Related papers: A Fast Lightweight Time-Series Store for IoT Data
The integration of Internet of Things (IoT) devices in healthcare has revolutionized patient care by enabling real-time monitoring, personalized treatments, and efficient data management. However, this technological advancement introduces…
The Internet of Things(IoT) will revolutionize the Future Internet through ubiquitous sensing. One of the challenges of having the hundreds of billions of devices that are estimated to be deployed would be rise of an enormous amount of…
The proliferation of connected devices through Internet connectivity presents both opportunities for smart applications and risks to security and privacy. It is vital to proactively address these concerns to fully leverage the potential of…
The tremendous advancements in the Internet of Things (IoT) increasingly involve computationally intensive services. These services often require more computation resources than can entirely be satisfied on local IoT devices. Cloud…
Towards realizing an intelligent networked society, enabling low-cost low-energy connectivity for things, also known as Internet of Things (IoT), is of crucial importance. While the existing wireless access networks require centralized…
We demonstrate Castor, a cloud-based system for contextual IoT time series data and model management at scale. Castor is designed to assist Data Scientists in (a) exploring and retrieving all relevant time series and contextual information…
The growing adoption of IoT devices in our daily life is engendering a data deluge, mostly private information that needs careful maintenance and secure storage system to ensure data integrity and protection. Also, the prodigious IoT…
While Internet of Things (IoT) devices and sensors create continuous streams of information, Big Data infrastructures are deemed to handle the influx of data in real-time. One type of such a continuous stream of information is time series…
The rapid deployment of Internet of Things (IoT) applications leads to massive data that need to be processed. These IoT applications have specific communication requirements on latency and bandwidth, and present new features on their…
The Internet of Things (IoT) being a promising technology of the future is expected to connect billions of devices. The increased number of communication is expected to generate mountains of data and the security of data can be a threat.…
Resource management in Internet of Things (IoT) systems is a major challenge due to the massive scale and heterogeneity of the IoT system. For instance, most IoT applications require timely delivery of collected information, which is a key…
In the real time processing, a new emerging technology where the need of connecting smart devices with cloud through Internet has raised. IoT devices processed information is to be stored and accessed anywhere needed with a support of…
The spatiotemporal data generated by massive sensors in the Internet of Things (IoT) is extremely dynamic, heterogeneous, large scale and time-dependent. It poses great challenges (e.g. accuracy, reliability, and stability) in real-time…
The preservation of cultural heritage faces growing challenges from climate change, tourism pressure, and limited conservation resources. Existing monitoring solutions are often cost-prohibitive, proprietary, and inflexible, leaving many…
Offloading is a popular way to overcome the resource and power constraints of networked embedded devices, which are increasingly found in industrial environments. It involves moving resource-intensive computational tasks to a more powerful…
In the context of the Internet of Things (IoT), reliable and energy-efficient provision of IoT applications has become critical. Equipping IoT systems with tools that enable a flexible, well-performing, and automated way of monitoring and…
Internet of Things (IoT) devices will play an important role in emerging applications, since their sensing, actuation, processing, and wireless communication capabilities stimulate data collection, transmission and decision processes of…
As deep neural networks continue to expand and become more complex, most edge devices are unable to handle their extensive processing requirements. Therefore, the concept of distributed inference is essential to distribute the neural…
We present a record-breaking result and lessons learned in practicing TPCx-IoT benchmarking for a real-world use case. We find that more system characteristics need to be benchmarked for its application to real-world use cases. We introduce…
The growing complexity of Internet of Things (IoT) environments, particularly in cross-domain data sharing, presents significant security challenges. Existing data-sharing schemes often rely on computationally expensive cryptographic…