M. Rasit Eskicioglu

Communicating affect via flight path: exploring use of the laban effort system for designing affective locomotion paths

People and animals use various kinds of motion in a multitude of ways to communicate their ideas and affective state, such as their moods or emotions. Further, people attribute affect and personalities to movements of even non-life like entities based solely on the style of their motions, e.g., the locomotion style of a geometric shape (how it moves about) can be interpreted as being shy, aggressive, etc. We investigate how robots can leverage this locomotion-style communication channel for communication with people. Specifically, our work deals with designing stylistic flying-robot locomotion paths for communicating affective state. To author and unpack the parameters of affect-oriented flying-robot locomotion styles we employ the Laban Effort System, a standard method for interpreting human motion commonly used in the performing arts. This paper describes our adaption of the Laban Effort System to author motions for flying robots, and the results of a formal experiment that investigated how various Laban Effort System parameters influence peoples perception of the resulting robotic motions. We summarize with a set of guidelines for aiding designers in using the Laban Effort System to author flying robot motions to elicit desired affective responses.

Adaptive popularity-driven replica placement in hierarchical data grids

Data grids support access to widely distributed storage for large numbers of users accessing potentially many large files. Efficient access is hindered by the high latency of the Internet. To improve access time, replication at nearby sites may be used. Replication also provides high availability, decreased bandwidth use, enhanced fault tolerance, and improved scalability. Resource availability, network latency, and user requests in a grid environment may vary with time. Any replica placement strategy must be able to adapt to such dynamic behavior. In this paper, we describe a new dynamic replica placement algorithm, Popularity Based Replica Placement (PBRP), for hierarchical data grids which is guided by file “popularity”. Our goal is to place replicas close to clients to reduce data access time while still using network and storage resources efficiently. The effectiveness of PBRP depends on the selection of a threshold value related to file popularity. We also present Adaptive-PBRP (APBRP) that determines this threshold dynamically based on data request arrival rates. We evaluate both algorithms using simulation. Results for a range of data access patterns show that our algorithms can shorten job execution time significantly and reduce bandwidth consumption compared to other dynamic replication methods.

Popularity-Driven Dynamic Replica Placement in Hierarchical Data Grids

Data grids provide geographically distributed storage for large-scale data-intensive applications. Ensuring efficient access to such large and widely distributed datasets is hindered by high latencies. To speed up data access, data grid systems replicate data in multiple locations so a user can access the data from a nearby site. In addition to reducing data access time, replication also aims to use network and storage resources efficiently. While replication is a well-known technique, the problem of replica placement has not been widely studied for data grid environments. To obtain the best possible gains from replication, strategic placement of the replicas is critical. In a grid environment resource availability, network latency, and userspsila requests can vary. To address these issues a placement strategy is needed that adapts to dynamic behavior. This paper proposes a new dynamic replica placement algorithm for hierarchical data grids based on file ldquopopularityrdquo. Our goal is to place replicas close to the clients to reduce access time while using the network and storage efficiently thereby effectively balancing storage cost and access latency. We evaluate our algorithm using OptorSim which shows that our approach outperforms other techniques in terms of access time and bandwidth used.

Distributed Popularity Based Replica Placement in Data Grid Environments

Data grids support distributed data-intensive applications that need to access massive datasets stored around the world. Ensuring efficient access to such datasets is hindered by the high latencies of wide-area networks. To speed up access, files can be replicated so a user can access a nearby replica. Replication also provides improved availability, decreased bandwidth use, increased fault tolerance, and improved scalability. Since a grid environment is dynamic, resource availability, network latency, and user requests may change. To address these issues a dynamic replica placement strategy that adapts to changing behaviour is needed. In this paper, we introduce a highly distributed replica placement algorithm for hierarchical data grids. Our algorithm exploits data access histories to identify popular files and determines optimal replication locations to improve access performance by minimizing replication overhead (access and update) assuming a given traffic pattern. The problem is formulated using dynamic programming. We evaluate our algorithm using the OptorSim simulator and find that it offers shorter execution time and reduced bandwidth consumption compared to other dynamic replica placement methods.

