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It is quite possible that Algorithm 1 returns multiple network coding solutions all of which have the same objective value.
No methods are known, however, to lower bound the cost of network coding solutions for a configuration.
Figure 6 reports the RD performance results obtained for the Outdoor, Book Arrival, Kendo and Balloons, for the nine coding solutions mentioned above.
This inevitable trend makes conventional BCH code increasingly inadequate, and iterative coding solutions such as low-density parity-check (LDPC) codes become very natural alternative options.
A straightforward order based solution representation is applied for coding solutions of the problem and clustering approach is used to generate appropriate initial solutions.
The ratio of the minimum energy consumption of routing solutions and the minimum energy consumption of network coding solutions, maximized over all node locations, multiple unicast sessions, and transmission ranges, with the transmission range equal for the routing and network coding solutions, is at least, that is, (4).
Similar(20)
Efficient search algorithms for the optimal network coding solution, as well as heuristic methods were presented and their delay and computational performance were tested in several system scenarios.
(25) end if . Figure 1 A schematic of Algorithm 1 with greedy pruning for finding the optimal network coding solution of (4).
In this work we, are interested in the energy benefit of network coding, which is the ratio of the minimum energy solution in a routing solution compared to the minimum energy network coding solution, maximized over all configurations.
These different genotypes co-exist in the population, however in the long term, the most compact coded solutions will out-compete those with a longer genome.
We suggested a coded solution to the problem, which codes over packets intended to different users.
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