Abstract: Increasingly, software should dynamically adapt its behavior at run-time in response to changing conditions in the supporting computing and communication infrastructure, and in the surrounding physical environment. In order for an adaptive program to be trusted, it is important to have mechanisms to ensure that the program functions correctly during and after adaptations. Adaptive programs are generally more difficult to specify, verify, and validate due to their high complexity. Particularly, when involving multi-threaded adaptations, the program behavior is the result of the collaborative behavior of multiple threads and software components. This paper introduces an approach to create formal models for the behavior of adaptive programs. Our approach separates the adaptation behavior and non-adaptive behavior specifications of adaptive programs, making the models easier to specify and more amenable to automated analysis and visual inspection. We introduce a process to construct adaptation models, automatically generate adaptive programs from the models, and verify and validate the models. We illustrate our approach through the development of an adaptive GSM-oriented audio streaming protocol for a mobile computing application.

Abstract: Traditional software development is based on the closed-world assumption that the boundary between system and environment is known and unchanging. However, this assumption no longer works within today's unpredictable open-world settings, especially in ubiquitous and pervasive computing settings, which demand techniques that let software react to changes by self-organizing its structure and self-adapting its behavior. The more we move toward dynamic and heterogeneous systems, and the more we stress their self-healing and self-adapting capabilities, the more we need new approaches to develop these applications and new ways to structure and program them. Programming open systems requires new programming language features. Two features that bear investigation are introspection mechanisms to get runtime information about newly encountered services and reflective mechanisms to adapt client applications dynamically. Some existing standards, industrial products, and research prototypes that support, to a certain extent, the open-world assumptions are service-oriented technologies, publish/subscribe middleware systems, grid infrastructures, autonomic frameworks

Abstract: The advances in computing and communication technologiesand software tools have resulted in an explosive growth innetworked applications and information services that coverall aspects of our life. These services and applications are in-herently complex, dynamic and heterogeneous. In a similarway, the underlying information infrastructure, e.g. the In-ternet, is large, complex, heterogeneous and dynamic, glob-allyaggregatinglargenumbersofindependentcomputingandcommunication resources, data stores and sensor networks.The combination of the two results in application develop-ment, configuration and management complexities that breakcurrent computing paradigms, which are based on static be-haviors, interactions and compositions of components and/orservices.Asaresult,applications,programmingenvironmentsand information infrastructures are rapidly becoming brittle,unmanageable and insecure. This has led researchers to con-sider alternative programming paradigms and managementtechniques that are based on strategies used by biological sys-tems to deal with complexity, dynamism, heterogeneity anduncertainty.Autonomiccomputingisinspiredbythehumanautonomicnervoussystemthathandlescomplexityanduncertainties,andaims at realizing computing systems and applications capableof managing themselves with minimum human intervention.In this paper we first give an overview of the architecture

Abstract: Virtualization was invented more than thirty years ago to allow large expensive mainframes to be easily shared among different application environments. As hardware prices went down, the need for virtualization faded away. More recently, virtualization at all levels (system, storage, and network) became important again as a way to improve system security, reliability and availability, reduce costs, and provide greater flexibility. Virtualization is being used to support server consolidation efforts. In that case, many virtual machines running different application environments share the same hardware resources. This paper shows how autonomic computing techniques can be used to dynamically allocate processing resources to various virtual machines as the workload varies. The goal of the autonomic controller is to optimize a utility function for the virtualized environment. The paper considers dynamic CPU priority allocation and the allocation of CPU shares to the various virtual machines. Results obtained through simulation show that the autonomic controller is capable of achieving its goal.

Abstract: A distributed computing system conforms to a multi-level, hierarchical organizational model. One or more control nodes provide for the efficient and automated allocation and management of computing functions and resources within the distributed computing system in accordance with the organization model. A user, such as a system administrator, interacts with the control nodes to logically define the hierarchical organization of distributed computing system. The control node includes an automation subsystem having one or more rule engines that provide autonomic control of the application nodes in accordance with a set of one or more rules. A pluggable, application-specific application governor is selected and installed within the control node to provide an application-independent interface through which the rule engines interact to control the deployment, execution and monitoring of the applications within the distributed computing system. The application governor uses a set of software image objects to configure an application on an application node. Each of the application software image objects share a common interface and are therefore interchangeable.

