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Study of Factors Affecting River Pollution byPetroleum and it’s ProductsThis thesis deals with pollution of river water ingeneral; and the Egyptain Nile in Pa~ticular, being pollutedwith petroleum and its products. This has been a topic ofincreasing importance in recent years, and a new law to com-bating pollution have ”been applied since 1982. This polloll-tion by oil is caused by continuous sources, such aseffluents from refineries and industrial canters, or byaccidental spills, due to oilfailure and barge collision.Such cources of water pollution by oil have been reviewea, and examples of important pollution accidentshave been OIiven. A discussion and comparison of differ-ant methods of removing pollution in have been made.Due to the increassing demand for crude oil and its fractions in Upper Egypt, and the increasing n’~ber ofbarges in Nile River ( for transporting, storing, ••• ); theaim of this study have been directed to\Vards usinga s:imple sinking method for combating accidental spills ofEgyptian oils and their fractions by using materials avail-able all along ~ale: Sand, Nile Si1t and their mixture.- 2 -Sinking consists of throwing granulated 0”” powderv materialof high true density on the polluting oil, in order toadsorb it and sink it. Later, the sinking agent-oilmixture is removed by mechanical means, in order to avoidre-pollution by the release of oil.The experimental work covered the main operatingparameters which affect the sinking treatment:-Oil S·pill Characteristics: Morgan and Sinai CrudeOils, and their fractions ( Gasoline, Kerosene, GasOil and Fuel Oil ) were useo.Oil to Water Ratio; Five Oil to Water ratios weretested ( 5,20,)5,50 and 65 ccl liter of water ).Sinking Agent to Oil Ratio: Experiments were carriedout in the range of Sinking Agent to Oil ( gm/cc ) of0.25il to 5/1 and sometimes 8/1.For each cut, experiments were carried out ~~th theThe second objective of this thesis is to evaluate the performance of genetic algorithm used for finding the shortest path in communication network. The performance of GA is compared to Dijkstra algorithm in terms of finding the optimum solution and running time. This is realized using different simulated networks to clarify the advantages and deficiencies of each algorithm.AbstractThere has been an explosive growth in both computer and communication networks since the last three decades. Routing problem is one of the most important issues facing the development, improvement and performance of communication and computer networks. The routing algorithm is used by network to compute the path that would best serve to transport the data from the source to the destination.Because the routing algorithms have so much impact on the overall performance of any network, the first objective of this thesis is to research and compare between six routing algorithms. Also, this thesis illustrated that how routing algorithms are most efficient under varying the network configuration parameters. A number of experiments were performed to evaluate the performance of these routing algorithms and an appropriate estimated function is generated which is completely dependent on the influences of the routing algorithms under various circumstances.The second objective of this thesis is to evaluate the performance of genetic algorithm used for finding the shortest path in communication network. The performance of GA is compared to Dijkstra algorithm in terms of finding the optimum solution and running time. This is realized using different simulated networks to clarify the advantages and deficiencies of each algorithm.AbstractThere has been an explosive growth in both computer and communication networks since the last three decades. Routing problem is one of the most important issues facing the development, improvement and performance of communication and computer networks. The routing algorithm is used by network to compute the path that would best serve to transport the data from the source to the destination.Because the routing algorithms have so much impact on the overall performance of any network, the first objective of this thesis is to research and compare between six routing algorithms. Also, this thesis illustrated that how routing algorithms are most efficient under varying the network configuration parameters. A number of experiments were performed to evaluate the performance of these routing algorithms and an appropriate estimated function is generated which is completely dependent on the influences of the routing algorithms under various circumstances.The second objective of this thesis is to evaluate the performance of genetic algorithm used for finding the shortest path in communication network. The performance of GA is compared to Dijkstra algorithm in terms of finding the optimum solution and running time. This is realized using different simulated networks to clarify the advantages and deficiencies of each algorithm.AbstractThere has been an explosive growth in both computer and communication networks since the last three decades. Routing problem is one of the most important issues facing the development, improvement and performance of communication and computer networks. The routing algorithm is used by network to compute the path that would best serve to transport the data from the source to the destination.Because the routing algorithms have so much impact on the overall performance of any network, the first objective of this thesis is to research and compare between six routing algorithms. Also, this thesis illustrated that how routing algorithms are most efficient under varying the network configuration parameters. A number of experiments were performed to evaluate the performance of these routing algorithms and an appropriate estimated function is generated which is completely dependent on the influences of the routing algorithms under various circumstances.The second objective of this thesis is to evaluate the performance of genetic algorithm used for finding the shortest path in communication network. The performance of GA is compared to Dijkstra algorithm in terms of finding the optimum solution and running time. This is realized using different simulated networks to clarify the advantages and deficiencies of each algorithm.AbstractThere has been an explosive growth in both computer and communication networks since the last three decades. Routing problem is one of the most important issues facing the development, improvement and performance of communication and computer networks. The routing algorithm is used by network to compute the path that would best serve to transport the data from the source to the destination.Because the routing algorithms have so much impact on the overall performance of any network, the first objective of this thesis is to research and compare between six routing algorithms. Also, this thesis illustrated that how routing algorithms are most efficient under varying the network configuration parameters. A number of experiments were performed to evaluate the performance of these routing algorithms and an appropriate estimated function is generated which is completely dependent on the influences of the routing algorithms under various circumstances.The second objective of this thesis is to evaluate the performance of genetic algorithm used for finding the shortest path in communication network. The performance of GA is compared to Dijkstra algorithm in terms of finding the optimum solution and running time. This is realized using different simulated networks to clarify the advantages and deficiencies of each algorithm.
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