Today's Internet provides only a single Class of Service (CoS) to all of its services (e.g., Multimedia, Data, Audio), namely the best-effort service. This service does not make any guarantees on the Quality of Service (QoS) an application receives. The continuous demands for QoS guarantees have led to the introduction of various network-layer mechanisms that provide some end-to-end QoS assurance including MPLS, Integrated Service Model (IntServ), and Differentiated Service Model (DiffServ). However, the QoS mapping between the network-layer and the application-layer is still a challenge and needs to be addressed. To guarantee and end-to-end QoS, it is essential to map QoS parameters between these layers. A framework for investigating the mapping of the packet loss rate as an important QoS parameter is presented here. The network QoS performance characteristic for the loss parameter is mapped from lower to upper layer in a quantifiable way.
We address the problem of creating an adaptive source coding algorithm for a genomic encryption protocol using a small alphabet such as the nucleotide bases represented in the genetic code. For codewords derived from an alphabet of N plaintext with probability of occurrence, p, we describe a mapping into a floating point representation of the codewords which are translated into genomic codewords derived from a novel modification of the Shannon-Fano-Elias coding process. Errors in the reverse decoding process are processed through an adaptive, self-correcting codebook to determine the best fit codeword decoding solution. A genetic algorithmic approach to error correction within the source coding is also summarized.
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