% % GENERATED FROM http://acme.able.cs.cmu.edu % by : anonymous % IP : ec2-44-222-233-8.compute-1.amazonaws.com % at : Fri, 29 Mar 2024 06:48:10 -0400 GMT % % Selection : Author: Vahe_Poladian % @Article{Poladian2006, AUTHOR = {Sousa, Jo\~{a}o and Poladian, Vahe and Garlan, David and Schmerl, Bradley and Shaw, Mary}, TITLE = {Task-Based Adaptation for Ubiquitous Computing}, YEAR = {2006}, MONTH = {May}, JOURNAL = {IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, Special Issue on Engineering Autonomic Systems}, VOLUME = {36}, NUMBER = {3}, PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/tbuc.pdf}, ABSTRACT = {An important domain for autonomic systems is the area of ubiquitous computing: users are increasingly surrounded by technology that is heterogeneous, pervasive, and variable. In this paper we describe our work in developing self-adapting computing infrastructure that automates the configuration and reconfiguration of such environments. Focusing on the engineering issues of self-adaptation in the presence of heterogeneous platforms, legacy applications, mobile users, and resource variable environments, we describe a new approach based on the following key ideas: (a) Explicit representation of user tasks allows us to determine what service qualities are required of a given configuration; (b) Decoupling task and preference specification from the lower level mechanisms that carry out those preferences provides a clean engineering separation of concerns between what is needed and how it is carried out; and (c) Efficient algorithms allow us to calculate in real time near-optimal resource allocations and reallocations for a given task.}, NOTE = {Also available at IEEE Xplore}, KEYWORDS = {Aura, Autonomic Systems, Ubiquitous Computing} } @InProceedings{Sousa2005, AUTHOR = {Sousa, Jo\~{a}o and Poladian, Vahe and Garlan, David and Schmerl, Bradley}, TITLE = {Capitalizing on Awareness of User Tasks for Guiding Adaptation.}, YEAR = {2005}, BOOKTITLE = {Proceedings of the First International Workshop on Adaptive and Self-managing Enterprise Applications, at CAISE'05}, ADDRESS = {Portugal}, PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/asmea05.pdf}, ABSTRACT = {Computers support more and more tasks in the personal and professional activities of users. Such user tasks increasingly span large periods of time and many locations across the enterprise space and beyond. Recently there has been a growing interest in developing applications that can cope with the specific environmental conditions at each location, and adapt to dynamic changes in system resources. However, in a given situation there may be many possible configuration solutions, and an awareness of the user's intent for each task is a critical element in knowing which one to pick. In this paper, we discuss the limitations of building such awareness into applications, and propose to factor the awareness of user tasks into a common software layer. That however, brings up the problem of coordinating the system-wide adaptation performed by such a layer with fine-grain adaptation performed by resource-aware applications. We summarize the main features of an architectural framework that incorporates such a layer, and distill some of the lessons learned in implementing the framework.}, KEYWORDS = {Aura, Autonomic Systems, Ubiquitous Computing} } @InProceedings{Poladian2005, AUTHOR = {Poladian, Vahe and Sousa, Jo\~{a}o and Padberg, Frank and Shaw, Mary}, TITLE = {Anticipatory Configuration of Resource-aware Applications}, YEAR = {2005}, MONTH = {May}, BOOKTITLE = {Proceedings of the 7th International Workshop on Economics Driven Software Engineering Research, affiliated with the 27th International Conference on Software Engineering}, ADDRESS = {St. Louis, MS}, PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/edser7.pdf}, ABSTRACT = {We propose an improved approach to dynamic configuration of resource-aware applications. The new anticipatory model of configuration maximizes utility based on three inputs: user preferences, application capability profiles, and resource availability. In this respect, the proposed model is similar to a model of configuration described in [2]. However, the latter addresses the dynamic nature of the problem by reacting to changes (such as decrease in resource availability), and maximizes the utility in a point-wise manner. The newly proposed anticipatory approach explicitly models the