  Many packing, scheduling and covering problems that were previously
considered by computer science literature in the context of various
transportation and production problems, appear also suitable for describing and
modeling various fundamental aspects in networks optimization such as routing,
resource allocation, congestion control, etc. Various combinatorial problems
were already studied from the game theoretic standpoint, and we attempt to
complement to this body of research.
  Specifically, we consider the bin packing problem both in the classic and
parametric versions, the job scheduling problem and the machine covering
problem in various machine models. We suggest new interpretations of such
problems in the context of modern networks and study these problems from a game
theoretic perspective by modeling them as games, and then concerning various
game theoretic concepts in these games by combining tools from game theory and
the traditional combinatorial optimization. In the framework of this research
we introduce and study models that were not considered before, and also improve
upon previously known results.
