Multi-Protocol Label Switching (MPLS), a label swapping and forwarding technology proposed by IETF, is very suitable for the backbone of the next-generation Internet. MPLS has the advantages in improving the performance of network-layer routing and increasing network scalability as well. To provide more reliable delivery in MPLS networks, it is necessary for every label switch router (LSR) to perform a fast recovery mechanism after link failures. It is also required for an LSR to support the functions of failure detection, failure notification, and protection mechanisms in each label switched path (LSP). Therefore, different kinds of recovery schemes in previous literatures have been proposed to enhance the reliability of MPLS networks when a link failure occurs in the primary LSP. In this thesis, we focus on the comparisons of three famous recovery mechanisms, Makam, Haskin, and Hundessa approach. By investigating different locations of link failure, the influences of the three approaches individually on the TCP performance are our major concerns, especially under different TCP versions. Finally, we use the MPLS Network Simulator (MNS) to verify our observations. Four different TCP versions, including TCP-Tahoe, TCP-Reno, TCP-NewReno, and TCP-SACK, are employed in our simulator. From the simulation results, the characteristics of congestion control when using different TCP versions are discussed. Without applying fast retransmission and fast recovery, the average throughput of TCP-Tahoe is the smallest, as compared to that of other TCP versions. In addition, multiple packet losses in the period of link failures would largely downgrade the performance of average throughput, no matter which TCP version (TCP-NewReno or TCP-Reno) is employed. Using Makam approach, we found out that the average throughput becomes better when the location of link failures is close to the ingress node.

The Wireless Sensor Networks (WSNs) have emerged as a new paradigm for collecting and processing data from physical environments, such as wild life sanctuaries, large warehouses, and battlefields. Users can access sensor data by issuing queries over the network, e.g., to find what are the 10 highest temperature values in the network. Typically, a WSN operates by constructing a logical topology, such as a spanning tree, built on top of the physical topology of the network. The constructed logical topology is then used to disseminate queries in the network, and also to process and return the results of such queries back to the user. A major challenge in this context is prolonging the network's lifetime that mainly depends on the energy cost of data communication via wireless radios, which is known to be very expensive as compared to the cost of data processing within the network. In this research, we investigate some of the core problems that deal with the different aspects of in-network query processing in WSNs. In that context, we propose an efficient filtering based algorithm for the top-k query processing in WSNs. Through a systematic study of the top-k query processing in WSNs we propose several solutions in this thesis, which are applicable not only to the top-k queries, but also to in-network query processing problems in general. Specifically, we consider broadcasting and convergecasting, which are two basic operations that are required by many in-network query processing solutions. Scheduling broadcasting and convergecasting is another problem that is important for energy efficiency in WSNs. Failure of communication links, which are common in WSNs, is yet another important issue that needs to be addressed. In this research, we take a holistic approach to deal with the above problems while processing the top-k queries in WSNs. To this end, the thesis makes several contributions. In particular, our proposed solutions include new logical topologies, scheduling algorithms, and an overall sophisticated communication framework, which allows to process the top-k queries efficiently and with increased reliability. Extensive simulation studies reveal that our solutions are not only energy efficient, saving up to 50% of the energy cost as compared to the current state-of-the-art solutions, but they are also robust to link failures.

No description available.