Abstract: In the past, the focus of the computer industry has been to improve hardware performance and add more and more features to the software. As a result, more and more appliances surrounding us are equipped with embedded computational power and wireless communication. As such, they become ever more flexible and multifunctional, and almost indispensable in daily life. On the other hand, the resulting systems become increasingly complex and unreliable, posing new challenges to designer and user. Organic Computing (OC) has the vision to address the challenges of complex distributed systems by making them more life-like (organic), i.e. endowing them with abilities such as self- organization, self-configuration, self-repair, or adaptation. The designer's task is simplified, because it is no longer necessary to exactly specify the low-level system behavior in all possible situations that might occur, but instead leaving the system with a certain degree of freedom which allows it to react in an intelligent way to new situations. Also, use of such systems is simplified, as they can be controlled by setting few high-level goals, rather than having to manipulate many low-level parameters with unclear influence. In this paper, we give a general introduction to OC, and propose a generic observer-controller architecture as a framework for designing OC systems. Then, it is shown how to use this architecture at the example of a traffic light controller. The paper concludes with a summary and a discussion of future challenges.

Abstract: Autonomic computing systems reduce software maintenance costs and management complexity by taking on the responsibility for their configuration, optimization, healing, and protection. These tasks are accomplished by switching at runtime to a different system behaviour - the one that is more efficient, more secure, more stable, etc. - while still fulfilling the main purpose of the system. Thus, identifying the objectives of the system, analyzing alternative ways of how these objectives can be met, and designing a system that supports all or some of these alternative behaviours is a promising way to develop autonomic systems. This paper proposes the use of requirements goal models as a foundation for such software development process and demonstrates this on an example.

Abstract: In service oriented systems, Quality of Service (QoS) is a service selection driver. Users evaluate QoS at run time to address their service invocation to the most suitable provider. Thus, QoS has a direct impact on providers' revenues. However, QoS requirements are difficult to satisfy because of the high variability of Internet workloads. Workload variability cannot be accommodated with traditional capacity planning and allocation practices, but requires autonomic computing techniques. Autonomic computing involves two tightly inter-related problems, namely, a short-term resource allocation problem and a long-term capacity planning problem. Capacity planning requires an investment that should be balanced by the revenues obtained through resource allocation. In this paper, we provide a comprehensive framework modelling both problems. The short-term resource allocation problem is analyzed in depth. The paper proposes an optimization model that identifies the optimal resource allocation by maximizing a provider's revenues while satisfying customers QoS constraints and minimizing resource usage cost. Preliminary computational experiments are presented to support the effectiveness of our approach.

Abstract: Software has become pervasive. Despite this success and expansion into daily life, there have, of course, been a number of software-related disasters and near-disasters. Software failures have resulted in giving cancer patients excessive (and lethal) doses of radiation, loss of aircraft and spacecraft, and disclosures of private financial information. We continue to push software to the limits, in many cases using it where failure would be catastrophic, and where many organizations are spending as much as 33 to 50 percent of the total cost of ownership of their computing and communication systems to avoid software failure. Many practitioners believe that self-managing software can potentially ensure safer, more reliable, and cost-effective computer systems. Creating software systems that are self-directed, self-governing, and self-adapting has been the focus of development in autonomic computing, autonomic communications, pervasive computing, organic computing, and adaptive computing.

Abstract: The Business Process Execution Language for Web Services (BPEL4WS or BPEL for short) is an XML-based language for defining business processes that provides an interoperable, portable language for both abstract and executable processes and that was designed from the beginning to operate in the heterogeneity and dynamism that is commonplace in information technology today. BPEL builds on the layers of flexibility provided by the Web Services stack, and especially by XML. In this paper, we provide a brief introduction to BPEL with emphasis on architectural drivers and basic concepts. Then we survey ongoing BPEL work in several application areas: adding quality of service to BPEL, extending BPEL to activities involving humans, BPEL for grid computing, and BPEL for autonomic computing.

Abstract: The evolution of networks and the Internet, which have presented high scalable and available services have made environments more complex. The increasing complexity, cost, and heterogeny in distributed computing systems have motivated researchers to investigate a new idea to cope with the management of complexity in IT industry. For this, Autonomic Computing Systems (ACSs) have been introduced. In this paper, we present a complete survey of ACSs. It consists of characteristics, their effects on quality factors, architecture of ACS building blockes, and challenges.

