Network Flows

: This thesis considers the combining of a ship overhaul project network with a shipyard project network to minimize possible scheduling conflicts during the ship overhaul process. The combined project is called the ship overhaul project network. A heuristic multi-pass scheduling algorithm is developed to combine the ship's and shipyard's project networks. The algorithm is tested with two sets of data. The work spaces on shipboard are considered as a common resource to both project networks, and the ship's complement is an uncommon but limited resource. Since the real-world problem is larger than the context of this thesis, some simplifying assumptions were made. The most important of these are the reliable communication link between ship and shipyard prior to and/or during the overhaul process, and sufficient knowledge about the shipyard project network as early as possible after overhaul initiation. (Author)

In studying traffic congestions at toll plazas, a basic model for traffic systems is introduced, which will hopefully contribute towards a longer term solution with the means for explaining and predicting congestions. It is targeted that this can then be followed by a more specific operations research approach, based on a simulation and queuing theory model, with a study on different arrival patterns, generating queue models, and constructing a Markov chain from the queuing systems, which would then provide a better insight towards a more sustainable solution.

— In studying traffic congestions at toll plazas, a basic model for traffic systems is introduced, which will hopefully contribute towards a longer term solution with the means for explaining and predicting congestions. It is targeted that this can then be followed by a more specific operations research approach, based on a simulation and queuing theory model, with a study on different arrival patterns, generating queue models, and constructing a Markov chain from the queuing systems, which would then provide a better insight towards a more sustainable solution.

We present a wide range of problems concerning minimum cost network flows, and give an overview of the classic linear single-commodity Minimum Cost Network Flow Problem (MCNFP) and some other closely related problems, either tractable or intractable. We also discuss state-of-the-art algorithmic approaches and recent advances in the solution methods for the MCNFP. Finally, optimization software packages for the MCNFP are presented.

This technical report documents the theoretical, computational, and practical aspects of the one-dimensional Navier-Stokes finite element flow model. The document is particularly useful to those who are interested in implementing, validating and utilizing this relatively-simple and widely-used model.

In any form of traffic, whether it is physical or digital, the main problem that sparks a lot of interest for researchers is congestion. This paper discusses a study of congestion around toll plazas. A newly formulated model called Basic Traffic Unit (BTU) is introduced from previous research. BTU is a representation of a basic network connected to form a larger network. A simulation study is conducted and some queuing theories are applied to calculate the measure of performance. Two sets of data from different modes of toll payment are collected. The same two types of payments are simulated and the measure of performance is recorded. The two types of payments from the collected real data are used to calculate the measure of performance using the formula developed by the BTU. This study demonstrates that the results from simulated data can be used to compare with the results from the real-time data using the formula developed by a static model of BTU to predict possible congestions. Comparing results from both methods validates the claim that BTU is useful for predicting congestions.

This paper presents an experimental study of constraint propagation algorithms for preemptive scheduling. We propose generalizations of non-preemptive constraint propagation techniques (based on timetables, on disjunctive constraints, and on edge-finding) to preemptive and "mixed" problems, i.e., problems in which some activities can be interrupted and some cannot. Another approach relies on incremental flow-based techniques. We theoretically compare these approaches and

Flash Crowds are the events that occur due to sudden increase in legitimate traffic towards a single web server due to popularity of that web server or a famous event posted on its web pages. Distributed DoS (DDoS) attacks are the attacking events conducted by an attacker to overwhelm the web server with huge amount of traffic due to which that web server cannot serve legitimate users. Distinguishing flash crowds from DDoS attacks is very important because the response of the defense systems should be different for these two types of traffic. Initially abnormal traffic condition on a web server is detected when there is a huge amount of traffic which is very larger than the normal traffic volume. Our proposed system makes use of flow strength as a metric for assigning suspicion mark to flows in order to group the flows as probable Flash Crowd flows or probable DDoS attack flows. The technique used here is very intuitive, functional and can be proved to be working in a simulation environment and is perhaps applicable for real time usage. We found some cyber crimes that are “Beyond DDoS Attacks” and we suggested a remedy for “Beyond DDoS Attacks

—The current energy infrastructure heavily depends on fossil energy, which will be mostly depleted beyond 21st century. Another built-in disadvantage of fossil energy is the pollutant and green house gas emission. It is time to reform the environment-degrading energy infrastructure into a sustainable and resilient energy infrastructure such that it is more environmental friendly. Compared with fossil energy, it is expensive to transport renewable energy for a long distance. Another problem of renewable energy is fluctuation and it is not so stable as fossil energy. To solve the two bottleneck energy investment planning problems (transmission and fluctuation) of renewable energy development, we propose a long-term investment planning model that can help analysts, investors and policy makers find out how to take full use of current and emerging technologies to support the development of renewable energy so that our energy infrastructure can be refomed to be cleaner in a long-term periond, e.g. 40 years. In this model, we propose and implement a parallel planning method for power systems. In this method, a large region that needs to be planned is partitioned into multiple subregions. Each subregion is modeled as two optimization models. One is an hour-level model with the goal to minimize the power price volatility caused by imbalance of power demand and supply and the CO2 emission at hour level. Another is a year-level model with the goal to minimize the investment cost of transmission, operation, and fossil/clean power capapcity expansion at year-level. The year-level model also needs to satisfy the RPS [1] (Renewable Portfolio Standard, which has been approved by 27 states and D.C.) requirements because it is a year-level policy. We use an energy storage system to store surplus clean power e.g. wind power and this helps solve the fluctuation problem of wind energy. The stored energy is allowed to be traded among neighbouring subregions. All models are linear or mixed integer linear programming models and need to satisfy the constraints about fossil/clean power capacity expansion and available clean energy. We use Midwest area and wind energy as an example and implement the parallel modeling method in a cluster system , which supports parallel computing. According to our best knowledge, this is the first parallel long-term energy investment planning model for exploring the relationships between public policy (RPS), renewable energy and fossil energy. It can be used to solve large-scale planning problems on supercomputers.

Let G=(V,E) be a supply graph and H=(V,F) a demand graph defined on the same set of vertices. An assignment of capacities to the edges of G and demands to the edges of H is said to satisfy the cut condition if for any cut in the graph, the total demand crossing the cut is no more than the total

This paper proposes a method for improving the performance of Web servers servicing static HTTP requests. The idea is to give preference to those requests which are quick, or have small remaining processing requirements, in accordancewith the SRPT (Shortest-Remaining-Processing-Time) scheduling policy. The implementation is at the kernel level and involves controlling the order in which socket buffers are drained into the network. Experiments use the Linux operating system and the Apache web server. All experiments are also repeated using the FlashWeb server. Experiments are run under both trace-based workloads and those generated by a Web workload generator. Results indicate that SRPT-based scheduling of connections yields significant reductions in mean response time, mean slowdown, and variance in response time at the Web server. Most significantly, and counter to intuition, the large requests are only negligibly penalized (or not at all penalized) as a result of SRPT-based schedu...

Continuous quantitative assessment is critical for security, correctness, performance, and scalability in distributed information sharing environments. Current approaches to quantitative assessment suffer from a number of shortcomings including limited coverage, tight integration with functional code, and off-line evaluation, which limits their use for continuous assessment. In this article, we present Metrinome, a framework that enables remote monitoring and controlled experimentation. Metrinome provides (1) increased coverage over observables by virtue of ingesting fine-grained application logs, (2) reduced integration cost due to loose coupling with the monitored system and its ability to hook into existing logging infrastructures, and (3) real-time visualization of key metrics as well as export of collected metric sets for persistence and reporting.