This seminar explores the physical, behavioral, and computational limits of crowd-assembly for problem-solving.
We consider online task computing environments such as volunteer computing platforms running on BOINC (e.g., SETI@home) and crowdsourcing platforms such as Amazon’s Mechanical Turk. We model the computations as an Internet-based task computing system under the master-worker paradigm. A master entity sends tasks across the Internet, to worker entities willing to perform a computational task.
After a number of years of its launch, OpenFlow does not yet provide deployable alternatives but it has fully changed the conceptual approach to manage and control networks.
The second wave of cloud computing, named network cloudification, in the forms of SDN (Software Defined Networking), NFV (Network Function Virtualization), and 5G-MEC (Mobile Edge Computing), is to centralize and virtualize networking into data centers.
The 'big data' scene has brought new improvement opportunities to most products and services, including education. Web-based learning has become very widespread over the last decade, which in conjunction with the MOOC phenomenon, it has enabled the collection of large and rich data samples regarding the interaction of students with these educational online environments.
Wireless communication is not only a key technology underlying the mobile revolution, it is also used to connect, monitor, alert, and interact with physical infrastructures such as smart-grids, transportation networks, and even implantable devices.
Cisco estimates that by 2019 traffic will be 64x than in 2005. Network caching can help cope with this traffic deluge as, by replicating content closer to the users, it reduces bandwidth consumption.
Crowdsourced signal monitoring systems are gaining attention for capturing the wireless spectrum at large geographical scale. Yet, most of the current systems are still limited to simple power spectrum measurements reported by each sensor.
Mobile cellular networks are complex system whose behavior is characterized by the superposition of several random phenomena, most of which, related to human activities, such as mobility, communications and network usage. However, when observed in their totality, the many individual components merge into more deterministic patterns and trends start to be identifiable and predictable.
Collecting data generated by widespread digital transactions is an increasingly common practice. The likes of telecommunication network operators, mobile service providers, app developers and financial companies have the possibility to track the movements, preferences, activities and habits of large populations of individuals.
