zani Deb

Towards Autonomic Distribution of Existing Object Oriented Programs

By harnessing computational power of distributed heterogeneous resources, it is possible to build a large scale integrated system so that a centralized program is partitioned and distributed to those resources in a way that results in both efficient execution of the program and maximized resource utilization. However, building such a system is a staggering challenge because of the associated complexities and required user intervention. This paper proposes an autonomic distributed architecture that statically analyzes the existing Java application, partitions it to self-managed components that handles the complexities related to distribution and coordination without user involvement. An efficient static analysis mechanism is implemented that identifies run time program instances and their dependencies in terms of a graph. It is observed that such a view of the program is essential towards self optimization and self management

Adding Self-Healing Capabilities into Legacy Object Oriented Application

Adding self healing functionalities into legacy applications without user involvement is immensely useful for users and programmers of such systems. This paper presents a technique of injecting user code with self-healing primitives by statically analyzing the legacy object oriented code and instrumenting it to become a self-manageable and self-healing component. Our experiments show that it is worthwhile to instrument legacy code to provide such autonomic behavior

An Evidence Based Learning and Teaching Strategy for Computer Science Classrooms and Its Extension into a Mobile Classroom Response System

Evidence-based instructional practices were incorporated in class, which gave immediate indication on students problem solving skills and class participation information. This pedagogy showed positive results and broader acceptance by students in several semesters of intervention. Significant usage of mobile devices during class motivates the extension of this pedagogical approach of asynchronous problem solving using mobile devices. We believe that use of such devices in the classroom for solving interactive problems will enhance students abilities to solve problems by using their preferred interaction mode. This paper presents the results of the evidence based pedagogy and development of a mobile classroom response system that extends this pedagogy to help student solve interactive problems in their mobile devices to improve their class engagement and problem solving skills.

Using Interactive Exercise in Mobile Devices to Support Evidence-based Teaching and Learning

To improve students class experience, the use of mobile devices has been steadily increasing. However, such use of mobile learning environments in the class is mostly static in nature through content delivery or multiple choice and true/false quiz taking. In CS courses, we need learning environments where students can interact with the problem in a hands-on-approach and instructor can assess their learning skills in real-time with problems having different degree of difficulty. To facilitate such interactive problem solving and real-time assessment using mobile devices, a comprehensive backend system is necessary. This paper presents one such system, named Mobile Response System (MRS) software, associated interactive problem-solving activities, and lessons learned by using it in the CS classrooms. MRS provides instructor with the opportunity of evidence-based teaching by allowing students to perform interactive exercises in their mobile devices with different learning outcomes and by getting an instant feedback on their performance and mental models. MRS is easy-to-use, extensible and can render interactive exercises developed by third-party developers. The student performance data shows its effectiveness in increasing student understanding of difficult concepts and the overall perception of using the software was very positive.

Achieving self-managed deployment in a distributed environment

This paper proposes algorithms and mechanisms for achieving self-optimized deployment of computationally intensive scientific and engineering applications in highly dynamic and large-scale distributed environment. The primary focus is on the modeling of the application and underlying architecture into a common abstraction and on the incorporations of autonomic features to those abstractions to achieve self-optimized deployment. To represent the underlying heterogeneous infrastructure, a hierarchical (tree) model of distributed resources has been adopted that organizes distributed nodes in a utility aware way. To accomplish the self-optimization, a utility-function has been formulated that governs both the initial deployment of an application and its dynamic reconfiguration. In our approach, the deployment decisions are made solely based on locally available information and without costly global communication or synchronization. The self-management is therefore decentralized to provide better adaptability, scalability and robustness.

