Intelligent Transportation System (ITS)  is the main research domain for making road transport safer and more comfortable. For the sake of increasing the benefits of ITS, projects about Inter-Vehicle Communication (IVC)  system have been proposed to make communications among vehicles possible, to exchange traffic information and avoid accidents. In order to create communication network among vehicles or between vehicles and infrastructure,  Vehicular Ad hoc Networks (VANETs) has been proposed. Many applications in VANETs need to send messages to vehicles within a specific geographic region. This behavior is called geocast and this specific geographic region is called the Zone of Relevance (ZOR). Some routing protocols which are related to Geocast have been proposed in literature for VANETs. So it is significant to evaluate and compare the performance of these known Geocast routing protocols. In this thesis, categories of the routing protocols, as well as communication forwarding schemes are introduced. The routing protocols in VANETs are also summarized and compared. In order to evaluate the performance of these protocols, the evaluation methods are proposed and then a Geocast routing simulator is designed and used to simulate the Geocast network environment and several Geocast routing protocols.

This thesis presents an evaluation of the performance, in terms of throughput and latency, of two Media Access Control (MAC) mechanisms in Underwater Acoustic Networks (UANs), using a model designed in the COTS simulation tool OPNET 10.5. The carrier sense multiple access with collision avoidance is the predominant approach for implementing the MAC mechanism in UANs. However, the underwater acoustic environment is characterized by extreme propagation delays and limited bandwidth, which suggests that an Aloha-like scheme may merit consideration. The performance of these two schemes was compared with respect to two topologies: tree and grid. The results showed that an Aloha-like scheme that does not segment messages outperforms the contention-based scheme under all load conditions, in terms of both throughput and latency, for the two topologies. This thesis is the first to establish that Aloha-like MAC mechanisms can be more than a limited alternative for lightly loaded networks; more specifically, they can be the preferred choice for an environment with large propagation delays. / Lieutenant Commander, Portuguese Navy

Simulation has become an important way to observe and understand various networking phenomena under various conditions. As the demand to simulate larger and more complex networks increases, the limited computing capacity of a single workstation and the limited simulation capability of a single network simulator have become apparent obstacles to the simulationists. In this research we develop techniques that can scale a simulation to address the limited capacity of a single workstation, as well as techniques that can compose a simulation from different simulator components to address the limited capability of a single network simulator. We scale a simulation with two different approaches: 1) We reduce the resource requirement of a simulation substantially, so that larger simulations can fit into one single workstation. In this thesis, we develop three technqiues (Negative Forwarding Table, Multicast Routing Object Aggregation and NIx-Vector Unicast Routing) to aggregate and compress the large amount of superfluous or redundant routing state in large multicast simulations. 2) The other approach to scale network simulations is to partition a simulation model in a way that makes the best use of the resources of the available computer cluster, and distribute the simulation onto the different processors of the computer cluster to obtain the best parallel simulation performance. We develop a novel empirical methodology called BencHMAP (Benchmark-Based Hardware and Model Aware Partitioning) that runs small sets of benchmark simulations to derive the right formulas of calculating the weights that are used to partition the simulation on a given computer cluster. On the other hand, to address the problem of the limited capability of a network simulator, we develop techniques for building complex network simulations by composing from independent components. With different existing simulators good at different protocol layers/scenarios, we can make each simulator execute the layers where it excels, using a simulation backplane to be the interface between different simulators. In this thesis we demonstrate that these techniques enable us to not only scale up simulations by orders of magnitude with a good performance, but also compose complex simulations with high fidelity.

Federated approach for the distributed simulation of a network, is an alternative method that aims to combine existing simulation models and software together using a Run Time Infrastructure (RTI), rather than building the whole simulation from scratch. In this study, an approach that significantly reduces the inter-federate communication load in federated simulation of communication networks is proposed. Rather than communicating packet-level information among federates, characteristics of packet flows in individual federates are dynamically identified and communicated. Flow characterization is done with the Gaussian Mixtures Algorithm (GMA) using a Self Organizing Mixture Network (SOMN) technique. In simulations of a network partitioned into eight federates in space parallel manner, it is shown that significant speedups are achieved with the proposed approach without unduly compromising accuracy.

