Dongman Lee

A virtual cloud computing provider for mobile devices

A mobile device like a smart phone is becoming one of main information processing devices for users these days. Using it, a user not only receives and makes calls, but also performs information tasks. However, a mobile device is still resource constrained, and some applications, especially work related ones, usually demand more resources than a mobile device can afford. To alleviate this, a mobile device should get resources from an external source. One of such sources is cloud computing platforms. Nevertheless an access to these platforms is not always guaranteed to be available and/or is too expensive to access them. We envision a way to overcome this issue by creating a virtual cloud computing platform using mobile phones. We argue that due to the pervasiveness of mobile phones and the enhancement in their capabilities this idea is feasible. We show prior evaluation results to support our concept and discuss future developments.

ATLAS: a scalable network framework for distributed virtual environments

A distributed virtual environment (DVE) is a software system that allows users on a network to interact with each other by sharing a common view of their states. As users are geographically distributed over large networks like the Internet and the number of users increases, scalability is a key aspect to consider for real-time interaction. Various solutions have been proposed to improve the scalability in DVE systems but they are either focused on only specific aspects or customized to a target application. In this paper, we classify the approaches for improving scalability of DVE into four categories: communication architecture, interest management, concurrency control, and data replication. We then propose a scalable network framework for DVEs, ATLAS. Incorporated with our various scalable schemes, ATLAS meets the scalability of a system as a whole. By providing system developers with a set of APIs as a network infrastructure, ATLAS intends to support various applications The integration experiences of ATLAS with several virtual reality systems ensures the versatility of the proposed solution.

A dynamic context-conflict management scheme for group-aware ubiquitous computing environments

In this paper, we propose a context-conflict management scheme for group-aware ubiquitous computing environments that allows context-aware applications to serve multiple users without distracting and sacrificing each other. The proposed scheme can detect semantic conflicts without explicit descriptions of the conflicts between different applications. Conflicts are resolved by a dynamically generated adaptation policy based on the weight value of user preference on each service. Individual context-aware applications can be reused without modification since middleware components for the context-conflict management take charge of detecting and resolving conflicts. Thus, the complicated context-conflict situation becomes more transparent to application programmers.

A scalable dynamic load distribution scheme for multi-server distributed virtual environment systems with highly-skewed user distribution

This paper proposes and evaluates a scalable dynamic load distribution scheme for multi-server distributed virtual environment systems, where users are highly skewed rather than uniformly distributed over a virtual environment. In the proposed scheme, an overloaded server initiating load distribution selects a set of servers to be involved in load distribution by dynamically adapting to the workload status of other servers, unlike the existing approaches. Upon completion of server selection, the intiating server repartitions the regions dedicated to the involved servers using a graph partitioning algorithm so that all the involved servers have the roughly equal workload. The involved servers then migrate their workloads with each other in a peer-to-peer manner according to the result of repartitioning. We present and analyze the simulation results that compare the performance of the proposed scheme with that of the existing schemes.

An Adaptive Hello Messaging Scheme for Neighbor Discovery in On-Demand MANET Routing Protocols

In mobile ad-hoc networks, local link connectivity information is extremely important for route establishment and maintenance. Periodic Hello messaging is a widely-used scheme to obtain local link connectivity information. However, unnecessary Hello messaging can drain batteries while mobile devices are not in use. This paper proposes an adaptive Hello messaging scheme to suppress unnecessary Hello messages without reduced detectability of broken links. Simulation results show that the proposed scheme reduces energy consumption and network overhead without any explicit difference in throughput.

ATLAS: A Scalable Network Framework for Distributed Virtual Environments

A distributed virtual environment (DVE) is a software system that allows users in a network to interact with each other by sharing a common view of their states. As users are geographically distributed over large networks like the internet and the number of users increases, scalability is a key aspect to consider for real-time interaction. Various solutions have been proposed to improve the scalability in DVE systems but they are either focused on only specific aspects or customized to a target application. In this paper, we classify the approaches for improving scalability of DVE into five categories: communication architecture, interest management, concurrency control, data replication, and load distribution. We then propose a scalable network framework for DVEs, ATLAS. Incorporated with our various scalable schemes, ATLAS meets the scalability of a system as a whole. The integration experiences of ATLAS with several virtual reality systems ensure the versatility of the proposed solution.

An Adaptable Application Offloading Scheme Based on Application Behavior

The advancement of personal devices such as PDAs and mobile phones become ubiquitous and their increasing computing capabilities allow users to perform tasks that used to be performed on workstations. However, we cannot expect to run all tasks on top of personal devices because of the limited resources. Application offloading allow us to overcome this issue by porting part of an application to a nearby server or workstation with more capabilities. In this paper we present a new application offloading mechanism to perform offloading based on the execution history of applications, and adaptable to the current conditions of the environment and device. We record the consumed resources and the state of the device and surrogates, and we use that information to perform an adaptable offloading. We show that our scheme can prevent the overhead of profiling and also reduce the execution time of an application against pure runtime offloading.

Scalable data management using user-based caching and prefetching in distributed virtual environments

For supporting real-time interaction in distributed virtual environments (DVEs), it is common to replicate virtual world data at clients from the server. For efficient replication, two schemes are used together in general - prioritized transfer of objects and a caching and prefetching technique. Existing caching and prefetching approaches for DVEs exploit spatial relationship based on distances between a user and objects. However, spatial relationship fails to determine which types of objects are more important to an individual user, not reflecting users interests. We propose a scalable data management scheme using user-based caching and prefetching exploiting the objects access priority generated from spatial distance and individual users interest in objects in DVEs. We also further improve the cache hit rate by incorporating users navigation behavior into the spatial relationship between a user and the objects in the cache. By combining the interest score and popularity score of an object with the spatial relationship, we improve the performance of caching and prefetching since the interaction locality between the user and objects are reflected in addition to spatial locality. The simulation results show that the proposed scheme outperforms the hit rate of existing caching and prefetching by 10% on average when the cache size is set to basic cache size, the size of expected number of objects included in the users viewing range.

MiRE4OWL: Mobile Rule Engine for OWL

Mobile user devices, such as smart phones have become the most popular high-end mobile devices far beyond just cellular communication devices. They will continue evolving toward being palm-top computers with the rapid development of wireless communications and platform technologies. This paper introduces our development of a semantic reasoner called MiRE4OWL to be installed onto the resource-limited mobile user devices to accommodate context-aware ubiquitous computing services. It is a data-log and rule-based inference engine which performs semantic reasoning operations over the application semantics represented in OWL-DL. The mobile rule engine that underlies MiRE4OWL achieves light-weight design to meet the resource constraints of the mobile devices and yet achieves better expressiveness than existing engines. The performance evaluation showed that the intended functionality and resource efficiency have been fulfilled.

Proactive Web caching with cumulative prefetching for large multimedia data

Abstract Web proxy caching provides an effective way to reduce access latency and bandwidth consumption, and thus improve performance of the World Wide Web. Due to the simplicity of incorporating various types of data into the Web, non-negligible access for large multimedia data is observed. Large multimedia data transfer, requiring a long-lived connection with consecutive data transmissions, often fails over wide area networks. Repetitive attempts to fetch large objects through proxy caches would waste network resources with no success guaranteed. In this paper, we propose on-demand cumulative prefetching to enhance proxy caches for better data availability of large multimedia files. Our analysis shows that on-demand cumulative prefetching can be performed within a few trials with minimal additional bandwidth requirement. The experimental results demonstrate that the proposed scheme substantially reduces error rate and increases byte hit rate for large multimedia data.