Dynamic QoS-aware multimedia service configuration in ubiquitous computing environments
Ubiquitous computing promotes the proliferation of various stationary, embedded and mobile devices interconnected by heterogeneous networks. It leads to a highly dynamic distributed system with many devices and services coming and going frequently. Many emerging distributed multimedia applications are being deployed in such a computing environment. In order to make the experience for a user truly seamless and to provide soft performance guarantees, we must meet the following challenges: (1) users should be able to perform tasks continuously, despite changes of resources, devices and locations; (2) users should be able to efficiently utilize all accessible resources within runtime environments to receive the best possible Quality-of-Service (QoS). In this paper, we propose an integrated QoS-aware service configuration model to address the above problems. The configuration model includes two tiers: (1) service composition tier, which is responsible for choosing and composing current available service components appropriately and coordinating arbitrary interactions between them to achieve the user's objectives; and (2) service distribution tier which is responsible for dividing an application into several partitions and distributing them to different available devices appropriately. Our initial experimental results based on both prototype and simulations show the soundness of our model and algorithms.

title: On Composing Stream Applications in Peer-to-Peer Environments
abstract: Stream processing has become increasingly important as many emerging applications call for continuous real-time processing over data streams, such as voice-over-IP telephony, security surveillance, and sensor data analysis. In this paper, we propose a composable stream processing system for cooperative peer-to-peer environments. The system can dynamically select and compose stream processing elements located on different peers into user desired applications. We investigate multiple alternative approaches to composing stream applications: 1) global-state-based centralized versus local-state-based distributed algorithms for initially composing stream applications at setup phase. The centralized algorithm performs periodical global state maintenance while the distributed algorithm performs on-demand state collection. 2) Reactive versus proactive failure recovery schemes for maintaining composed stream applications during runtime. The reactive failure recovery algorithm dynamically recomposes a new stream application upon failures while the proactive approach maintains a number of backup compositions for failure recovery. We conduct both theoretical analysis and experimental evaluations to study the properties of different approaches. Our study illustrates the performance and overhead trade-offs among different design alternatives, which can provide important guidance for selecting proper algorithms to compose stream applications in cooperative peer-to-peer environments

title: DIVERGE: phylogeny-based analysis for functional-structural divergence of a protein family
abstract: DetectIng Variability in Evolutionary Rates among GEnes (DIVERGE) is a software system to study functional divergence of a protein family by detecting site-specific change in evolutionary rate using a multiple alignment of amino acid sequences for a given phylogenetic tree. The program first conducts a statistical test for site-specific rate shifts along the tree, and predicting candidate amino acid residues responsible for functional divergence based on posterior analysis. These results can then be mapped on the 3D protein structure if available.


AVAILABILITY
DIVERGE is available free of charge from http://xgu1.zool.iastate.edu/. Distribution packages for both Linux and Microsoft Windows operating systems are available, including manual and example files.

title: Multiple Genome Rearrangement by Reversals
abstract: In this paper, we discuss a multiple genome rearrangement problem: Given a collection of genomes represented by permutations, we generate the collection from some fixed genome, e.g., the identity permutation, in a minimum number of signed reversals. It is NP-hard, so efficient heuristics is important for finding its optimal solution. We at first discuss how to generate two and three genomes from a fixed genome by polynomial algorithms for some special cases. Then based on the polynomial algorithms, we obtain some approximation algorithms for generating two and three genomes in general, respectively. Finally, we apply these approximation algorithms to design a new approximation algorithm for generating more genomes. We also show by some experimental examples that the algorithms are efficient.

title: Evolutionary analysis of functional divergence in TGF- signaling pathway
abstract: TGF-β cytokines and their interacting receptors form an intricate signaling network and play important roles in cell differentiation and development. Members in gene families involved in this complicated pathway are usually conserved in sequence but distinct in temporal and tissue-specific expression. Starting from an evolutionary perspective, we have statistically tested the functional divergence in major pathway components, targeted the critical amino acid residues responsible for functional divergence. Our results show that altered functional constraints is a common pattern in the evolution of TGF-β pathway. Moreover, we have found the correlation between structural divergence and functional divergence in the extracellular ligand-binding domain of Type II receptors. This study helps understand the complex intrinsic mechanisms of signaling.

title: Algorithms for Multiple Genome Rearrangement by Signed Reversals
abstract: We discuss a multiple genome rearrangement problem by signed reversals: Given a collection of genomes, we generate them in the minimum number of signed reversals. It is NP-hard and equivalent to finding an optimal Steiner tree to connect the genomes by reversal paths. We design two algorithms to find the optimal Steiner nodes of the problem: Neighbor-perturbing algorithm and branch-and-bound algorithm. The first one is a polynomial running time approximation algorithm. It searches for the optimal Steiner nodes by perturbing initial Steiner nodes nearby their neighborhoods and improving them better and better until convergence. The second one is an exact exponential running time algorithm for a median problem. It finds the optimal Steiner node by checking all candidates that satisfy the necessary conditions for optimal Steiner nodes. We implement the algorithms into two programs respectively and show by experimental examples that they are more efficient than other similar ones, such as GRAPPA, BPAnalysis, and MGR, etc.

title: Enabling network-centric music performance in wide-area networks
abstract: NMP on the Internet is not only possible, its delay bounds can satisfy the tight requirements involved in human perception while generating high-end audio quality for musicians and listeners alike.