A power system is typically one small part of a larger interconnected network and is affected to a varying degree, by contingencies external to itself as well as by the reaction of external network to its own contingencies. Thus, the accuracy of a complete interconnected network model would affect the results of many transmission level analyses. In an interconnected power system, the real-time network security and power transfer capability analyses require a ¡§real-time¡¨ complete network base case solution. In order to accurately assess the system security and the inter-area transfer capability, it is highly desirable that any available information from all areas is used. With the advent of communications among operations control center computers, real-time telemetered data can be exchanged for complete network modeling. Measurement time skew should be considered in the complete network modeling when combining large area data received via a data communication network. In this dissertation, several suggestions aiming toward the improvement of complete network modeling are offered. A discrete event simulation technique is used to assess the performance of a data exchange scheme that uses Internet interface to the SCADA system. Performance modeling of data exchange on the Internet is established and a quantitative analysis of the data exchange delay is presented. With the prediction mechanisms, the effect of time skew of interchanged data among utilities can be minimized, and consequently, state estimation (SE) could provide the accurate real-time complete network models of the interconnected network for security and available transfer capability analyses. In order to accommodate the effects of randomly varying arrival of measurement data and setup a base case for more accurate analyses of network security and transfer capability, an implementation of a stochastic Extended Kalman Filter (EKF) algorithm is proposed to provide optimal estimates of interconnected network states for systems in which some or all measurements are delayed. To have an accurate state estimation of a complete network, it is essential to have the capability of detecting bad data in the model. An efficient information debugging methodology based on the stochastic EKF algorithm is used for the detection, diagnosis and elimination of bad data.

This research investigates the impact of organizations' collaboration strategies and network positional variables on invention performance. Organizations, particularly those pursuing a differentiation strategy, are motivated to introduce novel products and services in order to remain competitive. Thus, two questions of interest to such organizations regarding the network dynamics of the invention process are: 1) What kind of strategies allow them to attain superior invention results? 2) What is the most advantageous structural positioning in a collaborative network of innovators? Three independent studies attempt to find answers to these questions by using three complementary study approaches. In the first study, in order to examine invention performance of organizations with different collaboration strategies, a simulation model is constructed and run at various levels of technological dynamism and with various types of invention tasks. The cognitive cooperation strategy, which pursues technological knowledge integration as a priority, is found to be the most effective strategy in most experiments. Success-driven cooperators, whose priority is to collaborate with the most effective performers in the network, provided the most consistent invention performance. Moreover, different strategies are shown to perform best at certain points of the industry environment space spanned by technological dynamism and invention type. The second study investigates the impact of positional metrics in a collaboration network on the inventive performance of organizations (as measured by the number of patents issued) by using survey data. Twenty-eight high-tech companies and universities located in Florida are surveyed to reveal their collaborative networking map. Network structural measures are obtained in order to test the hypotheses that high values in centrality metrics correspond with higher inventive performance. The regression analyses imply that degree and closeness centralities are predictive indicators of high inventive performance but the data does not support the significance of impact of local clustering. The third study analyzes the impact of positional metrics on inventive performance by using a national database for the announced research and production joint ventures. From the most inventive organizations (in terms of patent counts) 63 of them are selected for analysis. 371 research and production joint ventures are analyzed to identify their relationship network every year from 1994 to 2012. The results indicate that the number of joint venture partners, being close to other members of the network through network connections and strong local connectivity (except for their interaction effect) is associated with higher invention performance. All three studies bring new methodological contributions to the area of invention network research. The simulation study offers a new model in the area of collaborative invention networks. Furthermore, the ideas and practices developed during the construction of the agent based simulation model for the invention network can be adapted to similar areas of application. The survey study offers a holistic approach for the definition of connections in the development of invention network map and empirically tests it. The database study longitudinally analyzes the evolution of a highly accurate joint venture network over 19-year period while testing the impact of positional metrics with un-weighted and weighted calculation methods. Solutions to our health problems, communication or transportation needs etc. are not usually found due to some series of fortunate events. They are the product of an effective recombination process of technological knowledge. Moreover, effective invention performance is not only important for organizations individually, it is crucial for governments that are concerned with the problems of its citizens. Effective ways of facilitating the recombination of technological knowledge are addressed and presented to inform both companies and policy makers. Better understanding of the dynamics of the invention process will bring more solutions to existing problems.