duration of the task and leverages possible information about the future (such as stochastic resource availability over the expected duration of the task). We expect that the anticipatory model will improve user's utility, conserve scarce resources, and reduce the amount of disruption to the user resulting from changes when compared to the reactive model. However, the optimization problem underlying the anticipatory model is computationally more difficult than the problem underlying the reactive model. We would like to investigate if the anticipatory approach is feasible and efficient in practice while delivering the above-mentioned improvements. In this paper, we carefully state the model of anticipatory configuration, highlight the sources of complexity in the problem, propose an algorithm to the anticipatory configuration problem, and provide a roadmap for research.}, KEYWORDS = {Dynamic Configuration, Aura} } @InProceedings{Garlan2004a, AUTHOR = {Garlan, David and Poladian, Vahe and Schmerl, Bradley and Sousa, Jo\~{a}o}, TITLE = {Task-based Self-adaptation}, YEAR = {2004}, MONTH = {31 October - 1 November}, BOOKTITLE = {Proceedings of the ACM SIGSOFT 2004 Workshop on Self-Managing Systems (WOSS'04)}, ADDRESS = {Newport Beach, CA}, PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/woss04.pdf}, ABSTRACT = {Recently there has been increasing interest in developing systems that can adapt dynamically to cope with changing environmental conditions and unexpected system errors. Most efforts for achieving self-adaptation have focused on the mechanisms for detecting opportunities for improvement and then taking appropriate action. However, such mechanisms beg the question: what is the system trying to achieve? In a given situation there may be many possible adaptations, and knowing which one to pick is a difficult question. In this paper we advocate the use of explicit representation of user task as a critical element in addressing this missing link.}, KEYWORDS = {Autonomic Systems, Self-Repair} } @InProceedings{Poladian2004, AUTHOR = {Poladian, Vahe and Sousa, Jo\~{a}o and Garlan, David and Shaw, Mary}, TITLE = {Dynamic Configuration of Resource-Aware Services}, YEAR = {2004}, MONTH = {23-28 May}, BOOKTITLE = { Proceedings of the 26th International Conference on Software Engineering}, ADDRESS = {Edinburgh, Scotland}, PDF = {http://www.cs.cmu.edu/afs/cs/project/able/ftp/aura_icse04/aura_icse04.pdf}, ABSTRACT = {An important emerging requirement for computing systems is the ability to adapt at run time, taking advantage of local computing devices, and coping with dynamically changing resources. Three specific technical challenges in satisfying this requirement are to (1) select an appropriate set of applications or services to carry out a user s task, (2) allocate (possibly scarce) resources among those applications, and (3) reconfigure the applications or resource assignments if the situation changes. In this paper we show how to provide a shared infrastructure that automates configuration decisions given a specification of the user s task. The heart of the approach is an analytical model and an efficient algorithm that can be used at run time to make near-optimal (re)configuration decisions. We validate this approach both analytically and by applying it to a representative scenario.}, KEYWORDS = {Mult-fidelity Applications, Resource Allocation, Resource Aware Computing, Service Composition, Ubiquitous Computing} } @InProceedings{Poladian2003, AUTHOR = {Kumar, Rajnish and Poladian, Vahe and Greenberg, Ira and Messer, Alan and Milojicic, Dejan}, TITLE = {Selecting Devices for Aggregation}, YEAR = {2003}, BOOKTITLE = {Proceedings of the 5th IEEE Workshop on Mobile Computing Systems and Applications (WMCSA 2003)}, ABSTRACT = {As intelligent devices become affordable and wireless infrastructure becomes pervasive, the potential to combine, or aggregate, device functionality to provide a user with a better experience grows. Often, there will be multiple devices providing similar functionality that the user will have to choose from for the aggregation. This paper presents the design and prototype implementation of a system for automatic selection of devices for aggregation in a dynamic environment. It allows a user to express trade-offs between the quality of device attributes, user distraction, and aggregation stability. This approach enables a user to have a richer experience without having to constantly worry about the device and the environment details.