Big transfer and Write traffic shaping issues fixed

Motivation:
Several issues were shown by various ticket (#2900 #2956).
Also use the improvement on writability user management from #3036.

Issue #2900
When a huge amount of data are written, the current behavior of the
TrafficShaping handler is to limit the delay to 15s, whatever the delay
the previous write has. This is wrong, and when a huge amount of writes
are done in a short time, the traffic is not correctly shapened.

Moreover, there is a high risk of OOM if one is not using in his/her own
handler for instance ChannelFuture.addListener() to handle the write
bufferisation in the TrafficShapingHandler.

This fix use the "user-defined writability flags" from #3036 to
allow the TrafficShapingHandlers to "user-defined" managed writability directly, as
for reading, thus using the default isWritable() and
channelWritabilityChanged().
This allows for instance HttpChunkedInput to be fully compatible.

The "bandwidth" compute on write is only on "acquired" write orders, not
on "real" write orders, which is wrong from statistic point of view.

Issue #2956
When using GlobalTrafficShaping, every write (and read) are
synchronized, thus leading to a drop of performance.
ChannelTrafficShaping is not touched by this issue since synchronized is
then correct (handler is per channel, so the synchronized).

Modifications:
The current write delay computation takes into account the previous
write delay and time to check is the 15s delay (maxTime) is really
exceeded or not (using last scheduled write time). The algorithm is
simplified and in the same time more accurate.

This proposal uses the #3036 improvement on user-defined writability flags.

When the real write occurs, the statistics are update accordingly on a
new attribute (getRealWriteThroughput()).

To limit the synchronisations, all synchronized on
GlobalTrafficShapingHandler on submitWrite were removed. They are
replaced with a lock per channel (since synchronization is still needed
to prevent unordered write per channel), as in the sendAllValid method
for the very same reason.
Also all synchronized on TrafficCounter on read/writeTimeToWait() are
removed as they are unnecessary since already locked before by the
caller.
Still the creation and remove operations on lock per channel (PerChannel
object) are synchronized to prevent concurrency issue on this critical
part, but then limited.

Result:
The traffic shaping is more stable, even with a huge number of writes in
short time by taking into consideration last scheduled write time.

The current implementation of TrafficShapingHandler using user-defined writability flags
and default isWritable() and fireChannelWritabilityChanged works as expected.

The statistics are more valuable (asked write vs real write).

Various examples are shown in one added example (example/traffic), and
in particular how a user handler might managed the write to prevent OOM:

- using the ChannelFuture.addListener(new GenericFutureListener>() one by one, or by set of writes
- using the ctx.channel().isWritable() and channelWritabilityChanged()
- using a code as HttpChunkedInput to send the chunks according to the channelWritabilityChanged() (softWritability is needed)
- using no specific check, but with the risk of OOM (no control on the bufferisation made by the TSH)

The Global TrafficShapingHandler should now have less "global"
synchronization, hoping to the minimum, but still per Channel as needed.

@fredericBregier - Thanks for enlightening me....I was not aware of that use case.

I'm not sure of the access pattern here but if you have a natural "key" of a timestamp then you may be able to use TreeSet.  
Advantages of TreeMap:
1) A single call to get all elements your are looking for (less than now)  by using [headMap](http://docs.oracle.com/javase/7/docs/api/java/util/TreeMap.html#headMap(K,%20boolean)).
2) A single call (i.e. `.clear()`) on the return value from (1) will remove those entries from the map.
3) The locked area may be reduced and may simplify synchronization around this collection.

Potential down falls of TreeMap:
1) Insertion and other operations may become more expensive
2) You may lose the relative order of operations (if time stamps are equal) and you need are reliable "key" for the timestamp (i.e. `nanoTime()`).