Abstract: Internet computing is emerging as an important new distributed computing paradigm in which resource intensive computing is integrated over Internet-scale networks. Over these large networks, different users and organizations share their computing resources, and computations take place in a distributed fashion. In such an environment, a framework is needed in which the resource providers are given incentives to share their resources. CompuP2P is a lightweight architecture for enabling Internet computing. It uses peer-to-peer networks for sharing of computing resources. CompuP2P create dynamic markets of network accessible computing resources, such as processing power, memory storage, disk space, etc., in a completely distributed, scalable, and fault-tolerant manner. This paper discusses the system architecture, functionality, and applications of the proposed CompuP2P architecture. We have implemented a Java-based prototype, and our results show that the system is light-weight and can provide almost a perfect speedup for applications that contain several independent compute-intensive tasks

Abstract: Intelligent Spaces - The Vision,the Opportunities, and the Barriers.- The Socio-Economic Impact of Pervasive Computing - Intelligent Spaces and the Organisation of Business.- No Pervasive Computing Without Intelligent Systems.- The Supply Chain.- Care in the Community.- Pervasive Home Environments.- Traffimatics - Intelligent Co-operative Vehicle Highway Systems.- Mixed-Reality Applications in Urban Environments.- A Sensor Network for Glaciers.- Co-operation in the Digital Age - Engendering Trust in Electronic Environments.- Maintaining Privacy in Pervasive Computing - Enabling Acceptance of Sensor-based Services.- RFID Security and Privacy - Issues, Standards, and Solutions.- Ambient Technology - Now You See It, Now You Don't.- Integrated Sensor Networks for Monitoring the Health and Well-Being of Vulnerable Individuals.- Segmentation and Tracking of Multiple Moving Objects for Intelligent Video Analysis.- An Attention-based Approach to Content-based Image Retrieval.- Eye Tracking as a New Interface for Image Retrieval.- The Implications of Pervasive Computing on Network Design.- Autonomic Computing for Pervasive ICT - A Whole-System Perspective.- Scale-Free Topology for Pervasive Networks.- NEXUS - Resilient Intelligent Middleware.- Intelligent Data Analysis for Detecting Behaviour Patterns in iSpaces.- xAssist - Inferring User Goals from Observed Actions.- Programming iSpaces - A Tale of Two Paradigms.

Abstract: The complexity of modern networks raises several challenges in the design and development of communication services. The unbearable costs in configuration and management call for autonomic approaches, in which services are able to self-configure and self-adapt their activities without human intervention. The need for ubiquity of service provisioning calls for the capability of services of adapting their behavior depending on the current situation in which they are used. In this paper, after having discussed the need for innovative approaches facilitating the development and execution of autonomic and situation-aware services, we analyze the key features that should underly such a general approach, propose an architecture centered around the abstraction of "autonomic communication elements", and sketch the main research thrusts to be pursued for the realization of the vision

Abstract: B3G wireless access infrastructures can be realized through the concept of cognitive networks. In a B3G context, a network operator will rely on various alternate wireless access technologies, for realizing the appropriate business goals, such as capacity and QoS levels. Cognitive wireless access networks dynamically change their configuration, and in this respect the radio access technologies and spectrum used at the physical and MAC layers, in order to adapt to environment conditions. A cognitive infrastructure consists of reconfigurable elements and intelligent management functionality. This article focuses on the management part. We present a platform, called m@ANGEL, which adheres to autonomic computing principles, and aims at the provision of seamless cognitive connectivity to the mobile Internet. Our work starts from a business level view of cognitive wireless access networks. Technical requirements for m@ANGEL are identified, and the architecture of the platform is described. Moreover, the article describes the functionality and engineering challenges of the m@ANGEL components, which provide the means for monitoring, discovery, context acquisition, description of profiles/goals/agreements, resource and service brokerage, configuration negotiation, selection, and implementation. Finally, concluding remarks are drawn, and issues for the next phases of our work are identified

Abstract: Autonomic networking set a challenge for the research community to engineer systems and architectures that will increase the QoS and robustness of future network architectures. However, our experience is that so far the autonomic network research community does not have a common perception of what an autonomic network is. This paper attempts to propose a generic model for autonomic systems, along with a minimum set of required properties that would render a system compliant to this model. The paper emphasises the importance of such a common model for the credibility of the research community as well as to eliminate attempts to unnecessarily overload or blur the scope of the field.

Abstract: The increasing heterogeneity, dynamism and uncertainty of emerging DCE (Distributed Computing Environment) systems imply that an application must be able to detect and adapt to changes in its state, its requirements and the state of the system to meet its desired QoS constraints As system and application scales increase, ad hoc heuristic-based approaches to application adaptation and self-management quickly become insufficient This paper builds on the Accord programming system for rule-based self-management and extends it with model-based control and optimization strategies This paper also presents the development of a self-managing data streaming service based on online control using Accord This service is part of a Grid-based fusion simulation workflow consisting of long-running simulations, executing on remote supercomputing sites and generating several terabytes of data, which must then be streamed over a wide-area network for live analysis and visualization The self-managing data streaming service minimize data streaming overheads on the simulations, adapt to dynamic network bandwidth and prevent data loss An evaluation of the service demonstrating its feasibility is presented

