Wireless ad-hoc sensor networks have emerged as an interesting and important research area in the last few years. The applications envisioned for such networks require collaborative execution of a distributed task amongst a large set of sensor nodes. This is realized by exchanging messages

In this paper we show that application-aware adaptation, a collaborative partnership between the operating system and applications, offers the most general and effective approach to mobile information access. We describe the design of Odyssey, a prototype implementing this approach, and show how

One of the major applications of data mining is in helping companies determine which potential customers to market to. If the expected pro t from a customer is greater than the cost of marketing to her, the marketing action for that customer is executed. So far, work in this area has considered

Abstract—In this paper, we investigate the scheduling policy for collaborative execution in mobile cloud computing. A mobile application is represented by a sequence of fine-grained tasks formulating a linear topology, and each of them is executed either on the mobile device or offloaded onto

Abstract—Mobile devices are evolving into powerful systems due to recent advances in their communication, storage and computation technologies. They are poised to play a key role in providing a rich collaborative computing platform for vari-ous applications. This paper proposes “Transient Clouds

management. In this paper, the collaborative execution mechanisms have been developed for the TCPNenhanced process-view approach based interenterprises workflow. The state dependencies mechanism is proposed to facilitate the collaborative execution between TCPN workflow models and process-view workflow

This work presents Move Value Estimation for Robot Teams (MVERT), an architecture specifically designed for selecting low-level actions for multi-agent teams. The design goal for MVERT is to produce reasonable performance that takes advantage of a heterogeneous team while maintaining computational efficiency. MVERT is fully distributed – each agent selects actions based on its knowledge and knowledge provided it by teammates. Each robot approximates the expected next-step teammate contributions and, given these predictions, each robot can select its action to maximize the team’s progress. MVERT represents progress with mathematical value functions that map state and robot task performance models to a numerical value representing mission utility. Many action selection approaches (optimal trajectory planning, for example) in large state-spaces may be computationally prohibitive, particularly for online mission replanning. However, taking advantage of a team’s multi-agent nature to provide efficiency requires consideration of teammate contributions. Thus, in selecting an action with MVERT, each robot approximates the next-step contributions of teammates by applying their sensing models, task capabilities, and current poses in the value functions. The robot then evaluates its candidate actions by applying the value functions and its own sensor models. The action

In this paper, we describe the influence of physical proximity on the development of collaborative relationships between scientific researchers and on the execution of their work. Our evidence is drawn from our own studies of scientific collaborators, as well as from observations of research

of awareness for the purpose of aiding groupware design, focusing on one kind of group awareness called workspace awareness. We focus on how small groups perform generation and execution tasks in medium-sized shared workspaces – tasks where group members frequently shift between individual and shared

in collaboration with