}, KEYWORDS = {Resource Aware Computing, Service Composition} } @InProceedings{Poladian2003a, AUTHOR = {Poladian, Vahe and Butler, Shawn and Shaw, Mary and Garlan, David}, TITLE = {Time is Not Money: The case for multi-dimensional accounting in value-based software engineering}, YEAR = {2003}, MONTH = {May}, BOOKTITLE = {Fifth Workshop on Economics-Driven Software Engineering Research (EDSER-5)}, PDF = {http://www.cs.cmu.edu/afs/cs/project/able/ftp/EDSER5/paper.pdf}, ABSTRACT = {'Time is money', or so goes the old saying. Perhaps influenced by this aphorism, some strategies for incorporating costs in the analysis of software design express all costs in currency units for reasons of simplicity and tractability. Indeed, in theoretical economics all costs can, in principle, be expressed in dollars. Software engineering problems, however, often present situations in which converting all costs to a common currency is problematical. In this paper we pinpoint some of these situations and the underlying causes of the problems, and we argue that it is often better to treat costs as a multidimensional value, with dimensions corresponding to distinct types of resources. We go on to highlight the differences among cost dimensions that need to be considered when developing cost-benefit analyses, and we suggest mechanisms for mediating among heterogeneous cost dimensions.}, KEYWORDS = {Mult-fidelity Applications, Resource Allocation, Resource Aware Computing} } @InProceedings{Poladian2002, AUTHOR = {Poladian, Vahe and Garlan, David and Shaw, Mary}, TITLE = {Selection and Configuration in Mobile Environments: A Utility-Based Approach}, YEAR = {2002}, MONTH = {May}, BOOKTITLE = {Fourth Workshop on Economics-Driven Software Engineering Research (EDSER-4)}, PDF = {http://www.cs.cmu.edu/afs/cs/project/able/ftp/EDSER4/EDSER.pdf}, ABSTRACT = {Users of low-power mobile computing platforms make ad hoc decisions when choosing software components among alternatives and configuring those components. We propose applying utility-theoretic models, which can help determine optimal allocation of scarce resources to applications given the user's utility and application resource usage. We believe that taking into consideration resource consumption and applying microeconomic models has the potential of improving the user's satisfaction with the system. In this paper, we formulate the problem, demonstrate the use of a microeconomics-based model on a simple version of the problem, and list possible solutions. Further, we identify issues typical of mobile environments that are not addressed by existing research, and propose ways of tackling these issues.} } @TechReport{Sousa2005b, AUTHOR = {Sousa, Jo\~{a}o and Balan, Rajesh and Poladian, Vahe and Garlan, David and Satyanarayanan, Mahadev}, TITLE = {Giving Users the Steering Wheel for Guiding Resource-Adaptive Systems}, YEAR = {2005}, MONTH = {December}, NUMBER = {CMU-CS-05-198}, INSTITUTION = {Carnegie Mellon University School of Computer Science}, KEYWORDS = {Aura, Mult-fidelity Applications, Resource Allocation, Service Composition, Ubiquitous Computing} } @InProceedings{Poladian2007, AUTHOR = {Poladian, Vahe and Garlan, David and Shaw, Mary and Schmerl, Bradley and Sousa, Jo\~{a}o and Satyanarayanan, Mahadev}, TITLE = {Leveraging Resource Prediction for Anticipatory Dynamic Configuration}, YEAR = {2007}, MONTH = {8-11 July}, BOOKTITLE = { Proceedings of the First IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO-2007}, PAGES = {214-223}, PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/predictive_configuration_16_marked.pdf}, ABSTRACT = {Self-adapting systems based on multiple concurrent applications must decide how to allocate scarce resources to applications and how to set the quality parameters of each application to best satisfy the user. Past work has made those decisions with analytic models that used current resource availability information: they react to recent changes in resource availability as they occur, rather than anticipating future availability. These reactive techniques may model each local decision optimally, but the accumulation of decisions over time nearly always becomes less than optimal. In this paper, we propose an approach to self adaptation, called anticipatory configuration that leverages predictions of future resource availability to improve utility for the user over the duration of the task. The approach solves the following technical challenges: (1) how to express resource availability prediction, (2) how to combine prediction from multiple sources, and (3) how to leverage predictions continuously while improving utility to the user. Our experiments show that when certain adaptation operations are costly, anticipatory configuration provides better utility to the user than reactive configuration, while being comparable in resource demand.