The efficient emergency packet schedule implement the backpressure scheduling scheme applied in Internet of Things, which can control the network congestion effectively and increase the network throughput. However, in large-scale Emergency Internet of Things (eiot), emergency packets may exist because of the urgent events or situations. The traditional backpressure scheduling scheme will explore all the possible routes between the source and destination nodes that cause a superfluous long path for packets. Therefore, the end-to-end delay increases and the real-time performance of emergency packets cannot be guaranteed. In existing system, backpressure queue model with emergency packets is first devised based on the analysis of the arrival process of different packets. Meanwhile, EABS combines the shortest path with backpressure scheme in the process of next hop node selecting. The emergency packets are forwarded in the shortest path and avoid the network congestion according to the queue backlog difference. The extensive experiment results verify that EABS can reduce the average end-to-end delay and increase the average forwarding percentage. In proposed system, buffer dimensioning is therefore essential to design a practical and efficient hierarchical clustering algorithm (DTN). This project addresses the problem of quantifying the buffer size of DTN source nodes, under replication based routing protocol, using large deviation techniques. The proposed dimensioned-buffer model is shown to exhibit a routing performance of an equivalent infinite buffer model. In addition, the problem of routing in intermittently connected wireless networks comprising multiple classes of nodes is addressed. The proposed solution perform well in homogeneous scenarios, are not as competent in this setting. To this end, it proposes a class of routing schemes that can identify the nodes of “highest utility” for routing, improving the delay and delivery ratio By 4 ? 5×. Additionally, it proposes an analytical framework based on fluid models that can be used to analyze the performance of various opportunistic routing strategies, in heterogeneous settings. This project proposes a qos-Oriented Distributed routing protocol (QOD) to enhance the qos support capability of hybrid networks. Taking advantage of fewer transmission hops and anycast transmission features of the hybrid networks, QOD transforms the packet routing problem to a resource scheduling problem.