A PROPOSED SOLUTION TO THE BOTTLENECK AND CAPACITY PROBLEM FOR DATA TRANSFER

There is increased need for solution to communicate larger data over the PON network. In this study, two problems including bottleneck and the capacity load problem were investigated and based on this, a solution is proposed. For methodology, N number of Nodes is used for ringbased architecture which represent the complete PON system. The nodes are the save points are created for monitoring the nodes and tracking their network faults. The distance from each node is equal and there are N number of checkpoints. The source and receiver node are selected dynamically. A ring-based network model is proposed with the optimized solution, less data loss and higher speed. The proposed work sets a scenario which is based on ring topology with 08 number of nodes with same number of save points. 800 m * 800 m is the dimension of the topography. We found that time it took to transfer a packet is about 1.01 second.  For solving the bottleneck problem, the tree-based network model is used and accordingly, 4 sub-networks are taken in a hierarchal way.  Comparison of results based on packet delivery shows that proposed model has better time factor in terms of sending data compared to the existing system. 

Capacity and delay scaling for broadcast transmission in highly mobile wireless networks

We study broadcast capacity and minimum delay scaling laws for highly mobile wireless networks, in which each node has to disseminate or broadcast packets to all other nodes in the network. In particular, we consider a cell partitioned network under the simplified independent and identically distributed (IID) mobility model, in which each node chooses a new cell at random every time slot. We derive scaling laws for broadcast capacity and minimum delay as a function of the cell size. We propose a simple first-come-first-serve (FCFS) flooding scheme that nearly achieves both capacity and minimum delay scaling. Our results show that high mobility does not improve broadcast capacity, and that both capacity and delay improve with increasing cell sizes. In contrast to what has been speculated in the literature we show that there is (nearly) no tradeoff between capacity and delay. Our analysis makes use of the theory of Markov Evolving Graphs (MEGs) and develops two new bounds on flooding time in MEGs by relaxing the previously required expander property assumption.National Science Foundation (U.S.) (Grant CNS-12170)National Science Foundation (U.S.) (Grant CNS-17137)National Science Foundation (U.S.) (Grant AST-15473

The Capacity of Heterogeneous Wireless Networks

Abstract—A substantial body of the literature exists addressing the capacity of wireless networks. However, it is commonly assumed that all nodes in the network are identical. The issue of heterogeneity has not been embraced into the discussions. In this paper, we investigate the throughput capacity of heterogeneous wireless networks with general network settings. Specifically, we consider an extended network with n normal nodes and m nb (0 b 1) more powerful helping nodes in a rectangular area with width sðnÞ and length n=sðnÞ, where sðnÞ nw and 0 w 1=2. We assume that there are n flows in the network. All the n normal nodes are sources while only randomly chosen nd (0 d 1) normal nodes are destinations. We further assume that the n normal nodes are uniformly and independently distributed, while the m helping nodes are either regularly placed or uniformly and independently distributed, resulting in two different kinds of networks called Regular Heterogeneous Wireless Networks and Random Heterogeneous Wireless Networks, respectively. We show that network capacity is determined by the shape of the network area, the number of destination nodes, the number of helping nodes, and the bandwidth of helping nodes. We also find that heterogeneous wireless networks can provide throughput higher in the order sense than traditional homogeneous wireless networks only under certain conditions. Index Terms—Heterogeneous wireless networks, extended networks, achievable throughput Ç

On performance modeling of 3D mobile ad hoc networks

指導教員：姜 暁

Scaling Laws for Vehicular Networks

Equipping automobiles with wireless communications and networking capabilities is becoming the frontier in the evolution to the next generation intelligent transportation systems (ITS). By means of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications, information generated by the vehicle-borne computer, vehicle control system, on-board sensors, or roadside infrastructure, can be effectively disseminated among vehicles/infrastructure in proximity or to vehicles/infrastructure multiple hops away, known as vehicular networks (VANETs), to enhance the situational awareness of vehicles and provide motorist/passengers with an information-rich travel environment. Scaling law for throughput capacity and delay in wireless networks has been considered as one of the most fundamental issues, which characterizes the trend of throughput/delay behavior when the network size increases. The study of scaling laws can lead to a better understanding of intrinsic properties of wireless networks and theoretical guidance on network design and deployment. Moreover, the results could also be applied to predict network performance, especially for the large-scale vehicular networks. However, map-restricted mobility and spatio-temporal dynamics of vehicle density dramatically complicate scaling laws studies for VANETs. As an effort to lay a scientific foundation of vehicular networking, my thesis investigates capacity scaling laws for vehicular networks with and without infrastructure, respectively. Firstly, the thesis studies scaling law of throughput capacity and end-to-end delay for a social-proximity vehicular network, where each vehicle has a restricted mobility region around a specific social spot and services are delivered in a store-carry-and-forward paradigm. It has been shown that although the throughput and delay may degrade in a high vehicle density area, it is still possible to achieve almost constant scaling for per vehicle throughput and end-to-end delay. Secondly, in addition to pure ad hoc vehicular networks, the thesis derives the capacity scaling laws for networks with wireless infrastructure, where services are delivered uniformly from infrastructure to all vehicles in the network. The V2V communication is also required to relay the downlink traffic to the vehicles outside the coverage of infrastructure. Three kinds of infrastructures have been considered, i.e., cellular base stations, wireless mesh backbones (a network of mesh nodes, including one mesh gateway), and roadside access points. The downlink capacity scaling is derived for each kind of infrastructure. Considering that the deployment/operation costs of different infrastructure are highly variable, the capacity-cost tradeoffs of different deployments are examined. The results from the thesis demonstrate the feasibility of deploying non-cellular infrastructure for supporting high-bandwidth vehicular applications. Thirdly, the fundamental impact of traffic signals at road intersection on drive-thru Internet access is particularly studied. The thesis analyzes the time-average throughput capacity of a typical vehicle driving through randomly deployed roadside Wi-Fi networks. Interestingly, we show a significant throughput gain for vehicles stopping at intersections due to red signals. The results provide a quick and efficient way of determining the Wi-Fi deployment scale according to required quality of services. In summary, the analysis developed and the scaling laws derived in the thesis provide should be very useful for understanding the fundamental performance of vehicular networks