MarkCss lazy" data-original="//html.scirp.org/file/1-9702353x45.png" />

Figure 7. Total number of active OLT ports for the minimized blocking objective.

Figure 8. Average port utilization for the minimized power consumption objective.

Figure 9. Average port utilization for minimization of blocking objective.

Figure 10. Total power consumption for minimization of power and minimization of blocking objectives.

demands increases, the number of activated AM ports and OLT switches increases. Hence the power consumed by the network is increasing as the size of demand is increasing. This result is common for the two objective functions. However, the percentage of increase is higher with the minimization of blocking objective as the assignment of resources with that approach is random. Random assignment is inefficient as links and hardware resources are underutilized. This can be clearly observed from Figure 7 and Figure 9. Figure 6 and Figure 7 demonstrate the total number of active OLT switches and AM ports for the minimization of power consumption and minimization of blocking objectives, respectively. Figure 6 shows that total number of active components is kept to minimum through grouping and consolidating demands to minimum possible number of OLT switches and AM ports. This approach has efficiently utilized the resources of the communication links and hardware as shown in the results of Figure 9.

On the other hand, minimization of blocking objective approach is inefficient as demands are randomly assigned to OLTs. This method provisions all ONTs with resource to communicate with ISP through OLT switches, however links and hardware resources are underutilized especially at low rates. Figure 7 and Figure 9 demonstrate that all OLT switches are activated for all average demand rate with low utilization.

For a comparison on the efficiency of the utilization of resources between the two objectives, number of active OLT switches evaluated with average rates between 300 and 900 Mb/s for the minimization of power consumption is 1 with average utilization ranges between 25% and 90%. While the objective of minimization of blocking has shown that the number of activated OLT switches for the same average range of rates is 4 with 10% to 50% of utilization of resources.

Figure 10 demonstrates the total power consumption result for the two objective functions. Equation (1) earlier in Section 4 described the main quantities and variables that constitute the total power consumption. These values are the number of activated OLT switches, number of AM ports, number of ONTs with queued demands. Therefore; the reason behind the reduction of power consumption with the minimization of power consumption objective against the objective of minimization of blocking, is the reduced number of active OLTs and AM ports used to service all demands.

6. Conclusion

The rapid growth in bandwidth-hungry applications and services has set new requirements for high speed infrastructure in access network to overcome many limitations appeared in current implemented technologies. PONs in access network in the last decade were found as a premium solution to resolve many challenges appeared with the conventional wireless and copper-based designs. PONs have shown a proven performance in providing high per user access rate and reducing the overall network power consumption. In this work, a mathematical optimization approach was presented to reduce the power consumption through means of consolidation and efficient utilization of network and hardware resources. Different loads of traffic rate have been evaluated following uniform distribution. Hardware and network resources have shown efficient utilization and power savings results have reached 80% for the approach with minimization of power consumption objective when compared with conventional approaches in network designs such as the approach of minimization of blocking. The work presented in this article has been limited to mathematical models. However, for a future work, computer simulations to design heuristics to validate the results obtained from the MILP mathematical models shall be of great interest.

Conflicts of Interest

The author declares no conflicts of interest regarding the publication of this paper.

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