Phase-type Distributions

Abstract Both analytical (Chapter ??) and simulation-and experimentation-based (Chapter ??) approaches to resilience assessment rely on models for the various phenomena that may affect the system under study. These models must be both accurate, in that they reflect the phenomenon well, and suitable for the chosen approach. Analytical methods require models that are analytically tractable, while methods for experimentation, such as fault-injection (see Chapter ??), require the efficient generation of random-variates from the models. Phase-type (PH) distributions are a versatile tool for modelling a wide range of real-world phenomena. These distributions can capture many important aspects of measurement data, while retaining analytical tractability and efficient random-variate generation. This chapter provides an introduction to the use of PH distributions in resilience assessment. The chapter starts with a discussion of the mathematical basics. We then describe tools for fitting PH distributions to measurement data, before illustrating application of PH distributions in analysis and in random-variate generation

Privacy-Preserving Crowd Incident Detection: A Holistic Experimental Approach

International audienceDetecting dangerous situations is crucial for emergency management. Surveillance systems detect dangerous situations by analyzing crowd dynamics. This paper presents a holis-tic video-based approach for privacy-preserving crowd density estimation. Our experimental approach leverages distributed , on-board pre-processing, allowing privacy as well as the use of low-power, low-throughput wireless communications to interconnect cameras. We developed a multi-camera grid-based people counting algorithm which provides the density per cell for an overall view on the monitored area. This view comes from a merger of infrared and Kinect camera data. We describe our approach using a layered model for data aggregation and abstraction together with a work-flow model for the involved software components, focusing on their functionality. The power of our approach is illustrated through the real-world experiment that we carried out at the Schönefeld airport in the city of Berlin

Multi-Camera Crowd Monitoring: The SAFEST Approach

International audienceThis paper presents the current state of people counting approach created for the SAFEST project. A video based surveillance system for monitoring crowd behaviour is developed. The system detects dangerous situations by analysing the dynamics of the crowd density. Therefore we developed a grid-based people counting algorithm which provides density per cell for the global view on the monitored area. Since multiple cameras may observe same parts of the monitored area, the challenge is not only to count people seen by single cameras , but also to merge the views. Therefore we first detect people seen by each camera separately and then sum the results to a global representation. In order to avoid multiple counting of same objects, the output of cameras in the overlapped regions are weighted

Area & Perimeter Surveillance in SAFEST using Sensors and the Internet of Things

International audienceSAFEST is a project aiming to provide a comprehensive solution to ensure the safety and security of the general public and critical infrastructures. The approach of the project is to design a lightweight, distributed system using heterogeneous, networked sensors, able to aggregate the input of a wide variety of signals (e.g. camera, PIR, radar, magnetic, seismic, acoustic). The project aims for a proof-of-concept demonstration focusing on a concrete scenario: crowd monitoring, area and perimeter surveillance in an airport, realized with a prototype of the system, which must be deployable and foldable overnight, and leverage autoconfiguration based on wireless communications and Internet of Things. This paper reviews the progress towards reaching this goal, which is planned for 2015

SFERA: A simulation framework for the performance evaluation of restart algorithms in service-oriented systems

In service-oriented systems, fault detection and localisation are not straightforward, and client-side fault-tolerance techniques are required to reduce the impact of faults on the quality of service experienced by the user. Restart is a well-known client-side technique for improving performance and service availability. With restart, tasks whose completion-time exceeds a timeout are re-issued by the client, with the goal of obtaining a shorter completion-time on the next attempt. Evaluation of restart should be performed by a combination of analysis, simulation, and measurement. In this paper we present the SFERA framework for simulation of restart in complex SOA systems. We illustrate SFERA features with an evaluation of the optimal restart timeout in a complex SOA system. We simulate a SOA system using different scenarios and model component response-times by phase-type distributions fitted to measurements from a SOA testbed. We observe and compare completion times for different scenarios

Phase-type distributions

Both analytical (Chap. 6) and simulation- and experimentation-based (Chap. 17) approaches to resilience assessment rely on models for the various phenomena that may affect the system under study. These models must be both accurate, in that they reflect the phenomenon well, and suitable for the chosen approach. Analytical methods require models that are analytically tractable, while methods for experimentation, such as fault-injection (see Chap. 13), require the efficient generation of random-variates from the models. Phase-type (PH) distributions are a versatile tool for modelling a wide range of real-world phenomena. These distributions can capture many important aspects of measurement data, while retaining analytical tractability and efficient random-variate generation. This chapter provides an introduction to the use of PH distributions in resilience assessment. The chapter starts with a discussion of the mathematical basics. We then describe tools for fitting PH distributions to measurement data, before illustrating application of PH distributions in analysis and in random-variate generation

Multiple class G-networks with restart

Restart is a common technique for improving response-times in complex systems where the causes of delays can either not be discerned, or not be addressed by the user. With restart, the user aborts a running job that exceeds a deadline, and resubmits it to the system immediately. In many common scenarios, this approach can reduce the response-times that the user experiences. Restart has been well-studied for scenarios where only one user applies restart, and typically in cases where queueing effects can be neglected. In this paper we approach the question of restart in a scenario where restart is applied by many users in a system that can be modelled as an open queueing network. We apply the G-Networks formalism to this problem. We use negative customers to model the abortion and retry of a request. The open G-network uses multiple classes with phase-type distributed service times. This allows the approximation of a preemptive repeat different behaviour as it is natural for multiple restarts of a request. We compute the response time of a request and show that an optimal restart interval can be found. The results are compared with simulation

Area & perimeter surveillance in SAFEST using sensors and the Internet of Things: Paper presented at Interdisciplinaire sur la Securite Globale, WISG 2014, Troyes, 30-31 January 2014

SAFEST is a project aiming to provide a comprehensive solution to ensure the safety and security of the general public and critical infrastructures. The approach of the project is to design a lightweight, distributed system suing heterogeneous, networked sensors, able to aggregate the input of a wide variety of signals (e.g; camera, PIR, radar, magnetic, seismic, acoustic). The project aims for a proof-of-concept demonstration focusing on a concrete scenario: crowd monitoring, area and perimeter surveillance in an airport, realized with a prototype of the system, which must thus be deployable and foldable overnight, and leverage autoconfiguration based on wireless communications and Internet of Things. This paper reviews the progress towards reaching this goal, which is planned for 2015