}, KEYWORDS = {Aura, Dynamic Configuration, Resource Aware Computing, Service Composition, Ubiquitous Computing} } @InProceedings{Poladian:2007:iwlu, AUTHOR = {Poladian, Vahe and Shaw, Mary and Garlan, David}, TITLE = {Modeling Uncertainty of Predictive Inputs in Anticipatory Dynamic Configuration}, YEAR = {2007}, MONTH = {5 November}, BOOKTITLE = {Proceedings of the International Workshop on Living with Uncertainties (IWLU'07), co-located with the 22nd International Conference on Automated Software Engineering (ASE'07),}, ADDRESS = {Atlanta, GA, USA}, PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/uncertainty_in_configuration_v5.1.pdf}, ABSTRACT = {Dynamic adaptive systems based on multiple concurrent applications typically employ optimization models to decide how to allocate scarce resources among the applications and how to tune their runtime settings for optimal quality-of-service according to the preferences of an end user. Traditionally, such systems have avoided dealing with uncertainty by assuming that current snapshots of the relevant inputs are precise and by solving for an optimal system point. To achieve dynamic behavior, a system performs an optimization loop upon discovering changes in the input variables (e.g. changes in the available level of resources) and adapts the applications according to the new optimal solution. Unfortunately, when certain adaptation actions incur costs, such reactive adaptation strategies suffer from a significant shortcoming: several locally optimal decisions over time may often be less than optimal globally. By using predictive information about the future values of the problem inputs, we can model and implement an anticipatory adaptation strategy that helps improve the global behavior of the system in many situations. However, modeling predictions requires representing and dealing with uncertainty from different sources. In this paper, we describe our proposed approach to represent multiple sources of uncertainty and outline algorithms for solving the anticipatory configuration problem with predictive inputs.}, NOTE = {<a href=http://godzilla.cs.toronto.edu/IWLU/program.html>http://godzilla.cs.toronto.edu/IWLU/program.html</a>;}, KEYWORDS = {Aura, Dynamic Configuration, Resource Allocation, Resource Aware Computing, Ubiquitous Computing, uncertainty} } @InProceedings{Sousa2008-WICSA, AUTHOR = {Sousa, Jo\~{a}o and Schmerl, Bradley and Poladian, Vahe and Brodsky, Alex}, TITLE = {UDesign: End-User Design Applied to Monitoring and Control Applications for Smart Spaces}, YEAR = {2008}, MONTH = {18-22 February}, BOOKTITLE = {Proceedings of the 2008 Working IFIP/IEEE Conference on Software Architecture}, ADDRESS = {Vancouver, BC, Canada}, PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/uDesign-final.pdf}, ABSTRACT = {This paper introduces an architectural style for enabling end-users to quickly design and deploy software systems in domains characterized by highly personalized and dynamic requirements. The style offers an intuitive metaphor based on boxes, pipes, and wires, but retains enough preciseness that systems can be automatically assembled and dynamically reconfigured based on uDesign descriptions. uDesign was primarily motivated and validated within monitoring and control applications for smart spaces, but we envision possible extensions to other domains. Our contribution differs from early attempts at end-user programming in the level of abstraction, software architecture rather than programming, and in the subject of description: run-time rather than code structures. To validate the approach, the paper presents (a) two case studies, one in health care and one in home security, (b) the formal semantics of uDesign’s primitives, and (c) a mapping of those primitives to an existing software infrastructure: the Aura infrastructure.