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Internet of Things (IoT) brings more than an explosive proliferation of endpoints. It is disruptive in several ways. In this chapter we examine those disruptions, and propose a hierarchical distributed architecture that extends from the edge of the network to the core nicknamed Fog Computing. In particular, we pay attention to a new dimension that IoT adds to Big Data and Analytics: a massively distributed number of sources at the edge.

A counting Bloom filter (CBF) generalizes a Bloom filter data structure so as to allow membership queries on a set that can be changing dynamically via insertions and deletions. As with a Bloom filter, a CBF obtains space savings by allowing false positives. We provide a simple hashing-based alternative based on d-left hashing called a d-left CBF (dlCBF). The dlCBF offers the same functionality as a CBF, but uses less space, generally saving a factor of two or more. We describe the construction of dlCBFs, provide an analysis, and demonstrate their effectiveness experimentally.

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This paper gives a class of ow control algorithms for the adaptive allocation of bandwidths to virtual connections (VC) in high speed, wide area ATM networks. The feedback rate to the source from the network is parsimonious, with each feedback bit indicating whether the bu er at a distant switch is above or below a threshold. The service discipline at the switch is First-Come-First-Served. The important goal of adaptability aims to make all of the network bandwidth available to the active VCs, even though the number of such VCs is variable over a given range. Each VC has two parameters, one giving its minimum guaranteed bandwidth and the other is the weight for determining its share of the uncommitted bandwidth. Judicious selection of these parameters de nes distinctive services, such as Best E ort and Best E ort with Minimum Bandwidth. We derive design rules for selecting the parameters of the algorithms such that the appropriate guarantees and fairness properties are exhibited in the dynamical behavior. The systematic use of \damping" in right proportion with \gain" is shown to be a powerful device for stabilizing behavior and achieving fairness. Our analyses are based on a simple analytic uid model composed of a system of rst-order delay-di erential equations, which re ect the propagation delay across the network. Extensive simulations examine the following: (i) fairness, especially to start-up VCs; (ii) oscillations; (iii) transient behavior, such as the rate of equalization from di erent initial conditions; (iv) disparate bandwidth allocations; (v) multiple paths with diverse propagation delays; (vi) adaptability and robustness with respect to parameters; (vii) interoperability of di erent algorithms.