ns2 project in delhi
ns2 project in delhi for each metarule, designate an MRP. We assum that processors are available on demand. Otherwise,some processors will be chosen to processmultiple metarules.0 As ns2 project in delhiinstances are generated at each base rule processing(BRP) site, they are sent to the MRPsfor which they are relevant by first consulting theCMRT augmented with processing site information.0 As instances arrive at an MRP, they are processedby the two-phase algorithm described above, inpipeline fashion. When all instances have beenreceived, tokensns2 project in delhi representing the unredacted instances are reported back to the source BRPs o broadcast to all BRPs for firing. This dependson whether the database is fragmented or replicated.In our initial implementation, we use thelatter (broadcast) scheme, for simplicity.This achieves “redact-all-possible” metarule semantics.n This is deterministic and independent of ns2 project in delhi instance generation order and MRP processing order. Thismethod scales with respect to the metarules. Evenbetter performance may be extracted under some simplecompile time optimizations, e.g, suppressing thetransmission of “apparently relevant” instances whichdo not really have any possibility of matching the targetmetarule because of the presence of “inappropriate”constants. Such conditions canns2 project in delhi be determinedat cornpile tirne and incorporated into the mappingtables at each BRP that direct the flow of generatedinstances to the MRP, one for each metarule.The LPM scheme features a metarulens2 project in delhi processor ateach site, i.e., paired with each base rule processor.The scheme is outlined as follows.0 Each site runs a restricted version of a rule programin a BRP, as usual, as well as a “coupled”MRP, that processes instances as they are generatedusing the two-phase algorithm, in pipelinefashion.0 The scheme is optimistic in the following sense. Itrelies on the generation of instances at each sitesuch that a good fraction of redactions will takeplace by processing only the local instance D H ,i.e., remote ns2 project in delhiinstances will not be needed.0 The unredacted instances are passed on to a“global” MRP for a final global filtering phaseif needed. The global MRP also operates on thetwo-phase principle.0 All instances that remain after the global ns2 project in delhiMRPprocessing are broadcast back (their instance id’sare broadcast) so that each BRP can execute theRHS actions.0 Instead of %level hierarchy, a Log(P)-level hierarchyis also possible, where P is the number ofB RPs .This scheme can be implemented to exhibit, eitherdeterministic or non-deterministic rule execution,depending on whether instances are simply markedon redaction, but allowed to participate in further metarule matching, or they are actually deleted. Apossible worst-case scenario is that all the work maybe done at the global MRP, thus making the localMRPs sources of overhead rather than ns2 project in delhicontributingto speedup of the metarule matching process, The MGR scheme is similar to the LPM scheme in
that an MRP is located at each BRP. However, compile
time analysis is used to determine restrictions on
the base rules in such a way that instances generated
locally at each BRP are only ns2 project in delhithose that are mutually
relevant with respect to the matching of the metarules.
Of course, one must also guarantee completeness, i.e.,
all instances must be generated over all BRPs