sensor data coming from MobIoTSim. To be as close as possible to real world application, we created an IoT trace archive service called SUMMON, which can be used to gather real-world sensor data, which can be used by MobIoTSim. Finally, we demonstrate how to create IoT applications utilizing numerous IoT devices with this environment, and evaluate the device management scalability and responsiveness of its components.
