In this paper, we propose cyber foraging: a mechanism to augment the computational and storage capabilities of mobile devices. Cyber foraging uses opportunistically discovered servers in the environment to improve the performance of interactive applications and distributed file systems on mobile clients. We show how the performance of distributed file systems can be improved by staging data at these servers even though the servers are not trusted. We also show how the performance of interactive applications can be improved via remote execution. Finally, we present VERSUDS: a virtual interface to heteregeneous service discovery protocols that can be used to discover these servers.
Pervasive computing environments such as smart spaces require a mechanism to easily integrate, manage and use numerous, heterogeneous sensors and actuators into the system. However, available sensor network platforms are inadequate for this task. The goals are requirements for a smart space are very different from the typical sensor network application. Specifically, we found that the manual integration of devices must be replaced by a scalable, plug-and-play mechanism. The space should be assembled programmatically by software developers, not hardwired by engineers and system integrators. This allows for cost-effective development, enables extensibility, and simplifies change management. We found that in a smart space, computation and power are readily available and connectivity is stable and rarely ad-hoc. Our deployment of a smart house (an assistive environment for seniors) guided us to designing Atlas, a new, commercially available service-oriented sensor and actuator platform that enables self-integrative, programmable pervasive spaces. We present the design and implementation of the Atlas hardware and middleware components, its salient characteristics, and several case studies of projects using Atlas.
In social networks, nodes usually represent people and edges represent the relationship and connections between people. Ranking how important the nodes are with respect to some query nodes has a lot of applications in social networks. More often, people are interested in finding the Top-k most "relatively important" nodes with respect to some query nodes. A major challenge in this area of research is to define a function for measuring the "relative importance" between two nodes. In this paper, we present a measure called path probability to represent the connection strength of a between the ending node and the starting node. We proposed a measure of relative importance by using the sum of the path probabilities of all the "important" paths between a node with respect to a query node. Another challenge of computing the relative importance is the scalability issue. Most popular solutions are random walk based algorithms which involve matrix multiplication, and therefore are computationally too expensive for large graphs with millions of nodes. In this paper, by defining the path probability and introducing a small threshold value to determine whether a path is important or significant, we are able to ignore a lot of unimportant nodes so as to be able to efficiently identify the Top-k most relatively important nodes to the query nodes. Experiments are conducted over several synthetic and real graphs. The results are encouraging, and show a strong correlation between our approach and the well known random walk with restart algorithm.
While specialized knowledge and skills are the hallmark of modern society, the size and complexity of contemporary problems often require cooperative effort to analyze and solve. Therefore, experiences with skills, methodologies, and tools for effective interdisciplinary collaboration and structured problem solving are vital for preparing students for future academic and professional success. Meanwhile, computational systems have permeated much of modern professional and personal life, making computational thinking an essential skill for members of modern society. However, formal training in these techniques is primarily limited to students within computer science, mathematics, management of information systems, and engineering. At Iowa State University, we have designed and offered an experimental course to develop undergraduate students' abilities for interdisciplinary teamwork and to disseminate computational thinking skills to a broader range of students. This novel course was jointly designed and instructed by faculty from the Computer Science Department, Gerontology Program, and Graphic Design Program to incorporate diverse faculty expertise and pedagogical approaches. Students were required to interview real users to identify real-life problems, gather requirements, and assess candidate solutions, which necessitated communication both within the group and with technologically-disinclined users. In-class presentations and wiki-based project websites provided regular practice at disseminating domain expertise to larger interdisciplinary audiences. Workshops, group-based mentoring, peer learning, and guided discovery allowed non-CS majors to learn much more about computer programs and tools, and grading criteria held students individually accountable within their disciplines but also emphasized group collaboration.
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