During the 20th century, transportation programs were focused on the development of the basic infrastructure for the transportation networks. In the 21st century, the focus has shifted to management and operations of these networks. Transportation network reliability measure plays an important role in judging the performance of the transportation system and in evaluating the impact of new Intelligent Transportation Systems (ITS) deployment. The measurement of transportation network travel time reliability is imperative for providing travelers with accurate route guidance information. It can be applied to generate the shortest path (or alternative paths) connecting the origins and destinations especially under conditions of varying demands and limited capacities. The measurement of transportation network reliability is a complex issue because it involves both the infrastructure and the behavioral responses of the users. Also, this subject is challenging because there is no single agreed-upon reliability measure. This dissertation developed a new method for estimating the effect of travel demand variation and link capacity degradation on the reliability of a roadway network. The method is applied to a hypothetical roadway network and the results show that both travel time reliability and capacity reliability are consistent measures for reliability of the road network, but each may have a different use. The capacity reliability measure is of special interest to transportation network planners and engineers because it addresses the issue of whether the available network capacity relative to the present or forecast demand is sufficient, whereas travel time reliability is especially interesting for network users. The new travel time reliability method is sensitive to the users' perspective since it reflects that an increase in segment travel time should always result in less travel time reliability. And, it is an indicator of the operational consistency of a facility over an extended period of time. This initial theoretical effort and basic research was followed by applying the new method to the I-4 corridor in Orlando, Florida. This dissertation utilized a real life transportation data warehouse to estimate travel time reliability of the I-4 corridor. Four different travel time stochastic models: Weibull, Exponential, Lognormal, and Normal were tested. Lognormal was the best-fit model. Unlike the mechanical equipments, it is unrealistic that any freeway segment can be traversed in zero seconds no matter how fast the vehicles are. So, an adjustment of the developed best-fit statistical model (Lognormal) location parameter was needed to accurately estimate the travel time reliability. The adjusted model can be used to compute and predict travel time reliability of freeway corridors and report this information in real time to the public through traffic management centers. Compared to existing Florida Method and California Buffer Time Method, the new reliability method showed higher sensitivity to geographical locations, which reflects the level of congestion and bottlenecks. The major advantages/benefits of this new method to practitioners and researchers over the existing methods are its ability to estimate travel time reliability as a function of departure time, and that it treats travel time as a continuous variable that captures the variability experienced by individual travelers over an extended period of time. As such, the new method developed in this dissertation could be utilized in transportation planning and freeway operations for estimating the important travel time reliability measure of performance. Then, the segment length impacts on travel time reliability calculations were investigated utilizing the wealth of data available in the I-4 data warehouse. The developed travel time reliability models showed significant evidence of the relationship between the segment length and the results accuracy. The longer the segment, the less accurate were the travel time reliability estimates. Accordingly, long segments (e.g., 25 miles) are more appropriate for planning purposes as a macroscopic performance measure of the freeway corridor. Short segments (e.g., 5 miles) are more appropriate for the evaluation of freeway operations as a microscopic performance measure. Further, this dissertation has explored the impact of relaxing an important assumption in reliability analysis: Link independency. In real life, assuming that link failures on a road network are statistically independent is dubious. The failure of a link in one particular area does not necessarily result in the complete failure of the neighboring link, but may lead to deterioration of its performance. The "Cause-Based Multimode Model" (CBMM) has been used to address link dependency in communication networks. However, the transferability of this model to transportation networks has not been tested and this approach has not been considered before in the calculation of transportation networks' reliability. This dissertation presented the CBMM and applied it to predict transportation networks' travel time reliability that an origin demand can reach a specified destination under multimodal dependency link failure conditions. The new model studied the multi-state system reliability analysis of transportation networks for which one cannot formulate an "all or nothing" type of failure criterion and in which dependent link failures are considered. The results demonstrated that the newly developed method has true potential and can be easily extended to large-scale networks as long as the data is available. More specifically, the analysis of a hypothetical network showed that the dependency assumption is very important to obtain more reasonable travel time reliability estimates of links, paths, and the entire network. The results showed large discrepancy between the dependency and independency analysis scenarios. Realistic scenarios that considered the dependency assumption were on the safe side, this is important for transportation network decision makers. Also, this could aid travelers in making better choices. In contrast, deceptive information caused by the independency assumption could add to the travelers' anxiety associated with the unknown length of delay. This normally reflects negatively on highway agencies and management of taxpayers' resources.

Thesis (MSc (Mathematical Sciences. Computer Science))--University of Stellenbosch, 2009. / ENGLISH ABSTRACT: Since 2002 data tra c has overtaken voice tra c in volume [1]. Telecom / Network operators still generate most of their income carrying voice tra c. There is however a huge revenue potential in delivering reliable guaranteed data services. Network survivability and recovery from network failures are integral to network reliability. Due to the nature of the Internet, recovery from link failures needs to be distributed and dynamic in order to be scalable. Link failure recovery schemes are evaluated in terms of the survivability of the network, the optimal use of network resources, scalability, and the recovery time of such schemes. The need for recovery time to be improved is highlighted by real-time data tra c such as VoIP and video services carried over the Internet. The goal of this thesis is to examine existing link failure recovery schemes and evaluate the need for their extension, and to evaluate the performance of the proposed link failure recovery schemes. i / AFRIKAANSE OPSOMMING: Sedert 2002 het data verkeer die stem verkeer in volume verbygesteek [1]. Telekommunikasie / netwerk operateurs genereer egter steeds die meeste van hul inkomste met stem verkeer. Netwerk oorlewing en die herstel van netwerk mislukkings is integraal tot netwerk stabiliteit. Die samestelling van die Internet noodsaak dat die herstel van skakel mislukkings verspreid en dinamies van natuur moet wees. Die herstel-skema van skakel mislukkings word evalueer in terme van die oorleefbaarheid van die netwerk, die mees e ektiewe benutting van network bronne, aanpasbaarheid, en die herstel tydperk van die skema. Die vinnig moontlikste herstel tydperk word genoodsaak deur oombliklike data verkeer soos VoIP en beeld dienste wat oor die Internet gedra word. The doel van hierdie tesis is om bestaande skakel mislukking herstel skemas te evalueer, en dan verder ondersoek in te stel na hul uitbreiding. Daarna word die voorgestelde skakel mislukking skema se e ektiwiteit gemeet.

This master’s thesis deals with the distributed computing and mathematical tools for modelling the distributed systems. Firstly, my attention is focused on a description of the distributed algorithms, characteristic failures for the distributed systems, and mathematical tools for an analysis of the distributed systems.The experimental part is concerned with the impact of stochastic link failures on the chosen parameters of the protocol Push-sum, namely the deviation of the final states from the average value, the convergence rate of the protocol, the distribution of the final states, and the distribution of the convergence rates. My intention is demonstrated using Matlab on a tree, a ring, a line, a star, and a fully-connected mesh topology. Was analyzed two functionalities of the protocol Push-sum, namely an estimation of the average value and an estimation of sum.