When: Wednesday, January 24, 2018
Where: PGH 563
Time: 11:00 AM

The Complexity of Leader Election: A Chasm at Diameter Two

Speaker: Soumyottam Chatterjee

Leader election is one of the fundamental problems in distributed computing. In its implicit version, only the leader must know who is the elected leader. This work focuses on studying the message complexity of leader election in synchronous distributed networks, in particular, in networks of diameter two. For graphs of diameter two, the complexity was not known. In this work, we settle this complexity by showing a tight bound of Θ̃(n) on the message complexity of leader election in diameter-two networks.

Bio:

Soumyottam Chatterjee is a 3rd year PhD student working with Dr. Gopal Pandurangan. He is interested in the design and analysis of algorithms, especially in the domain of distributed computing.

A Framework for Transactive Grids for Cities, Neighborhoods, and Homes

Speaker: Nacer Khalil

With the advent of renewable energies, the electricity grid suffers from both peak consumption and peak production. The research community has been developing scalable microgrids that manage the power production and consumption in households and communities. However, many of the current approaches manage the power consumption and allocation in a centralized fashion. These solutions are not flexible as they do not take into consideration the user's preferences. In this study, we propose a hierarchical model where the decision is dispatched to the lower layers and build a solution from the bottom-up. We estimate the power consumed at the appliance level and estimate the benefit generated by the appliance and propagate it to the home level and then to the neighborhood level. This approach makes the system more able to cope with changes in power consumption and production and takes the users' preference into consideration. We evaluate our approach in a simulation environment and based on real user data.

Bio:

Nacer Khalil is a fifth year PhD Candidate advised by Professor Omprakash Gnawali. He is interested in sensor networks, signal processing, and machine learning.