Previously all blocks that were already in our chain were never re
announced as potential uncle block (e.g. ChainSideEvent). This is
problematic during mining where you want to gather as much possible
uncles as possible increasing the profit. This is now addressed in this
PR where during reorganisations of chains the old chain is regarded as
uncles.
Fixed#2298
Assuming the following scenario where a miner has 15% of all hashing
power and the ability to exert a moderate control over the network to
the point where if the attacker sees a message A, it can't stop A from
propagating, but what it **can** do is send a message B and ensure that
most nodes see B before A. The attacker can then selfish mine and
augment selfish mining strategy by giving his own blocks an advantage.
This change makes the time at which a block is received less relevant
and so the level of control an attacker has over the network no longer
makes a difference.
This change changes the current td algorithm `B_td > C_td` to the new
algorithm `B_td > C_td || B_td == C_td && rnd < 0.5`.
Pending logs are now filterable through the Go API. Filter API changed
such that each filter type has it's own bucket and adding filter
explicitly requires you specify the bucket to put it in.
When a chain reorganisation occurs we collect the logs that were deleted
during the chain reorganisation. The removed logs are posted to the
event mux indicating that those were deleted during the reorg.
This removes the burden on a single object to take care of all
validation and state processing. Now instead the validation is done by
the `core.BlockValidator` (`types.Validator`) that takes care of both
header and uncle validation through the `ValidateBlock` method and state
validation through the `ValidateState` method. The state processing is
done by a new object `core.StateProcessor` (`types.Processor`) and
accepts a new state as input and uses that to process the given block's
transactions (and uncles for rewords) to calculate the state root for
the next block (P_n + 1).
Log filtering is now using a MIPmap like approach where addresses of
logs are added to a mapped bloom bin. The current levels for the MIP are
in ranges of 1.000.000, 500.000, 100.000, 50.000, 1.000. Logs are
therefor filtered in batches of 1.000.
