Improved Recovery Management and Routing in W-Grid, a Distributed Infrastructure for Effective and Efficient Multidimensional Data Management over Wireless Ad-Hoc Sensor Networks - Data Management in Cloud, Grid and P2P Systems - page 83

capabilities and the local learning with a new distance evaluation technique, a
routing technique that improves the average path length measures of W-Grid
networks.
Besides, the work has showed that in case of failures, W-Grid guarantees net-
work robustness while reducing the energy consumption with respect to existing
solutions that instead require broadcast/flooding propagations. In particular, the
simulations have measured both the ecacy and eciency of the routing method
and the recovery approach according to an extensive number of scenarios with
different radio connectivity density, with several logical network topology chang-
ing the number of coordinates and with the treatment of node failures.
The results have highlighted that the routing performance of GPSR and W-
Grid with local learning are quite similar despite GPSR requires GPS; finally
the new recovery approach drastically reduces the network trac while preserv-
ing the same recovery ecacy of solutions based on costly broadcast/flooding
operations.
Future work is manly oriented towards integrating W-Grid with novel
paradigms dictated by recent Big Data initiatives (e.g., [26,27]), perhaps in-
spired by approximation paradigms (e.g. [28,29]).
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