|Plenary Talk 1: 16 May 2017, 09.00-09.45|
|Prof. Yunghsiang S. Han
School of Electrical Engineering & Intelligentization, Dongguan University of Technology, China
Reed-Solomon Codes on Security Applications
Recently, coding theory has found many applications on information security. In this talk we will introduce how (n; k) Reed-Solomon codes apply on secrete sharing, key distribution systems, and networked distributed (big data) storage.
We start from a generalization of Shamir’s famous (k; n) threshold scheme on secrete sharing, where any k or more users who pool their secret shares may easily recover the initial secret S but any group of users knowing only
k-1 or fewer shares may not.
Then we pay attention to a forgotten key distribution scheme, Blom’s scheme, which has found to be useful in wireless sensor networks. During an initialization stage of key distribution, a base station generates and distributes secret data values to sensors and then any pair of sensors may compute a shared key unknown to all others aside from the base station. Blom’s scheme guarantees that any coalition of k-1 or fewer sensors can do no better at computing the key shared by the two than a party which guesses the key without any secret data values. Each sensor only carries k secret data values in Blom’s scheme.
Recently, organizations need to manage, process, and store huge amounts
of data. Since these data are large and complex, they are very difficult to process, manage, and store by traditional database tools and data processing applications. Large data centers with storage nodes (disks) have been built to store “big data.” One critical requirement of a data center is to assure data integrity. Due to the use of commodity software and hardware, crashstop and Byzantine failures (or attacks) are likely to be more prevalent in today’s large-scale data centers or distributed storage systems. Regenerating codes have been shown to be a more efficient way to disperse information
across multiple storage nodes and recover crash-stop failures in the literature.
Finally, we introduce a class of error-correcting regenerating codes based on Reed-Solomon codes . Error-correcting regenerating codes are not only capable of resisting crash-stop failures but also Byzantine attacks.
|Plenary Talk 2: 16 May 2017, 10.15-11.00|
|Prof. Sangarapillai Lambotharan
The Head of Signal Processing and Networks Research Group at Loughborough University, UK
Game Theory and its Applications in Wireless Communications and Sensing Systems.
With the development of the Internet of Things and an abundance of sensors, it is expected that the number of connected devices will reach 50 billion globally by 2020. All these devices will need to operate in a radio congested environment and will compete for the scarce frequency spectrum. This competition for resources between fixed and mobile users presents major challenges to future generation wireless systems and needs a mathematical framework for its solution. Likewise, in emergent wireless networks and sensor systems, there is competitive demand for higher data rates, efficient spectrum utilization and autonomous operation.
The talk presents the successful application of game theoretic methods in economics, political science and evolutionary biology, to embed strategic operation in such wireless communications and sensing systems. In particular, the focus will be on the application of these methods to enable wireless and sensor systems to adapt to changes in their environment, optimise operational parameters in a distributed manner and interact strategically to mitigate disturbances caused by malicious transmitters. The talk will be concluded by presenting a collection of current and future application scenarios including 5G networks, distributed radars, smart grids and data mining.
|Plenary Talk 3: 16 May 2017, 11.00-11.45|
|Prof Tom J Moir
School of Engineering, Computing and Mathematical Sciences
Auckland University of Technology (AUT), New Zealand
The hidden world of control-systems in digital signals and systems algorithms
There is an old saying that “East is east and West is West and never the twain shall meet”. The same can be said of control-systems and signal processing. The two subjects are often studied separately with no care as to how the two relate. This talk examines the relationships of negative feedback and stability and how it appears in some commonly (and some not so common) digital signal processing algorithms. For example, the idea of Steepest Descent was founded by Louis Augustin Cauchy, in his Compte Rendu `a l’Acad´emie des Sciences of October 18, 1847. At that time the theory of negative feedback was not developed until Maxwells paper on Governors (1868), and any explanation Maxwell gave was not immediately recognisable with the modern day Laplace-Transform operator methods we use. Yet the steepest descent method is the simplest and earliest example of a mathematical feedback-type algorithm. At the time it wasn’t greatly understood of course but forms the basis for the famous least-mean-squares algorithm (LMS) which is commonly used today. Even in 1960 when the LMS algorithm appeared, it’s recognition as a system with feedback was not exploited until over 20 years later. The speaker will explore such cases as steepest descent, matrix inversion, least-squares and spectral-factorization and show alternative approaches derived from a control-systems point of view. Moreover, it will be shown how the conventional algorithms can be improved by using no more than classical control theory.
|Tutorial: 16 May 2017, 13.00-15.00|
Dr. Eng. Khoirul Anwar
Center for Advanced Wireless Technologies (AdWiTech), School of Electrical Engineering,
Telkom University, Bandung, Indonesia
Challenges on Massive Internet of Things: Inspirations from Coding Theory
Applications based on the Internet of things (IoT) supported by Machine-type communication technologies are expected to grow exponentially. Forecasts indicate that the number of connected things will reach about 30 to 50 billion in 2020 reaching a ratio of human and machine closes to 1:7 or 1:10. This situation requires the development of efficient wireless technologies serving massive number of users or devices. We may also need to find new resources beyond frequency, time and space for 5G and 6G wireless networks.
Inspired by the recent development of coding theory, this talk addresses a technique solving multiple access involving massive number of IoT devices, of which are not solved by the current technologies. We consider interference and dynamic fading channels as two new resources, where conventionally they are treated as ‘enemies’ in communication systems. Based on the concept of low density parity check (LDPC) codes, LT codes, Raptor codes, and turbo processing principle allowing slight computational complexity, we can improve the traffic of massive IoT networks about 10 times and even approaching the network capacity limit of future wireless networks, of which is higher than the conventional IoT technologies, e.g., pure ALOHA, slotted ALOHA, pure carrier sense multiple access with collision avoidance (CSMA/CA) and slotted CSMA/CA.