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Abstract-Queuing theory is an important concept in current internet technology. As the requirement of bandwidth goes on increasing it is necessary to use optical communication for transfer of data. Optical communication at backbone network requires various devices for traffic grooming. The cost of these devices is very high which leads to increase in the cost of network. One of the solutions to this problem is to have sparse traffic grooming in optical WDM mesh network. Sparse traffic grooming allows only few nodes in the network as grooming node (G-node). These G-nodes has the grooming capability and other nodes are simple nodes where traffic grooming is not possible. The grooming nodes are the special nodes which has high cost. The possibility of faults at such a node, or link failure is high. Resolving such faults and providing efficient network is very important. So we have importance of such survivable sparse traffic grooming network.Queuing theory helps to improve the result of network and groom the traffic in the network. The paper focuses on the improvement in performance of the backbone network and reduction in blocking probability. To achieve the goals of the work we have simulated the model. The main contribution is to use survivability on the sparse grooming network and use of combiner queues at each node. It has observed that Combiner queuing alone does the job of minimizing blocking probability and balancing the load over the network. The model is not only cost effective but also increases the performance of network and minimizes the call blocking probability.

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Wireless Sensor Network (WSN) is widely used in recent years for the applications where human intervention is impossible. In case of nuclear power plant if any small delay occurs for data forwarding due to any node failure may results in severe disaster. Hence effective Topology Control is required to obtain an energy efficient sensor network even if any node fails. An efficient topology control using genetic algorithm based cluster head selection is presented in this paper. In this work, three tier sensor network architecture is developed and is comprised of Super Head nodes, Cluster Head nodes and Cluster Slave nodes. The results obtained for the developed three tier architecture is compared with two tier and one tier architectures. Residual Energy, Bandwidth and Memory Capacity are used as selection criteria. Quantitative analysis is also carried out to study the impact of N-tiers on the performance of the proposed algorithms. From the quantitative analysis of the proposed methodologies on the N-tier architecture with various node densities, it has been proved that two tier architecture provides reduced energy consumption compared to others.