APPOL II


Open Problems



  • Given n_1 jobs of length p_1, n_2 jobs of length p_2, n_3 jobs of length p_3, given m machines, and a deadline D, does there exist a feasible schedule? (i.e. a schedule in which each job is scheduled nonpreemptively at some machine and completed no later than time D). Does there exist a polynomial-time algorithm to answer this question or is the problem NP-complete?


  • Wavelength conversion in optical networks

    Regarding the problem of computing small placements of converters in optical networks with shortest-path routings, we still do not have good approximation algorithms. Our results indicate that it is unlikely or at least highly non-trivial to obtain a constant factor approximation algorithm. Therefore, we believe that a promising direction for future research is to investigate whether there is an approximation algorithm achieving logarithmic approximation ratio.



  • Wavelength conversion in optical networks with dynamic routings

    Our work on optical networks with dynamic routings points to several interesting directions for future research. In particular, it would be interesting to develop algorithms for testing whether a placement of wavelength converters results in optimal capacity usage in networks with dynamic arbitrary or shortest-path routings. Also, the problem of computing small placements of converters in these networks is worth studying.



  • In the context of OVSF code assignment, we have been considering various online strategies. The only known strategy with constant competitive ratio needs an additional layer of codes. It is still open to find such a strategy exists, that guarantees a constant competitive ratio, without additional resources, and independent of the height of the code tree.


  • Broadcast Scheduling

    - Find a non-trivial approximation algorithm which does not use resource augmentation, so far from below only NP-hardness is known.
    - Experimental analysis: how do algorithms perform on real-world data (e.g. traces of Web-Servers).



  • Flows over Time

    - Close a gap: for the quickest multicommodity flow problem in the setting with constant transit times and where intermediate storage of flow is prohibited. From above a $2$-approximation algorithm has been given and from below it was shown that no FPTAS exists, unless $\P = \NP$. This gap seems particularly interesting, since the $2$-approximation is based on computing temporally repeated flows, which have a relatively simple structure; but no better ratio can be achieved with this technique.
    - Consider other models of flow-dependent transit times: devise a mathematical model that both captures real-world behavior as accurately as possible and can still be solved efficiently, even on large networks.



  • Customer-Provider Relationships in the Internet

    - Integrate other (frequent) commercial relationships into the setting.
    - Concerning connectivity issues: study special graph classes, search for fixed-parameter tractable algorithms, consider the multi-cuts and multiway-cuts problems.