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This paper contributes tail bounds of the age-of-information of a generalclass of parallel systems and explores their potential. Parallel systems arisein relevant cases, such as in multi-band mobile networks, multi-technologywireless access, or multi-path protocols, just to name a few. Typically,control over each communication channel is limited and random service outagesand congestion cause buffering that impairs the age-of-information. Theparallel use of independent channels promises a remedy, since outages on onechannel may be compensated for by another. Surprisingly, for the well-knowncase of M$\mid$M$\mid$1 queues we find the opposite: pooling capacity in onechannel performs better than a parallel system with the same total capacity. Ageneralization is not possible since there are no solutions for other types ofparallel queues at hand. In this work, we prove a dual representation ofage-of-information in min-plus algebra that connects to queueing models knownfrom the theory of effective bandwidth/capacity and the stochastic networkcalculus. Exploiting these methods, we derive tail bounds of theage-of-information of parallel G$\mid$G$\mid$1 queues. In addition to parallelclassical queues, we investigate Markov channels where, depending on the memoryof the channel, we show the true advantage of parallel systems. We continue toinvestigate this new finding and provide insight into when capacity should bepooled in one channel or when independent parallel channels perform better. Wecomplement our analysis with simulation results and evaluate different updatepolicies, scheduling policies, and the use of heterogeneous channels that ismost relevant for latest multi-band networks.

Statistical Age-of-Information Bounds for Parallel Systems: When Do Independent Channels Make a Difference?