2018 · 174 citations · 10 references
ComputingComputer ScienceComputer SystemsDatabasesDistributed SystemsReal-time SystemsCache Behavior AnalysisCachingCaching StrategiesData SynchronizationCaching MechanismsData Cache BehaviorFreshness Monitoring
We consider a cache refresh system where a local server is connected to multiple remote sources and maintains local copies of the data items at the sources. The data at each source is updated randomly and independently without notifying the local server, while the local server refreshes the corresponding cached data periodically. The freshness of the local cache is measured by two different freshness metrics, <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">age of synchronization</i> (AoS) and <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">age of information</i> (AoI). We address the following problem: given a constrained total refresh rate, how does the local server allocate the refresh rate for each source to maintain overall data freshness? We derive the AoI optimal policy which depends only on the square root of the source popularity. For a large refresh rate, we propose an AoS near-optimal rate allocation policy that is proportional to the cube root of both the source update rate and the source popularity. For small refresh rates, we also prove that the square root law with respect to the popularity minimizes both AoS and AoI.
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