A Causal Model to predict the Effect of Business Process Evolution on Quality of Service

International audienceManaging Quality of Service (QoS) of Service-based systems is a key challenge to produce systems that fulfill their requirements. Verifying the respect of a QoS contract in a system becomes more and more difficult as systems are more and more complex. Moreover, systems have to evolve in order to fulfil constantly changing requirements. As QoS properties are influenced by hidden factors such as connection rate or the system execution itself, determining the cause of a performance degradation is not mainstream. We propose in this paper to identify the causal relations to make explicit the hidden factors of influence. We more specifically focus on the consequences of system evolution with respect to QoS properties: using causal relations, we aim at predicting the possible overhead caused by an evolution. This paper shows through an example of Business Process how our evolution analysis helps to understand the effect of evolution on QoS property such as the Response Time. We show its efficiency by comparing the prediction with measured values

QoSME: QoS Management Environment

Distributed multimedia applications are sensitive to the Quality of Service (QoS) delivered by underlying communication networks. For example, a video conference exchange can be very sensitive to the effective network throughput. Network jitter can greatly disrupt a speech stream. The main question this thesis addresses is how to adapt multimedia applications to the QoS delivered by the network and vice versa. Such adaptation is especially important because current networks are unable to assure the QoS required by applications and the latter is usually unprepared for periods of QoS degradation. This work introduces the QoS Management Environment (QoSME) that provides mechanisms for such adaptation. The main contributions of this thesis are: Language level abstractions for QoS management. The Quality Assurance Language (QuAL) in QoSME enables the specification of how to allocate, monitor, analyze, and adapt to delivered QoS. Applications can express in QuAL their QoS needs and how to handle potential violations. Automatic QoS monitoring. QoSME automatically generates the instrumentation to monitor QoS when applications use QuAL constructs. The QoSME runtime scrutinizes interactions among applications, transport protocols, and Operating Systems (OS) and collects in QoS Management Information Bases (MIBs) statistics on the QoS delivered. Integration of QoS and standard network management. A Simple Network Management Protocol (SNMP) agent embedded in QoSME provides QoS MIB access to SNMP managers. The latter can use this feature to monitor end-to-end QoS delivery and adapt network resource allocation and operations accordingly. A partial prototype of QoSME has been released for public access. It runs on SunOS 4.3 and Solaris 2.3 and supports communication on ATM adaptation layer, ST-II, UDP/IP, TCP/IP, and Unix internal protocols

QuAL: Quality Assurance Language

Distributed multimedia applications are sensitive to the Quality of Services (QoS) provided by their computing and communication environment. For example, scheduling of processing activities or network queueing delays may cause excessive jitter in a speech stream, rendering it difficult to understand. It is thus important to establish effective technologies to ensure delivery of QoS required by distributed multimedia applications. This proposal presents a new language for the development of distributed multimedia applications: Quality Assurance Language (QuAL). QuAL abstractions allow the specification of QoS constraints expected from the underlying computing and communication environment. QuAL specifications are compiled into run time components that monitor the actual QoS delivered. Upon QoS violations, application provided exception handlers are signaled to act upon the faulty events. Language level abstractions of QoS shelter programs from the heterogeneity of underlying infrastructures. This simplifies the development and maintenance of multimedia applications and promotes their portability and reuse. QuAL generates Management Information Bases (MIBs) that contain QoS statistics per application. Such MIBs may be used to integrate application level QoS management into standard network management frameworks

Efficient runtime management for enabling sustainable performance in real-world mobile applications

Mobile devices have become integral parts of our society. They handle our diverse computing needs from simple daily tasks (i.e., text messaging, e-mail) to complex graphics and media processing under a limited battery budget. Mobile system-on-chip (SoC) designs have become increasingly sophisticated to handle performance needs of diverse workloads and to improve user experience. Unfortunately, power and thermal constraints have also emerged as major concerns. Increased power densities and temperatures substantially impair user experience due to frequent throttling as well as diminishing device reliability and battery life. Addressing these concerns becomes increasingly challenging due to increased complexities at both hardware (e.g., heterogeneous CPUs, accelerators) and software (e.g., vast number of applications, multi-threading). Enabling sustained user experience in face of these challenges requires (1) practical runtime management solutions that can reason about the performance needs of users and applications while optimizing power and temperature; (2) tools for analyzing real-world mobile application behavior and performance. This thesis aims at improving sustained user experience under thermal limitations by incorporating insights from real-world mobile applications into runtime management. This thesis first proposes thermally-efficient and Quality-of-Service (QoS) aware runtime management techniques to enable sustained performance. Our work leverages inherent QoS tolerance of users in real-world applications and introduces QoS-temperature tradeoff as a viable control knob to improve user experience under thermal constraints. We present a runtime control framework, QScale, which manages CPU power and scheduling decisions to optimize temperature while strictly adhering to given QoS targets. We also design a framework, Maestro, which provides autonomous and application-aware management of QoS-temperature tradeoffs. Maestro uses our thermally-efficient QoS control framework, QScale, as its foundation. This thesis also presents tools to facilitate studies of real-world mobile applications. We design a practical record and replay system, RandR, to generate repeatable executions of mobile applications. RandR provides this capability by automatically reproducing non-deterministic input sources in mobile applications such as user inputs and network events. Finally, we focus on the non-deterministic executions in Android malware which seek to evade analysis environments. We propose the Proteus system to identify the instruction-level inputs that reveal analysis environments

