For different fault tolerance requirement, graph-based simulations results indicated that FICTC outperforms the state-of-the-art fault-tolerant topology control algorithms in terms of average node degree, maximum transmit radius, and maximum link interference.
When expressing network capacity and requirements as graph structures, this entails a graph embedding or graph matching problem.
This paper proposes a framework for supporting the design process by defining design requirements over graph-based representations of designs.
We have that f(C =C, where for each v i, f(v i )=v i, and f(v i,vi+1)=(v i,vi+1), by the validity requirement of graph convergence.
To meet diverse requirements of big graph partitioning scenarios, we first devise 3 measurement schemes for measuring the graph vertex count, graph workload, and graph processing time, respectively.
Then, local and global graph requirements over HL-graphs, which correspond to design constraints, are defined.
The satisfiability of graph requirements by representations of designs allows for checking correctness of design solutions.
Besides previous quality assessments, the computational requirements of the graph clustering-based methods are discussed here.
The proposed ontological interpretations transform first-order and monadic second-order logic formulas expressing design criteria into equivalent local and global graph requirements.
In addition to providing significant improvements in the memory requirements for the graph edges, as seen by comparing Tables 1 and 2, the total memory requirements for Fig. 2 (including graph edges and all other storage requirements) are also significantly improved by the transformed dataflow graph of Fig. 3.