Abstract: Ubiquitous computing refers to building a global computing environment where seamless and invisible access to computing resources is provided to the user. Pervasive computing deals with acquiring context knowledge from the environment and providing dynamic, proactive and context-aware services to the user. A Ubiquitous computing environment is created by sharing knowledge and information between Pervasive computing environments. In this paper we propose a framework that uses the potential of the Semantic Web to weave Pervasive computing environments into a Ubiquitous computing environment. We discuss how the collaboration of these Pervasive environments can create an effective Ubiquitous computing environment referred herein as the Integrated Global Pervasive Computing Framework (IGPF). We test the effectiveness of the Ubiquitous environment through a small scenario from a prototype system that we have implemented over this framework to handle medical emergency scenario.

Abstract: The wide deployment of wireless sensor and RFID (Radio Frequency IDentification) devices is one of the key enablers for next-generation pervasive computing applications, including large-scale environmental monitoring and control, context-aware computing, and “smart digital homes”. Sensory readings are inherently unreliable and typically exhibit strong temporal and spatial correlations (within and across different sensing devices); effective reasoning over such unreliable streams introduces a host of new data management challenges. The Data Furnace project at Intel Research and UC-Berkeley aims to build a probabilistic data management infrastructure for pervasive computing environments that handles the uncertain nature of such data as a first-class citizen through a principled framework grounded in probabilistic models and inference techniques.

Abstract: Summary form only given. The increasing complexity of computing systems is beginning to overwhelm the capabilities of software developers and system administrators to design, evaluate, integrate, and manage these systems. Major software and system vendors, such as IBM, HP and Microsoft, along with Telecom suppliers and vendors, such as France Telecom and Motorola Labs, have concluded that the only viable long-term solution is to create computer systems that manage themselves - a vision that is often referred to as autonomic computing. In the last few years, interest in autonomic computing has burgeoned within academia and industry. In 2005, there were at least 15 conferences and workshops devoted to the subject, and new ones are being established for 2006. Many companies such as IBM, Motorola, Intel, HP and Microsoft and several start-ups are actively pursuing research and development efforts in autonomic computing. Such widespread interest is fortunate, because autonomic computing is a broad topic, one that requires contributions from many people in a broad array of fields over a long period of time to reach full fruition. This tutorial will motivate, define, explain and explore autonomic computing, giving attendees a good understanding of its essential relevance to systems and network management today and over the course of the foreseeable future. A typical autonomic computing architecture will be presented, along with several important components of this architecture. This will provide participants with a good understanding of the architectural principles and technologies that contribute to autonomic computing, as well as a sense of the role that emerging standards will play. Participants will learn about how state-of-the-art technologies in policy-based management, artificial intelligence and many other fields are being applied to and developed for future autonomic systems and networks. Particular attention will be paid to change management (e.g., recognizing and accommodating change in users, environmental conditions, business goals, and other factors). One of the most important elements of the tutorial will be systems and networking use cases and scenarios that will be used for illustration throughout. The tutorial will conclude with an exploration of research challenges and an account of some early progress towards them by researchers in industry and academia

Abstract: The continued movement towards converged networks changes the focus to building application services that enable customers to move between different types of service providers based on their needs. Policy management becomes paramount for the rapid deployment and management of these application services. This paper presents the concept of a policy continuum and discusses the importance of modeling and natural languages in the presence of the policy continuum, resulting in a novel architecture suitable for autonomic computing.

Abstract: This paper presents work towards generic policy toolkit support for autonomic computing systems in which the policies themselves can be adapted dynamically and automatically. The work is motivated by three needs: the need for longer-term policy-based adaptation where the policy itself is dynamically adapted to continually maintain or improve its effectiveness despite changing environmental conditions; the need to enable non autonomics-expert practitioners to embed self-managing behaviours with low cost and risk; and the need for adaptive policy mechanisms that are easy to deploy into legacy code. A policy definition language is presented; designed to permit powerful expression of self-managing behaviours. The language is very flexible through the use of simple yet expressive syntax and semantics and facilitates a very diverse policy behaviour space through both hierarchical and recursive uses of language elements. A prototype library implementation of the policy support mechanisms is described. The library reads and writes policies in well-formed XML script. The implementation extends the state of the art in policy-based autonomics through innovations which include support for multiple policy versions of a given policy type, multiple configuration templates and meta-policies to dynamically select between policy instances and templates. Most significantly, the scheme supports hot-swapping between policy instances. To illustrate the feasibility and generalised applicability of these tools, two dissimilar example deployment scenarios are examined. The first is taken from an exploratory implementation of self-managing parallel processing and is used to demonstrate the simple and efficient use of the tools.

