Characterization of a Dominant Negative Mutant of the Cell Cycle Ubiquitin-conjugating Enzyme Cdc34

The yeast Saccharomyces cerevisiae CDC34 gene encodes a ubiquitin-conjugating enzyme that is required for the cell cycle G(1)/S transition. We show here that a dominant negative Cdc34 protein is generated by simultaneously replacing both Cys and Leu with Ser residues. Cys is an essential catalytic residue that forms a transient thiol ester with ubiquitin during catalysis, and Leu is highly conserved among all known ubiquitin-conjugating enzymes. Mutants that encode either an alanine or a serine at one or both of these two positions are inactive. Of these eight mutants, overexpression of CDC34-C95S,L99S in wild type strains was found to block cell growth. Although cells overexpressing Cdc34-C95S,L99S do not exhibit the characteristic multibudded phenotype of cdc34 temperature-sensitive or null mutants, this blockade is relieved by simultaneous overexpression of wild type Cdc34. Purified Cdc34-C95S,L99S protein can be shown to inhibit in vitro ubiquitination of the Cdc34-specific substrate, Cln2 protein. We suggest that Cdc34-C95S,L99S selectively sequesters a subset of Cdc34 substrates or regulators. These findings have implications for the structure/function relationships of ubiquitin-conjugating enzymes, and suggest a general method for identifying components and substrates of specific ubiquitination pathways of eukaryotes

Energy Efficient Scheduling of MapReduce Jobs

MapReduce is emerged as a prominent programming model for data-intensive computation. In this work, we study power-aware MapReduce scheduling in the speed scaling setting first introduced by Yao et al. [FOCS 1995]. We focus on the minimization of the total weighted completion time of a set of MapReduce jobs under a given budget of energy. Using a linear programming relaxation of our problem, we derive a polynomial time constant-factor approximation algorithm. We also propose a convex programming formulation that we combine with standard list scheduling policies, and we evaluate their performance using simulations.Comment: 22 page

Feasibility of Using Discriminate Pricing Schemes for Energy Trading in Smart Grid

This paper investigates the feasibility of using a discriminate pricing scheme to offset the inconvenience that is experienced by an energy user (EU) in trading its energy with an energy controller in smart grid. The main objective is to encourage EUs with small distributed energy resources (DERs), or with high sensitivity to their inconvenience, to take part in the energy trading via providing incentive to them with relatively higher payment at the same time as reducing the total cost to the energy controller. The proposed scheme is modeled through a two-stage Stackelberg game that describes the energy trading between a shared facility authority (SFA) and EUs in a smart community. A suitable cost function is proposed for the SFA to leverage the generation of discriminate pricing according to the inconvenience experienced by each EU. It is shown that the game has a unique sub-game perfect equilibrium (SPE), under the certain condition at which the SFA's total cost is minimized, and that each EU receives its best utility according to its associated inconvenience for the given price. A backward induction technique is used to derive a closed form expression for the price function at SPE, and thus the dependency of price on an EU's different decision parameters is explained for the studied system. Numerical examples are provided to show the beneficial properties of the proposed scheme.Comment: 7 pages, 4 figures, 3 tables, conference pape

Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches

Peer-to-peer (P2P) energy trading has emerged as a next-generation energy management mechanism for the smart grid that enables each prosumer of the network to participate in energy trading with one another and the grid. This poses a significant challenge in terms of modeling the decision-making process of each participant with conflicting interest and motivating prosumers to participate in energy trading and to cooperate, if necessary, for achieving different energy management goals. Therefore, such decision-making process needs to be built on solid mathematical and signal processing tools that can ensure an efficient operation of the smart grid. This paper provides an overview of the use of game theoretic approaches for P2P energy trading as a feasible and effective means of energy management. As such, we discuss various games and auction theoretic approaches by following a systematic classification to provide information on the importance of game theory for smart energy research. Then, the paper focuses on the P2P energy trading describing its key features and giving an introduction to an existing P2P testbed. Further, the paper zooms into the detail of some specific game and auction theoretic models that have recently been used in P2P energy trading and discusses some important finding of these schemes.Comment: 38 pages, single column, double spac