}, KEYWORDS = {Architectural Style, Aura, Service Composition, Ubiquitous Computing} } @InProceedings{Sousa2008a, AUTHOR = {Sousa, Jo\~{a}o and Poladian, Vahe and Garlan, David and Schmerl, Bradley and Steenkiste, Peter}, TITLE = {Steps toward Activity-Oriented Computing}, YEAR = {2008}, MONTH = {14 April}, BOOKTITLE = {Proceedings of the 2008 NSF Next Generation Software Program Workshop}, ADDRESS = {Miami, FL}, PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/IPDPS-web.pdf}, ABSTRACT = {Most pervasive computing technologies focus on helping users with computer-oriented tasks. In this NSF-funded project, we instead focus on using computers to support user-centered “activities” that normally do not involve the use of computers. Examples may include everyday tasks around such as answering the doorbell or doing laundry. A focus on activity-based computing brings to the foreground a number of unique challenges. These include activity definition and representation, system design, interfaces for managing activities, and ensuring robust operation. Our project focuses on the first two challenges.}, KEYWORDS = {Aura, Ubiquitous Computing} } @PhdThesis{Poladian2008:Thesis, AUTHOR = {Poladian, Vahe}, TITLE = {Tailoring Configuration to User's Tasks under Uncertainty}, YEAR = {2008}, MONTH = {April}, SCHOOL = {Carnegie Mellon University}, URL = {http://reports-archive.adm.cs.cmu.edu/anon/2008/abstracts/08-121.html}, ABSTRACT = {The expansion of computing infrastructure has opened the possibility of a world in which users can compute everywhere. Despite such advances, computing resources are often scarce and changing, limiting a user�s ability to take advantage of the applications and devices, and requiring changes to the application runtime settings. Currently, the burden of managing the computing environment (devices, applications, and resources) falls on the user. A user must manually start applications and adjust their settings according to the available resources. Assigning such chores of configuration to the user has a number of disadvantages. First, it consumes user�s precious cognitive resources. Second, effectively managing the environment requires skills that a typical user might not have. Third, even with adequate low-level expertise, managing the environment optimally (or even adequately) can be difficult. Ideally, the computing needs of a user are seamlessly matched with the capabilities of the environment: devices, applications, and available resources. The user should enjoy the best possible application quality, without worrying about managing the low-level computing mechanisms. In this dissertation, we describe a novel approach that substantially automates the control of the configuration of the environment for a user�s task: finding and starting applications, configuring their runtime settings, and allocating possibly limited resources. Our approach simultaneously satisfies two important requirements: utility and practicality. Utility ensures that configuration decisions take into account user�s preferences for specific applications and quality of service. Practicality ensures that configuration has low runtime overhead in terms of the latency of configuration decisions and its usage of resources. First, we model configuration analytically as a problem of optimizing user�s utility based on three inputs: (1) user�s preferences, (2) application capability, and (3) resource availability. Formally, automating the control of the configuration requires solving an optimization problem, and then using the optimization solution to control the environment. Next, we design a software infrastructure that is based on the analytical model. The infrastructure implements efficient algorithms to solve the problem of configuration, eliminating the need for manual configuration. We validate our approach using experiments and simulation, demonstrating that the infrastructure satisfies the requirements of utility and practicality while substantially automating configuration.