Abstract: Disclosed is an improved method and system for implementing DBMS server performance optimization. According to some approaches, the method and system incorporates DBMS wizards recommendations with analytical queuing network models for purpose of evaluating different alternatives and selecting the optimum performance management solution with a set of expectations, enhancing autonomic computing by generating periodic control measures which include recommendation to add or remove indexes and materialized views, change the level of concurrency, workloads priorities, improving the balance of the resource utilization, which provides a framework for a continuous process of the workload management by means of measuring the difference between the actual results and expected, understanding the cause of the difference, finding a new corrective solution and setting new expectations.

Abstract: A system and process for providing adaptable controls to computing applications to facilitate interaction by an operator with displayable content. In a computer system running a computing application, it is advantageous to provide adaptable controls that have the ability to reflect content or feature preferences of operators of computing applications. These dynamic computing application controls cooperate with computing applications to provide additional features to the operator.

Abstract: On demand and autonomic computing will benefit from policy-based management systems which are responsive to new and ambiguous situations and learn from them. In a typical data center, there are thousands of different events reporting system faults, status, and performance information. Their occurrences are unpredictable. In addition, new events and conditions can occur as operating environment changes. Traditional approaches of authoring policies and techniques of implementing policy-based management systems, such as relying entirely on static authoring of simple "if [condition] then [actions]" rules, become insufficient. Hence, new approaches, such as goal policy, utility function etc., to the design and implementation of policy-based management systems have emerged. However, none of these approaches provides a systematic way to enable policies in a policy-based management system to be responsive to new and ambiguous situations. In this paper, we describe a novel method by which policies can be selected or created automatically based on events observed and knowledge learned. This new approach treats the observed event-policy relationship represented by an event-policy matrix as a statistical problem. Using singular value decomposition (SVD) technique, implicit higher order correlations among policies and their associated events are used to estimate the selection or creation of recommended policies based on events found in the observed event set. Initial results have indicated that this approach to policy-based management system is very promising.

Abstract: The complexity of today's distributed computing environments is such that the presence of bugs and security holes is statistically unavoidable. A very promising approach to this issue is to implement a self-protected system, similarly to a natural immune system which has the ability to detect the intrusion of foreign elements and react while it is still in progress. This paper describes an approach relying on component-based software engineering to ease the protection of distributed systems. The knowledge of the application architecture is used to detect foreign activities and to trigger counter measures. We focus on a mean to recognize known and unknown attacks independently from legacy software and avoiding false positives. Hence, the scope of the detected attacks is, for the moment, limited to the detection of illegal communications. We describe how this approach can be applied to provide self-protection for clustered J2ee applications with a very low overhead.

Abstract: The increase in complexity of network management systems and a consequent lack of association to business requirements has driven the need for autonomic communications. By integrating context information, autonomic computing can provide more efficient means to counter technical problems found in complex network systems and at the same time address associated business requirements. In this paper, we propose an autonomic communications architecture that manages complexity through policy-based management where we incorporate a shared information model integrated with knowledge-based reasoning mechanisms to provide self- governaning behavior.

Abstract: Manual administration of complex distributed applications is almost impossible to achieve. On the one side, work in autonomic computing focuses on systems that maintain themselves, driven by high-level policies. Such a self-administration relies on the concept of a control loop. The autonomic computing control loop involves an abstract representation of the system to analyze the situation and to adapt it properly. On the other side, models are currently used to ease design of complex distributed systems. Nevertheless, at runtime, models remain useless, because they are decoupled from the running system, which dynamically evolves. Our proposal, named Dacar, introduces models in the control loop. Using adequate models, it is possible to design and execute both the distributed systems and their autonomic policies. The metamodel suggested in this paper mixes both OMG Deployment and Configuration (OMG D&C) specification and the Event-Condition-Action (ECA) metamodels. This paper addresses the different concerns involved in the control loop and focuses on the metamodel concepts that are required to express entities of the control loop. This paper also gives an overview of our Dacar prototype and illustrates it on a ubiquitous application case study.

Abstract: Autonomic computing addresses increasing complexity in computer-based systems by giving these systems the ability to automatically manage many aspects of their own operation. While many aspects of self-management have been examined in isolation, there is a notable lack of an effective autonomic computing infrastructure publicly available with which these techniques could be integrated, compared, and evaluated. We describe an autonomic computing architecture and accompanying implementation infrastructure constructed on top of the cognitive agent architecture, showing that many of its features map naturally to autonomic computing concepts. By implementing a common infrastructure and providing sample applications, autonomic computing research will be better prepared to develop and evaluate self-management techniques