One of the algorithms that we tried was built from the following approach: trying to correlate the update frequency of a property with the “number of pixels” eventually affected by a property change on the viewer's screen. Practically, the first budget-based algorithm that was developped dealt with each property: each tuple (viewer client, viewed entity, property) was assigned a priority, and a data structure representing “shelves & buckets” was browsed when sending updates to the client. The priority helped assigning a property change event into the right bucket. It was computed from several criteria:
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Then another step was required to filter which properties would be sent to a viewer when processing a particular viewed entity.
另外一个步骤用来对特定的被观察的实体进行处理，以决定哪些属性需要发送给观察者。
Other properties were taken into account as well. For example, if a viewed entity suddenly put on their hat, without moving, the entity would get a higher update priority.
其他属性也同样被列入考虑。比如，如果一个被观察实体突然戴上了他的帽子，而并没有移动，这个实体也同样会获得一个比较高的更新优先级。
These countries can no longer be viewed as a single entity.
这些国家不能再被看成是一个单独的实体。
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