The Experts below are selected from a list of 168 Experts worldwide ranked by ideXlab platform
Zunguo Huang - One of the best experts on this subject based on the ideXlab platform.
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GCC Workshops - Autonomic Computing for Defense-in-Depth Information Assurance: Architecture and a Case Study
Grid and Cooperative Computing - GCC 2004 Workshops, 2004Co-Authors: Xin Xu, Zunguo Huang, Lei XuanAbstract:In recent years, defense-in-depth information assurance is one of the main focuses in information security research. However, the complexity of information assurance systems increases rapidly with more and more security functions and subsystems being included. In this paper, we propose an autonomic computing architecture for defense-in-depth information assurance systems (DDIAS) so that the increasing complexity of DDIAS can be tackled by distributed autonomous security subsystems with the abilities of self-configuration, self-optimization, self-healing and self-protection. We also present a case study of autonomic computing for distributed emergency response and Incident Recovery, which is usually the last line of in-depth defense. In the case study, we combine the tenure duty method (TDM) with autonomic system architecture to realize autonomic service roaming and dynamic backup. Experiments show that the proposed method greatly improves the survivability of information systems without much loss of quality of service.
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the tenure duty method tdm in the active Incident Recovery research
Lecture Notes in Computer Science, 2003Co-Authors: Zunguo HuangAbstract:When on duty, a server should take charge for everything needed to operate the network information service system, including the switching between service and backup. That is the main idea of tenure duty method (TDM). It is a sharp contrast with the cluster method which has an extra front end load balancer and the domain name resolution method with a dedicated DNS. The idea came from the survivability research, which emphasized the idea of mission critical and sought the goal of recovering the ordinary services rapidly assuming the essential services being secure. So minimize the essential service set is one of the way of trading performance cost for survivability. The implementation of autonomous connection migration and free competition mechanism are the technical support of TDM. The survivability situation of the server is described with the Petri net expression. This is follow by the description of TDM. It featured temporal stochastic tenure and spatial Brown motion model. And finally with the experimental model and the mathematical tool, the paper analyzed the related index showing the survivability of TDM quantitatively.
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APPT - The Tenure Duty Method (TDM) in the Active Incident Recovery Research
Lecture Notes in Computer Science, 2003Co-Authors: Zunguo HuangAbstract:When on duty, a server should take charge for everything needed to operate the network information service system, including the switching between service and backup. That is the main idea of tenure duty method (TDM). It is a sharp contrast with the cluster method which has an extra front end load balancer and the domain name resolution method with a dedicated DNS. The idea came from the survivability research, which emphasized the idea of mission critical and sought the goal of recovering the ordinary services rapidly assuming the essential services being secure. So minimize the essential service set is one of the way of trading performance cost for survivability. The implementation of autonomous connection migration and free competition mechanism are the technical support of TDM. The survivability situation of the server is described with the Petri net expression. This is follow by the description of TDM. It featured temporal stochastic tenure and spatial Brown motion model. And finally with the experimental model and the mathematical tool, the paper analyzed the related index showing the survivability of TDM quantitatively.
Praprut Songchitruksa - One of the best experts on this subject based on the ideXlab platform.
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empirical method for estimating traffic Incident Recovery time
Transportation Research Record, 2010Co-Authors: Xiaosi Zeng, Praprut SongchitruksaAbstract:Incident duration and traffic Recovery time are the two critical periods for any Incident management process. Because Incident durations are available in postevaluation analyses, the reliability of estimating Incident-induced delay depends significantly on the accuracy of Recovery time estimation. The dynamics of the traffic system under the combined impact of recurrent and nonrecurrent congestions are complex and thus make it difficult to quantify the Incident impact from recurrent congestion. This paper extends the difference-in-travel-time method to estimate traffic Recovery time by using both Incident and travel time data. The proposed method uses percentile statistics to establish the background conditions that represent travelers' anticipation under Incident-free conditions and then employs the concept of the difference in the travel time and the information from the Incident database to estimate traffic Recovery time. The variability of estimates of traffic Recovery time was also obtained by using ...
P W Parfomak - One of the best experts on this subject based on the ideXlab platform.
