Tree-Based Concurrency Control in Distributed Groupware

We present a novel algorithm, called dARB, forsolving the concurrency control problem indistributed collaborative applications. Themain issue of concurrency control is resolvingthe conflicts resulting from simultaneousactions of multiple users. The algorithmreduces the need for manual conflict resolutionby using a distributed arbitration scheme. Themain advantages of our approach are thesimplicity of use and good responsiveness, asthere are no lock mechanisms. Our algorithmrequires the applications to use a tree as theinternal data structure. This makes itapplication independent and suitable forgeneral collaborative applications. The treerequirement is reasonable since many newapplications use XML (extensible MarkupLanguage) for data representation and exchange,and parsing XML documents results in treestructures. Example applications of thealgorithm, a group text editor and acollaborative 3D virtual environment calledcWorld, are implemented and evaluated in theDISCIPLE collaboration framework. We alsointroduce awareness widgets that users avoidgenerating the conflicting events and help inmanual conflict resolution.     

Performance analysis of the IEEE 802.11 DCF in the presence of the hidden stations

In this paper, we present an analytical model to evaluate the hidden station effect on the performance of the IEEE 802.11 Distributed Coordination Function (DCF) in both non-saturation and saturation condition. DCF is a random channel-access scheme based on Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) method and the exponential backoff procedure. DCF is widely used and can support both wireless network with an access point and ad hoc wireless network because of its random channel-access method. On the other hand, this method unavoidably suffers the hidden station effect that causes significant performance degradation. As shown in this paper, hidden stations occur frequently in real-world settings, and the performance impact on the 802.11 DCF is a significant concern, but it has not been adequately studied. We study this problem through a spatial–temporal analysis and a Markov chain model. Our model generalizes the existing work on the performance modeling of 802.11 DCF for both non-saturation and saturation conditions. The scenario of no hidden station can be considered as a special case in our model. The performance of our model is evaluated by comparison with ns-2 simulations.     

MAC-layer proactive mixing for network coding in multi-hop wireless networks

Network coding is a recent research topic in wireless networking. By combining multiple packets in a single broadcast transmission, network coding can greatly improve the capacity of multi-hop wireless networks. Packet mixing, when applied with traditional routing, can only be performed at the junctions of the paths determined by the routing module. This limits significantly the coding opportunities in the network. This paper presents a novel MAC-layer mixing method, named BEND, which proactively seizes opportunities for coding. Without relying on fixed forwarders, BEND allows each node in the neighborhood to be a potential coder and forwarder and coordinates their packet transmissions for higher coding gain. By taking advantage of redundant copies of a packet in the neighborhood coding repository, the number of mixing points, and thus the coding opportunities, can be significantly increased. This high coding gain is verified by our simulation studies.     

Piecewise Network Awareness Service for Wireless/Mobile Pervasive Computing

This paper presents a piecewise framework for network awareness service (NAS) for wireless/mobile pervasive computing. We investigate how piecewise consideration of wired and wireless elements of the framework architecture benefits service advertisement and discovery and network-awareness techniques. We also discuss scalability of the NAS framework with respect to platform computing capabilities. The framework is suitable for a wide range of computing devices, from powerful ones with multi-tasking operating systems (OS) to small ones with lightweight OS. Case studies applying the NAS framework to sensor monitoring in home networks and data streaming in pervasive multimedia computing are presented. The analytical results on the performance of the NAS framework in these case studies show that it has significant advantages over traditional network-awareness frameworks in terms of reducing wireless bandwidth consumption and saving battery energy of mobile devices.     

A Query Scope Agent for Flood Search Routing Protocols

Flood-search on-demand routing has received considerable interest for its application to mobile ad hoc networks. To alleviate the effects of flooding the network with control packets to discover a route, the concept of an expanding ring search (ERS) has been proposed elsewhere for reducing the packet transmission overhead of the route discovery process. Essentially, ERS consists of incrementally increasing the allowable hop radius of the flood search until a route to the target node is returned. However, ERS incurs additional latency to successfully complete the route discovery procedure. This paper presents a query scope agent (QSA) that assists in the selection of an appropriate ERS. The QSA accepts as input, from the user or network application, a maximum allowable value for route discovery delay. The QSA then estimates network parameter values to determine an ERS approach that satisfies the delay requirement while reducing expected packet transmission overhead. Simulation results show that it successfully achieves this objective. Further, the QSA incurs little communication and computation overhead, and operates in a distributed and asynchronous fashion.     

