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As a significant branch of detection-based techniques, the research of anomaly detection in wired networks and wireless ad hoc networks is already quite mature, but such solutions can be rarely applied to WSNs without any change, because WSNs are characterized by constrained resources, such as limited energy, weak computation capability, poor memory, short communication range, etc.
In the traditional resource-constrained environment, the constrained devices such as nodes in wireless sensor networks and radio-frequency identification (RFID) tags usually have the characteristics of weak computation ability, extremely small storage space, and strictly usage of power consumption [1 3].
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In this paper we investigate how formal software verification systems can be improved by utilising parallel assignment in weakest precondition computations.
By computer computation, the first 10 billion or so do.
In the context of outsourced computation, computationally weak clients (or devices) can outsource their computation and data to a server in the cloud.
A class of new explicit second order accurate finite difference schemes for the computation of weak solutions of hyperbolic conservation laws is presented.
The Gaussian basis is introduced with the aim of achieving more efficient computations in the weak noise case with near-deterministic dynamics.
Consider a weak client that wishes to delegate a computation to an untrusted server, and then verify the correctness of the result.
Thus shock jump conditions are used for rarefactions, which limits the applicability of this work to weak rarefactions, the case most important for computation.
Figure 4 illustrates the computation of P knn y=1|x) when two weak classifiers are available.
Also new development of packages Hadoop for computation in distributed mode is a weaker tool.
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