Title Brief Description Member/s
Designing Scalable network for Internet Of Things Scalability is the key to handling the explosive growth in the IoT. With the increasing number of nodes, all the other components increase proportionally. The IoT applications must have the ability to support an increasing number of connected devices, users, application features, and analytics capabilities without any degradation in the QoS. Monitoring, securing, and managing an increasing number of devices require a proportionate increase in the resources. As a massive number of connections need to be maintained by a cloud server with the deployed devices, provisioning scalability in it is the primary concern. Networking and communicating such huge number of devices is another challenge of IoT. The objective of this work is to analyze the scalability issues over IoT. Nurzaman Ahmed
Provisioning Semantic Interoperability for Large-scale Internet of Things Internet of Things (IoT) is a new paradigm of communication aiming at integrating the state of everyday things into the digital world. But, things are everywhere, have different format, come in different semantics, so, building reliable applications that depend on such things imposes great challenges and demand for new approaches to integrating heterogeneous devices smoothly. From connected fridges, cars and cities, the IoT creates opportunities in numerous domains. The communication among these devices is enabled by different protocols and technologies. As these devices are designed by different companies with different standards and technologies there is an issue exists in their connectivity. Interoperability is a burning issue in providing seamless communication among various systems in heterogeneous IoT environment. Achieving semantic interoperability in such a diverse system is a great challenge for the researchers. Recently, several organizations and researchers have started working on semantic interoperability issues, however many issues are yet to get sufficient attention. Hafizur Rahman
Real time data mining in IoT/td> In any real world Internet of Things (IoT) scenario an exponential amount of data is created every second. In order to facilitate a wide array of applications and use the data efficiently; we must discover knowledge from the data. Knowledge discovery from databases (KDD) is otherwise known as data mining. In IoT the same needs to be done in real time. Real time data mining can help us to efficiently take Smart decisions without any Human intervention. Md. Saifur Rahman
Designing Lightweight Authentication scheme for 6LoWPAN based Internet of Things 6LoWPAN is a low power wireless personal area network (LoWPAN) with devices of IEEE 802.15.4 standard using IPv6. 6LoWPAN based network are widely used in Internet of Things (IoT) implementations. The large number of IoT devices need larger address space and auto-configuration which is provided by IPv6. Security is necessary in 6LoWPAN devices as they are always connected and accessible over untrusted Internet. When collecting data from multiple fragments, collated, analyzed, ensuring security to IoT devices becomes a major problem. IoT security protocols are different from the traditional security protocols because traditional security protocols needs more processing power and hence cannot be used in battery operated devices. Data authentication allows a receiver to verify whether the data is sent by the claimed sender or not. For example, local networks inside or outside the house can get access to sensitive information such as data metering or can change the dose of diabetic medicine endangering the lives of the residents. This means that the IoT network has to authenticate all devices. Leki chom Thungon
Data Analytics in Internet of Things using Machine Learning It sounds like impossible to connect everything on the earth together via internet, but Internet of Things (IoT) has change our life, by making many impossible possible. The basic idea of IoT is to connect all things in the world to the internet. The IoT is going to be the next technological revolution. Every moment IoT generates a massive amount of data which has a very high business value. Data Analytic (DA) algorithms can be applied to IoT data to extract hidden information from data. DA is defined as a process which is used to examine data sets with varying data properties to extract meaningful knowledge from these data sets. This knowledge are usually in the form of trends, patterns, and statistics that help business organizations in effective decision-making processes. Kishore Medhi
Enhancing end-point security using edge computing Edge computing is a method of optimizing cloud computing systems "by taking the control of computing applications, data, and services away from some central nodes (the "core") to the other logical extreme (the "edge") of the Internet" which makes contact with the physical world. In this architecture, data comes in from the physical world via various sensors, and actions are taken to change physical state via various forms of output and actuators; by performing analytics and knowledge generation at the edge, communications bandwidth between systems under control and the central data center is reduced. Ravinandan