MAC Scheduling Using Channel State Diversity for High-Throughput IEEE 802.11 Mesh Networks

The head-of-line blocking problem impairs the throughput of the hotspot nodes in multihop wireless mesh networks. FIFO scheduling in the current IEEE 802.11 MAC suffers from this problem when the network is highly loaded. The problem may keep the sender in backoff stage up to 70 percent of the time, leading to significant throughput degradation. One solution is to increase the RTS success rate by extending the RTS frame to multicast RTS so that multiple receivers can be checked simultaneously. We present an adaptive learning process that constructs the receiver list based on the dynamic channel-state diversity of candidate receivers. Our variable-length channel-state-based scheduling scheme outperforms the basic MRTS by 20-60 percent.     

A system for medical consultation and education using multimodalhuman/machine communication

We propose a novel application of an interactive and distributed system in medical consultation and education. The presented application uses a multiuser, collaborative environment with multimodal human/machine communication in the dimensions of sight, sound, and touch. The experimental setup, consisting of two user stations, and the multimodal interfaces, including sight (eye tracking), sound (automatic speech), and touch (microbeam pen), were tested and evaluated. The system uses a collaborative workspace as a common visualization space. Users communicate with the application through a fusion agent by eye tracking, speech, and microbeam pen. The audio/video teleconferencing is also included to help the radiologists to communicate with each other simultaneously while they are working on the mammograms. The system has three software agents: a fusion agent, a conversational agent, and an analytic agent. The fusion agent interprets multimodal commands by integrating the multimodal inputs. The conversational agent answers the user's questions and detects human related or semantic errors and notifies the user about the results of the image analysis. The analytic agent enhances the digitized images using the wavelet denoising algorithm if requested by the user. To evaluate the system, we used it for medical consultation on mammograms. Results also show that the relevant information about the region of interest of the mammograms chosen by the users is extracted automatically and used to enhance the mammograms     

Compression guidelines for diagnostic telepathology

As the healthcare community has begun to rely increasingly upon digital technologies for acquisition, storage, and transmission of pictorial data, image compression has become an indispensable tool. The authors have investigated the feasibility of lossy compression in a well-defined task domain, the clinical assessment of digitized images of chromatic microscopic pathology specimens. The effect of compression was measured under two distinct perceptual criteria, just noticeable difference (JND) and largest tolerable distortion (LTD), differing in the involvement required from subjects, who were experts in pathology. For standard JPEG compressed images it was found that when the experiment is performed under the LTD criterion, a significantly larger compression ratio is reported as satisfactory. It is concluded that lossy compression holds promise for diagnostic telepathology     

Software Framework for Managing Heterogeneity in Mobile Collaborative Systems

Heterogeneity in mobile computing devices and application scenarios complicates the development of collaborative software systems. Heterogeneity includes disparate computing and communication capabilities, differences in users needs and interests, and semantic conflicts across different domains and representations. In this paper, we describe a software framework that supports mobile collaboration by managing several aspects of heterogeneity. Adopting graph as a common data structure for the application state representation enables us to develop a generic solution for handling the heterogeneities. The effect external forces, such as resource constraints and diverging user interests, can be quantified and controlled as relational and attribute heterogeneity of state graphs. When mapping the distributed replicas of the application state, the external forces inflict a loss of graph information, resulting in many-to-one correspondences of graph elements. A key requirement for meaningful collaboration is maintaining a consistent shared state across the collaborating sites. Our framework makes the best of maximizing the state consistency, while accommodating the external force constraints, primarily the efficient use of scarce system resources. Furthermore, we describe the mobility aspects of our framework, mainly its extension to peer-to-peer scenarios and situations of intermittent connectivity. We describe an implementation of our framework applied to the interoperation of shared graphics editors across multiple platforms, where users are able to share 2D and 3D virtual environments represented as XML documents. We also present performance results, namely resource efficiency and latency, which demonstrate its feasibility for mobile scenarios.