Various commercial software packages are available for simulating compressed air network operations. However, none of these software packages are able to dynamically prioritise compressor selection on large compressed air networks in the mining industry. In this dissertation, a dynamic compressor selector (DCS) will be developed that will actively and continuously monitor system demand. The software will ensure that the most suitable compressors, based on efficiency and position in the compressed air network, are always in operation. The study will be conducted at a platinum mine. Compressed air flow and pressure requirements will be maintained without compromising mine safety procedures. Significant energy savings will be realised. DCS will receive shaft pressure profiles from each of the shafts’ surface compressed air control valves. These parameters will be used to calculate and predict the compressed air demand. All pipe friction losses and leaks will be taken into account to determine the end-point pressure losses at different flow rates. DCS will then prioritise the compressors of the compressed air network based on the overall system requirement. This software combines the benefits of supply-side and demand-side management. Potential energy savings with DCS were proven and compressor cycling reduced. A DCS user-friendly interface was created to easily set up any mine’s compressed air network. / Thesis (MIng (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2013

Various commercial software packages are available for simulating compressed air network operations. However, none of these software packages are able to dynamically prioritise compressor selection on large compressed air networks in the mining industry. In this dissertation, a dynamic compressor selector (DCS) will be developed that will actively and continuously monitor system demand. The software will ensure that the most suitable compressors, based on efficiency and position in the compressed air network, are always in operation. The study will be conducted at a platinum mine. Compressed air flow and pressure requirements will be maintained without compromising mine safety procedures. Significant energy savings will be realised. DCS will receive shaft pressure profiles from each of the shafts’ surface compressed air control valves. These parameters will be used to calculate and predict the compressed air demand. All pipe friction losses and leaks will be taken into account to determine the end-point pressure losses at different flow rates. DCS will then prioritise the compressors of the compressed air network based on the overall system requirement. This software combines the benefits of supply-side and demand-side management. Potential energy savings with DCS were proven and compressor cycling reduced. A DCS user-friendly interface was created to easily set up any mine’s compressed air network. / Thesis (MIng (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2013

The aim of this thesis is to investigate the traffic patterns in the mobile data networks. In this work, a simple Cellular Digital Packet Data (CDPD) network was modeled in order to be used in simulations. For the purpose of using in the CDPD model, a synthetic bursty traffic model was produced and using different traffic patterns some performance investigations were made in CDPD network. During the whole work, OPNET simulation tool was used. The CDPD network modeled by OPNET simulation tool was compared with a CDPD model described in the literature and the differences were shown. The new model has some new features: 1) Burst transmission of MAC blocks. 2) Exponential backoff. 3) New packet structures. 4) Frame segmentation and encapsulation into MAC layer frames. Using OPNET, a traffic having higher level of burstiness was produced and applied to the CDPD network model. Under the bursty traffic, some CDPD performance parameters were collected and according to the collected results some suggestions were given.

Network emulation has been widely used to aid in the development and evaluation of real-time applications. Many of today s applications and protocols need to be tested and evaluated in large scale network environments such as the Internet, which requires emulation tools that meet the requirements of scale, accuracy, timeliness. Due to physical resource constraints in network emulators, existing emulation tools fail to meet these requirements as they are either limited to small and static networks, use simplified network models, or fail to deliver timely emulation results. If more physical resources are devoted to network emulation by utilizing high performance computing facilities, the accuracy and scalability of network emulation can be greatly improved. However, for many users, high performance computing facilities may not be readily available in a local laboratory environment, and co-locating application code with a remote high performance computing facility may be cumbersome and inconvenient. This thesis proposes a network emulation approach called ROSENET (RemOte SErver-based Network EmulaTion) that utilizes a distributed server-based architecture in which local low-fidelity emulators provide real-time QoS predictions to distributed applications, coupled with a remote large scale high-fidelity simulator that continuously updates and calibrates the local low-fidelity emulators. A library-based modeling approach based on online simulation data collection is proposed and a system identification modeling technique is presented. Experimental results examining emulation end-to-end delay and loss show that ROSENET provides a promising approach to network emulation supporting accuracy and scale while meeting real-time constraints. Challenges faced in applying ROSENET to real world applications are addressed through two case studies including applying synthetic workload on DARPA s NMS network topology for large scale network simulation and a contemporary real-time distributed VoIP application Skype.