Analysis the Impact of Game theory (Pay-off Matrix, Nash Equilibrium) in the High Tech Industry: AI – Digital Assistant

International audienceIn this paper we are going to discuss and analysis the formal application of game theory which require the identity of independent actors, their preferences, their knowledge, strategic acts they are allowed to make. Each independent actor is assumed to be coherent. This game theory is not limited to case analysis rather psychology, tag of war, business, economy etc. Our focus is to use the game theory in information technology more specifically in Artificial Inelegance, Digital Assistant solution. Analysis the outcomes of game theory to determine the strategy for market penetration. The study however reveals some challenges such as affordance, access to information, cost advantage and subsidy or support or funding that change the total game of the deployment plan in order not to exacerbate the problem of digital divide

Cooperative Scheduling of Bag-of-Tasks Workflows on Hybrid Clouds

We address the problem of scheduling a class of large-scale applications inspired from real-world on hybrid Clouds, characterized by a large number of homogeneous and concurrent tasks that are the main sources of bottlenecks but open great potential for optimization. We formulate the scheduling problem as a new sequential cooperative game and propose a communication- and storage-aware multi-objective algorithm that optimizes two user objectives (execution time and economic cost) while fulfilling two constraints (network bandwidth and storage requirements). We present comprehensive experiments using both simulation and real-world applications that demonstrate the efficiency and effectiveness of our approach in terms of algorithm complexity, make span, cost, system-level efficiency, fairness, and other aspects compared with other related algorithms.(VLID)2217955Accepted versio

Cooperative Scheduling of Bag-of-Tasks Workflows on Hybrid Clouds

We address the problem of scheduling a class of large-scale applications inspired from real-world on hybrid Clouds, characterized by a large number of homogeneous and concurrent tasks that are the main sources of bottlenecks but open great potential for optimization. We formulate the scheduling problem as a new sequential cooperative game and propose a communication- and storage-aware multi-objective algorithm that optimizes two user objectives (execution time and economic cost) while fulfilling two constraints (network bandwidth and storage requirements). We present comprehensive experiments using both simulation and real-world applications that demonstrate the efficiency and effectiveness of our approach in terms of algorithm complexity, make span, cost, system-level efficiency, fairness, and other aspects compared with other related algorithms.(VLID)2217955Accepted versio