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Pipeline safety and security: Federal programs
Pipeline Safety and Security, 2011Co-Authors: P W ParfomakAbstract:Nearly half a million miles of oil and natural gas transmission pipeline crisscross the United States. While an efficient and fundamentally safe means of transport, many pipelines carry hazardous materials with the potential to cause public injury and environmental damage. The nation’s pipeline networks are also widespread, running alternately through remote and densely populated regions; consequently, these systems are vulnerable to accidents and terrorist attack. The 109th Congress passed the Pipeline Safety Improvement Act of 2006 (P.L. 109-468) to improve pipeline safety and security practices. The 110th Congress passed the Implementing Recommendations of the 9/11 Commission Act of 2007 (P.L. 110-53), which mandated pipeline security inspections and potential enforcement (§ 1557) and required federal plans for critical pipeline security and Incident Recovery (§ 1558). The 111th Congress is overseeing the implementation of these acts and considering new legislation related to the nation’s pipeline network. Recent legislative proposals include the Clean, Affordable, and Reliable Energy Act of 2009 (S. 1333), which would change natural gas pipeline integrity assessment intervals (§ 401); the Transportation Security Administration Authorization Act (H.R. 2220), which would mandate a new federal pipeline security study (§ 406); and the Hazardous Material Transportation Safety Act of 2009 (H.R. 4106), which seeks to improve the collection and use of hazardous material transportation Incident data (§ 203) and increase staffing at the Pipeline and Hazardous Material Safety Administration (§304). The Pipeline and Hazardous Materials Safety Administration (PHMSA), within the Department of Transportation (DOT), is the lead federal regulator of pipeline safety. PHMSA uses a variety of strategies to promote compliance with its safety regulations, including inspections, investigation of safety Incidents, and maintaining a dialogue with pipeline operators. The agency clarifies its regulatory expectations through a range of communications and relies upon a range of enforcement actions to ensure that pipeline operators correct safety violations and take preventive measures to preclude future problems. The Transportation Security Administration (TSA), within the Department of Homeland Security (DHS), is the lead federal agency for security in all modes of transportation—including pipelines. The agency oversees industry’s identification and protection of pipelines by developing security standards; implementing measures to mitigate security risk; building stakeholder relations; and monitoring compliance with security standards, requirements, and regulation. While PHMSA and TSA have distinct missions, pipeline safety and security are intertwined. Although pipeline impacts on the environment remain a concern of some public interest groups, both federal government and industry representatives suggest that federal pipeline programs have been on the right track. As oversight of the federal role in pipeline safety and security continues, Congress may focus on the effectiveness of state pipeline damage prevention programs, the promulgation of low-stress pipeline regulations, federal pipeline safety enforcement, and the relationship between DHS and the DOT with respect to pipeline security, among other provisions in federal pipeline safety regulation. In addition to these specific issues, Congress may wish to assess how the various elements of U.S. pipeline safety and security activity fit together in the nation’s overall strategy to protect transportation infrastructure.
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Pipeline Safety and Security: Federal Programs
2010Co-Authors: P W ParfomakAbstract:This report discusses the United States pipeline networks and their security. The Surface Transportation and Rail Security Act of 2007 (S. 184) would require federal plans for critical pipeline security and Incident Recovery, and would mandate pipeline security inspections and enforcement.
Anthony A Saka - One of the best experts on this subject based on the ideXlab platform.
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Traffic Recovery time estimation under different flow regimes in traffic simulation
Journal of Traffic and Transportation Engineering, 2015Co-Authors: Mansoureh Jeihani, Petronella A James, Anthony A Saka, Anam ArdeshiriAbstract:Incident occurrence and Recovery are critical to the smooth and efficient operations of freeways. Although many studies have been performed on Incident detection, clearance, and management, travelers and traffic managers are unable to accurately predict the length of time required for full traffic Recovery after an Incident occurs. This is because there are no practical studies available to estimate post-Incident Recovery time. This paper estimates post-Incident traffic Recovery time along an urban freeway using traffic simulation and compares the simulation results with shockwave theory calculations. The simulation model is calibrated and validated using a freeway segment in Baltimore, MD. The model explores different flow regimes (traffic intensity) and Incident duration for different Incident severity, and their effects on Recovery time. A total of 726 simulations are completed using VISSIM software. Finally, the impact of congestion and Incident delay on the highway network is quantified by a regression formula to predict traffic Recovery time. The developed regression model predicts post-Incident traffic Recovery time based on traffic intensity, Incident duration, and Incident severity (ratio of lanes closure). In addition, three regression models are developed for different flow regimes of near-capacity, moderate, and low-traffic intensity. The model is validated by collected field data on two different urban freeways.