On Utility Driven Deployment in a Distributed Environment

By harnessing the computational power of distributed heterogeneous resources, it is possible to build a large scale integrated system so that a centralized program is partitioned and distributed across those resources in a way that maximizes the systems overall utility. However, building such a system is a staggering challenge because of the associated complexities. This paper proposes a self-managing distributed system ADE, that incorporates autonomic entities to handle the complexities associated with distribution, coordination and efficient execution of program components. The proposed approach models a centralized application in terms of an application graph consisting application components and then deploys the application components across the underlying hierarchically organized distributed resources so that all constraints and requirements are satisfied and the systems overall utility is maximized. Then, based on the observations obtained by the monitoring of the system resources, ADE redeploys the application graph to maintain maximized system utilization in spite of the dynamism and uncertainty involved in the system

Developing interactive classroom exercises for use with mobile devices to enhance class engagement and problem-solving skills

A recent Pew research center study of mobile device usage revealed that, African American and Latinos are the most active users of the Internet from mobile devices. The study also revealed that minority cell phone owners take advantage of a much greater range of their phones features compared with people of other ethnicities. At Winston Salem State University (WSSU), it is common for students to multitask and use their mobile devices while in class for studying, or performing other activities. This paper reports our ongoing experiences running a National Science Foundation (NSF)-sponsored targeted Infusion Project (TIP) in Computer Science Department that aims to leverage this situation by developing a mobile classroom response system (MRS) to allow students solve interactive problems in their mobile devices in order to improve their class engagement and problem solving skills. By allowing them to solve problems in their preferred devices, the project expects to create a friendly learning environment where the students want to retain, be active and skillful.

Distributed Document Clustering Using Word-clusters

Document clustering has become an increasingly important task in analyzing huge numbers of documents distributed among various sites. The challenging aspect is to analyze this enormous number of extremely high dimensional distributed documents and to organize them in such a way that results in better search and knowledge extraction without introducing much extra cost and complexity. This paper presents a distributed document clustering approach called distributed information bottleneck (DIB). DIB adopts a two stage agglomerative information bottleneck (aIB) algorithm to generate local clusters. At the first stage, the high-dimensional document vector is significantly reduced by finding word-clusters. These word-clusters are then used to obtain document-clusters in the second stage. DIB then extracts compact but informative local models from these document-clusters and transfers them to a central site. At the global site, the local models, that are likely to describe the same document set, are first combined. The resultant local models are then clustered by using the aIB algorithm to produce a hierarchical organization of all distributed documents. Our experimental results demonstrate the robustness, efficiency and effectiveness of DIB approach to cluster distributed documents.

Use of mobile application to improve active learning and student participation in the computer science classroom (abstract only)

This poster addresses a significant learning barrier experienced at many CS departments, specially at predominantly minority institutions, which is the problem of students? inability to keep engaged and interested in classroom. In this research, we investigate the applicability of using mobile devices in the classroom and incorporation of interactive problem solving using those devices to increase class engagement and active learning for students. By allowing the students to solve problems in their preferred devices, the research expects to create a friendly learning environment where the students want to retain, be active and skillful. The poster will present the design aspects of Mobile Response System (MRS) software that will be utilized to communicate, collaborate and evaluate interactive problems using mobile devices. The poster will also showcase several interactive problem-solving activities utilizing mobile devices and MRS software, which have been developed and are being adopted in CS and IT courses at Winston-Salem State University (WSSU). It is expected that this research will invigorate interest in Computer Science among minority and underrepresented students through exposure to the technology-rich learning environment. By enhancing student learning and problem solving abilities, it is also expected that this research work will improve the quality and quantity of underrepresented minority students in STEM workforce or graduate study. The successful execution of this project will advance research and the knowledge of mobile device usage in CS classrooms and more importantly the way it impact teaching strategy and student learning at WSSU and other institutions.

Self-healing by means of runtime execution profiling

A self-healing application brings itself into a stable state after a failure put the software into an unstable state. For such self-healing software application, finding fix for a previously unseen fault is a grand challenge. Asking the user to provide fixes for every fault is bad for productivity, especially when the users are non-savvy in technical aspect of computing. If failure scenarios come into existence, the user wants the runtime environment to handle those situations autonomically. This paper presents a new technique of finding self-healing actions by matching a fault scenario to already established fault models. By profiling and capturing runtime parameters and execution pathways, stable execution models are established and later are used to match with an unstable execution scenario. Experimentation and results are presented that showed that even with additional overheads; this technique can prove beneficial for autonomically healing faults and reliving system administrators from mundane troubleshooting situations.