}, NOTE = {Technical Report CMU-CS-08-121} } @InProceedings{Sousa2008b, AUTHOR = {Sousa, Jo\~{a}o and Balan, Rajesh and Poladian, Vahe and Garlan, David and Satyanarayanan, Mahadev}, TITLE = {User Guidance of Resource-Adaptive Systems}, YEAR = {2008}, MONTH = {July}, BOOKTITLE = {ICSOFT'08 International Conference on Software and Data Technologies}, ADDRESS = {Porto, Portugal}, ABSTRACT = {This paper presents a framework for engineering resource-adaptive software systems targeted at small mobile devices. The proposed framework empowers users to control tradeoffs among a rich set of servicespecific aspects of quality of service. After motivating the problem, the paper proposes a model for capturing user preferences with respect to quality of service, and illustrates prototype user interfaces to elicit such models. The paper then describes the extensions and integration work made to accommodate the proposed framework on top of an existing software infrastructure for ubiquitous computing. The research question addressed here is the feasibility of coordinating resource allocation and adaptation policies in a way that end-users can understand and control in real time. The evaluation covered both systems and the usability perspectives, the latter by means of a user study. The contributions of this work are: first, a set of design guidelines for resource-adaptive systems, including APIs for integrating new applications; second, a concrete infrastructure that implements the guidelines. And third, a way to model quality of service tradeoffs based on utility theory, which our research indicates end-users with diverse backgrounds are able to leverage for guiding the adaptive behaviors towards activity-specific quality goals.}, KEYWORDS = {Aura, Resource Aware Computing} } @InBook{Prediction2008, AUTHOR = {Poladian, Vahe and Cheng, Shang-Wen and Garlan, David and Schmerl, Bradley}, TITLE = {Improving Architecture-Based Self-Adaption Through Resource Prediction}, YEAR = {2008}, BOOKTITLE = {Software Engineering for Self-Adaptive Systems}, VOLUME = {5525}, EDITOR = {Cheng, Betty H.C. and de Lemos, Rog\'{e}rio and Giese, Holger and Inverardi, Paola and Magee, Jeff}, SERIES = {Lecture Notes in Computer Science}, PUBLISHER = {LNCS}, CHAPTER = {15}, PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/LNCS-SEfSASChapter-2009-0222-web.pdf}, ABSTRACT = {An increasingly important concern for modern systems design is how best to incorporate self-adaptation into systems so as to improve their ability to dynamically respond to faults, resource variation, and changing user needs. One promising approach is to use architectural models as a basis for monitoring, problem detection, and repair selection. While this approach has been shown to yield positive results, current systems use a reactive approach: they respond to problems only when they occur. In this paper we argue that self-adaptation can be improved by adopting an anticipatory approach in which predictions are used to inform adaptation strategies. We show how such an approach can be incorporated into an architecture-based adaptation framework and demonstrate the benefits of the approach.}, KEYWORDS = {Rainbow, Resource prediction, Self-adaptation} } @InCollection{Sousa-SDT2009, AUTHOR = {Sousa, Jo\~{a}o and Balan, Rajesh Krishna and Poladian, Vahe and Garlan, David and Satyanarayanan, Mahadev}, TITLE = {A Software Infrastructure for User-Guided Quality-of-Service Tradeoffs}, YEAR = {2009}, BOOKTITLE = {Software and Data Technologies}, VOLUME = {47}, PAGES = {48-61}, EDITOR = {Cordeiro, J.}, SERIES = {CCIS}, PUBLISHER = {Springer}, PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/SIUGQoST.pdf}, ABSTRACT = {This paper presents a framework for engineering resource-adaptive software targeted at small mobile devices. Rather than building a solution from scratch, we extend and integrate existing work on software infrastructures for ubiquitous computing, and on resource-adaptive applications. This paper addresses two research questions: first, is it feasibility to coordinate resource allocation and adaptation policies among several applications in a way that is both effective and efficient. And second, can end-users understand and control such adaptive behaviors dynamically, depending on user-defined goals for each activity. The evaluation covered both the systems and the usability perspectives, the latter by means of a user study. The contributions of this work are: first, a set of design guidelines, including APIs for integrating new applications; second, a concrete infrastructure that implements the guidelines. And third, a way to model quality of service tradeoffs based on utility theory, which our research indicates end-users with diverse backgrounds are able to leverage for guiding the adaptive behaviors towards activity-specific quality goals.}, KEYWORDS = {Activity-oriented Computing, Self-awareness & Adaptation, Software Architecture, Ubiquitous Computing, Usability} }