Distributed Placement of Replicas in Hierarchical Data Grids with User and System QoS Constraints

Data grids support distributed data-intensive applications that need to access massive datasets stored around the world. Ensuring efficient access to such datasets is hindered by the high latencies of wide-area networks. To speed up access, files can be replicated so a user can access a nearby replica. Much of the work on the replica placement problem in data grids has focused on average system performance and ignored quality assurance issues. In the existing work that considers QoS, a simplified replication model is often assumed, therefore, resulting solutions may not be applicable to real systems. In this paper, we introduce a more realistic model for replica placement in hierarchical Data Grids which determines the positions of a minimum number of replicas expected to satisfy certain quality requirements both from user and system perspectives. Our placement algorithm is based on a highly distributed and decentralized technique that exploits the data access history for popular data files and computes replica locations by minimizing overall replication cost (read and update) while maximizing QoS satisfaction for a given traffic pattern. The problem is formulated using dynamic programming. We assess our algorithm using OptorSim. Simulation results demonstrate the effectiveness of our replica placement technique considering various factors such as storage and workload constraints of replica servers, link capacity constraints, user QoS requirements, etc.

Allocating replicas in large-scale data grids using a QoS-aware distributed technique with workload constraints

An important technique to speed access in data grids is replication, which provides nearby replicas. In a data grid environment, resource availability, network latency and user request patterns may change. In this paper, we introduce a new distributed replica placement algorithm for hierarchical data grids that determines the positions of a minimum number of replicas expected to satisfy certain quality requirements. Our placement algorithm computes replica locations by minimising overall replication cost (read and update) while maximising Quality of Service (QoS) satisfaction for a given traffic pattern. Our algorithm also assumes that the workload capacity of each replica server is bounded. The problem is formulated using dynamic programming. We assess our algorithm using OptorSim. A comparison of our algorithm to its QoS-unconstrained counterpart and to two other existing algorithms (Greedy Add and Greedy Remove) shows that our algorithm can shorten job execution time significantly while requiring only moderate network bandwidth.

Visually Augmented Interfaces for Co-located Mobile Collaboration

We explore the difficulties involved with tightly coupled collaborative work on mobile devices. Small screens and separate workspaces hinder close interaction, even for co-located users. We begin our inquiry with a set of user focus groups to determine collaborative usage patterns, determining that shared workspaces present an opportunity to overcome the barriers to collaboration. The case for integrating awareness information into such distributed systems has been well established. We present two conceptual designs using visualization cues to present user awareness information, the first for co-located mobile devices, and the second using a mobile projector.

Gaze-contingent interactive visualization of high-dynamic-range imagery

There exist many types of visual imagery that span a dynamic range that exceeds what typical displays are able to capture. This implies that some information is lost, and requires schemes for compressing the dynamic range so that images are amenable to viewing on standard display technology. In certain application domains, specialized displays that cover a wider dynamic range are employed including for the display of medical images for diagnostic purposes. In this paper, we present a means of locally adapting the dynamic range of the display as a function of gaze location to allow for visualization of high dynamic range media on standard displays. This allows for viewing visual media over a dynamic range that exceeds limitations of any display, and presents additional value for certain application domains. The implemented system also allows for control over dynamic range globally based on hand gestures.

Developing guidelines for in-the-field control of a team of robots

In this work we explore the development of guidelines for creating “in-the-field” interfaces for enabling a single user to remotely control multiple robots. The problem of controlling a remote team of robots is complex, requiring a user to monitor and interpret robotic state and sensor information in real time, and to simultaneously communicate direction commands to the robots. The result is that a robot controller is often seated at a console; for many relevant applications such as search and rescue or firefighting this removes the user from the field of action, rendering them unable to directly participate in a task at hand. Therefore, one challenge in HRI is to develop efficient interfaces that will enable a user to effectively control and monitor a team of robots in the field. In our project we explore various interface designs in terms of supporting this goal, taking the approach of involving a panel of professionals in the design process to direct exploration and development.

Guidelines for Designing Awareness-Augmented Mobile DUIs

Colocated groups using mobile devices do not share all of the benefits of face-to-face collaborators. Close interaction requires application support for awareness features, allowing participants to establish common ground. Following an overview of research on awareness and grounding, the results of an informal user study are presented, which demonstrate how current systems can deter users from engaging in close collaboration. Literature on awareness provides hope for improving this situation, but a naive transfer to mobile distributed user interfaces will not necessarily succeed. From prior art, a concise list of guidelines has been compiled to assist designers in providing awareness information to users of shared mobile workspaces. These guidelines can also serve as heuristics for the evaluation of future systems. An example is provided to demonstrate how these guidelines can be applied to the development of features for providing awareness of current location and browsing history to colocated users of mobile distributed user interfaces.