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estimation of non recurring post Incident traffic Recovery time for different flow regimes comparing shock wave theory and simulation modeling
Transportation Research Board 90th Annual MeetingTransportation Research Board, 2011Co-Authors: Mansoureh Jeihani, Petronella A James, Anthony A SakaAbstract:The aim of this study is to estimate post-Incident traffic Recovery time along a freeway using Monte Carlo simulation techniques and compare the simulation results with shockwave theory calculations to evaluate if the simulated model offers any advantages over the traditional queuing and delay methodology in estimating post-Incident Recovery time. The model investigates the variability within traffic intensity and Incident duration for different lane closures, and their effects on Recovery time. Finally, the impact of congestion and Incident on the highway network is quantified by applying regression formula for determining post-Incident traffic Recovery time. A total of 121 traffic scenarios of traffic intensity (volume to capacity ratio) and Incident duration were simulated for six different random seeds. To derive values for output flow, density, speed and Recovery time, 726 simulations were completed using the VISSIM (4.30) and TransModeler (2.5) traffic simulation models. The reported results in this study are based on the averages from these runs for each traffic scenario. The results indicate that a higher post-Incident Recovery time is estimated for traffic to attain pre-Incident travel conditions using simulation method than the shock wave theory. Shockwave theory only calculates queue dissipation time which does not necessarily equate with the time to return to pre-Incident normal traffic flow condition. The results also indicate that a higher Recovery time is required with each corresponding increase in traffic intensity level and Incident time. In addition, within the same Incident duration, Recovery time increases proportionally as traffic intensity builds. Regression results indicate that traffic Recovery time can be reasonably represented as a nonlinear function of Incident time and traffic intensity. Full traffic Recovery time can be determined after an Incident occurs on a freeway when the nonlinear regression formula derived in this study is used within the defined constraints.
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Estimation of Traffic Recovery Time for Different Flow Regimes on Freeways
2008Co-Authors: Anthony A Saka, Mansoureh Jeihani, Petronella A JamesAbstract:This study attempts to estimate post-Incident traffic Recovery time along a freeway using Monte Carlo simulation techniques. It has been found that there is a linear relationship between post-Incident traffic Recovery time, and Incident time and traffic intensity. For purposes of this paper, the post-Incident Recovery time is defined as that time beyond the clearing of an Incident when pre-Incident traffic conditions are achieved and traffic has returned to normalcy or steady state. The research supports Objective 2.1 of the SHA Business Plan, which seeks to develop measures to enhance the Maryland State Highway Administration’s (SHA's) ability to quantify the impact of congestion and delay on the highway network. In addition, the SHA understands that the capability to reasonably estimate the traffic Recovery time for a given duration of Incident is crucial in quantifying the cost-effectiveness of current/future traffic management programs involving detection and clearance of Incident on freeways. A total of 121 traffic scenarios of traffic intensity (Rho - volume to capacity ratio), Incident duration, and proportion of lane blockage were simulated resulting in a total of 726 experiments. The VISSIM simulation platform was used to derive values for output flow, density, and speed to determine the post-Incident traffic Recovery times. The analysis of simulated data showed that for a given Incident duration and lane blockage scenario, the Recovery time of the traffic increases non-linearly with traffic intensity. The traffic Recovery time becomes uniform (stable) for low and moderate traffic intensity values. A set of linear regression models was developed to reasonably estimate the post-Incident traffic Recovery time using traffic intensity, Incident duration, and proportion of lane blockage as exogenous variables.
Zillur Rahman - One of the best experts on this subject based on the ideXlab platform.
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gender loyalty card membership age and critical Incident Recovery do they moderate experience loyalty relationship
International Journal of Hospitality Management, 2020Co-Authors: Imran Khan, Mobin Fatma, Amjad Shamim, Yatish Joshi, Zillur RahmanAbstract:Abstract The study examines the critical role of customer experience in determining hotel brand loyalty and the moderating role of gender, loyalty card membership, age, and critical Incident Recovery in this relationship. Based on a sample of 408 hotel guests and employing structural equation modeling approach, dimensions that comprise ‘customer experience with hotel brands’—hotel location, hotel staff competence, hotel stay, and ambience, hotel website and social media, and guest-to-guest experience—are found to have relative effects on hotel brand loyalty. The results contribute to hospitality realm by suggesting the moderating effect of gender, loyalty card membership, age, and critical Incident Recovery on customer experience-loyalty relationship. Implications for managerial practice and theory are discussed together with limitations and further research directions.
