A Coggle Diagram about Contribution
, Integrate network awareness and tuple ranking in data acquisition systems for WSNs
, Improved the Quality of Data (QaD) for all queries executed over WSNs (accuracy and freshness)
and Linear scalable, modular and resilient to node and communication failure.
(Reconstruct the Routing Query Tree periodically either complementary or incrementally, instead of balancing only the initial tree.
, Extend ETC to support network semantics and compare to other approaches that do the same.
, A dynamic representation of the network topology is crucial to allow user mobility among WSNs.
and Develop the support for multi-query execution
(Is the Routing Query Tree an abstract representation of the Network Topology?
, What is the influence of dynamically adaptation of the Routing Query Tree into the user mobility?
, Why does ETC assume fixed workload for sensor nodes? Can we make it variable?
and Is the cost of running either a machine learning algorithm or a compression algorithm higher than the cost of data transmission?
, Tree Balancing
and Query processing
(Automatically tune the Routing Query Tree without any user intervention or any prior knowledge
, Transform the initial Routing Query Tree T into a near-balanced T' in a distributed manner
and Decrease the energy cost by introducing top-k queries into the query execution process
and Query Sets
(Routing Query Tree
and The energy consumption for transmitting 1 bit of data using MICA mote is approximately equivalent to processing 1000 CPU instructions.
) and Papers