A COGNITIVE ARCHITECTURE FOR AMBIENT INTELLIGENCE

L’Ambient Intelligence (AmI) è caratterizzata dall’uso di sistemi pervasivi per monitorare l’ambiente e modificarlo secondo le esigenze degli utenti e rispettando vincoli definiti globalmente. Questi sistemi non possono prescindere da requisiti come la scalabilità e la trasparenza per l’utente. Una tecnologia che consente di raggiungere questi obiettivi è rappresentata dalle reti di sensori wireless (WSN), caratterizzate da bassi costi e bassa intrusività. Tuttavia, sebbene in grado di effettuare elaborazioni a bordo dei singoli nodi, le WSN non hanno da sole le capacità di elaborazione necessarie a supportare un sistema intelligente; d’altra parte senza questa attività di pre-elaborazione la mole di dati sensoriali può facilmente sopraffare un sistema centralizzato con un’eccessiva quantità di dettagli superflui. Questo lavoro presenta un’architettura cognitiva in grado di percepire e controllare l’ambiente di cui fa parte, basata su un nuovo approccio per l’estrazione di conoscenza a partire dai dati grezzi, attraverso livelli crescenti di astrazione. Le WSN sono utilizzate come strumento sensoriale pervasivo, le cui capacità computazionali vengono utilizzate per pre-elaborare i dati rilevati, in modo da consentire ad un sistema centralizzato intelligente di effettuare ragionamenti di alto livello. L’architettura proposta è stata utilizzata per sviluppare un testbed dotato degli strumenti hardware e software necessari allo sviluppo e alla gestione di applicazioni di AmI basate su WSN, il cui obiettivo principale sia il risparmio energetico. Per fare in modo che le applicazioni di AmI siano in grado di comunicare con il mondo esterno in maniera affidabile, per richiedere servizi ad agenti esterni, l’architettura è stata arricchita con un protocollo di gestione distribuita della reputazione. È stata inoltre sviluppata un’applicazione di esempio che sfrutta le caratteristiche del testbed, con l’obiettivo di controllare la temperatura in un ambiente lavorativo. Quest’applicazione rileva la presenza dell’utente attraverso un modulo per la fusione di dati multi-sensoriali basato su reti bayesiane, e sfrutta questa informazione in un controllore fuzzy multi-obiettivo che controlla gli attuatori sulla base delle preferenze dell’utente e del risparmio energetico.Ambient Intelligence (AmI) systems are characterized by the use of pervasive equipments for monitoring and modifying the environment according to users’ needs, and to globally defined constraints. Furthermore, such systems cannot ignore requirements about ubiquity, scalability, and transparency to the user. An enabling technology capable of accomplishing these goals is represented by Wireless Sensor Networks (WSNs), characterized by low-costs and unintrusiveness. However, although provided of in-network processing capabilities, WSNs do not exhibit processing features able to support comprehensive intelligent systems; on the other hand, without this pre-processing activities the wealth of sensory data may easily overwhelm a centralized AmI system, clogging it with superfluous details. This work proposes a cognitive architecture able to perceive, decide upon, and control the environment of which the system is part, based on a new approach to knowledge extraction from raw data, that addresses this issue at different abstraction levels. WSNs are used as the pervasive sensory tool, and their computational capabilities are exploited to remotely perform preliminary data processing. A central intelligent unit subsequently extracts higher-level concepts in order to carry on symbolic reasoning. The aim of the reasoning is to plan a sequence of actions that will lead the environment to a state as close as possible to the users’ desires, taking into account both implicit and explicit feedbacks from the users, while considering global system-driven goals, such as energy saving. The proposed conceptual architecture was exploited to develop a testbed providing the hardware and software tools for the development and management of AmI applications based on WSNs, whose main goal is energy saving for global sustainability. In order to make the AmI system able to communicate with the external world in a reliable way, when some services are required to external agents, the architecture was enriched with a distributed reputation management protocol. A sample application exploiting the testbed features was implemented for addressing temperature control in a work environment. Knowledge about the user’s presence is obtained through a multi-sensor data fusion module based on Bayesian networks, and this information is exploited by a multi-objective fuzzy controller that operates on actuators taking into account users’ preference and energy consumption constraints

Processing Structured Hypermedia : A Matter of Style

With the introduction of the World Wide Web in the early nineties, hypermedia has become the uniform interface to the wide variety of information sources available over the Internet. The full potential of the Web, however, can only be realized by building on the strengths of its underlying research fields. This book describes the areas of hypertext, multimedia, electronic publishing and the World Wide Web and points out fundamental similarities and differences in approaches towards the processing of information. It gives an overview of the dominant models and tools developed in these fields and describes the key interrelationships and mutual incompatibilities. In addition to a formal specification of a selection of these models, the book discusses the impact of the models described on the software architectures that have been developed for processing hypermedia documents. Two example hypermedia architectures are described in more detail: the DejaVu object-oriented hypermedia framework, developed at the VU, and CWI's Berlage environment for time-based hypermedia document transformations

On the Use of Hybrid Heuristics for Providing Service to Select the Return Channel in an Interactive Digital TV Environment

The technologies used to link the end-user to a telecommunication infrastructure, has been changing over time due to the consolidation of new access technologies. Moreover, the emergence of new tools for information dissemination, such as interactive digital TV, makes the selection of access technology, factor of fundamental importance. One of the greatest advantages of using digital TV as means to disseminate information is the installation of applications. In this chapter, a load characterization of a typical application embedded in a digital TV is performed to determine its behavior. However, it is important to note that applications send information through an access technology. Therefore, this chapter, based on the study on load characterization, developed a methodology combining Bayesian networks and technique for order preference by similarity to ideal solution (TOPSIS) analytical approach to provide support to service providers to opt for a technology (power line communication, PLC, wireless, wired, etc.) for the return channel