5754031
Group management for mobile Ad Hoc networks: design, implementation and experiment
Mobile ad hoc networks (MANET) offer a convenient basis toward realization of pervasive computing, due to its ease of deployment and inherent support for anytime, anywhere network access for mobile users. However, the development of applications over such networks is faced by the challenge of network dynamics attributed to node mobility and the scalability issue. Group management poses as a promising paradigm to ease the development of distributed applications for dynamic, mobile networks. Specifically, group management makes transparent the failures due to node mobility and assembles mobile nodes to meet target functional and non-functional properties. Various network-level grouping schemes over MANET have been investigated over the last couple of years. In this paper, we introduce the design and implementation of a generic group service for MANET, defined with respect to the various attributes of relevance. Generic group management is further demonstrated with its support of scalable service discovery in MANET.
6152126
QoS-aware dynamic service composition in ambient intelligence environments
Due to the large success of wireless networks and handheld devices, the ambient intelligence (AmI) paradigm is becoming a reality. One of the most challenging objectives to achieve in AmI environments is to enable a user to perform a task by composing on the fly networked services available at a specific time and place. Towards this goal, we propose a solution based on semantic Web services, and we show how service capabilities described as conversations can be integrated to perform a user task that is also described as a conversation, further meeting the QoS requirements of the user task. Experimental results show that the runtime overhead of our algorithm is reasonable, and further, that QoS-awareness improves its performance.
15518330
Enhanced Reputation Mechanism for Mobile Ad Hoc Networks
Interactions between entities unknown to each other are inevitable in the ambient intelligence vision of service access anytime, anywhere. Trust management through a reputation mechanism to facilitate such interactions is recognized as a vital part of mobile ad hoc networks, which features lack of infrastructure, autonomy, mobility and resource scarcity of composing light-weight terminals. However, the design of a reputation mechanism is faced by challenges of how to enforce reputation information sharing and honest recommendation elicitation. In this paper, we present a reputation model, which incorporates two essential dimensions, time and context, along with mechanisms supporting reputation formation, evolution and propagation. By introducing the notion of recommendation reputation, our reputation mechanism shows effectiveness in distinguishing truth-telling and lying agents, obtaining true reputation of an agent, and ensuring reliability against attacks of defame and collusion.
407371
Service Allocation in Selfish Mobile Ad Hoc Networks Using Vickrey Auction
Incentive scheme for stimulating service provision in Mobile Ad hoc NETworks (MANET) has been under intensive investigation due to its significance to the operation of MANET This paper applies distributed algorithmic mechanism design and utilizes Vickrey auction for service allocation in mobile ad hoc networks We show that our method stimulates service provision and achieves desired system-wide service allocation in spite of each agent's selfish behavior, while introducing challenges from the inherent shortcomings of Vickrey auction and characteristics of MANET We discuss the challenges, the existing solutions for wireline networks and propose a system model for service allocation in MANET.
14806639
A unified framework for resource discovery and QoS-aware provider selection in ad hoc networks
With the rising popularity of network-based applications and the potential use of mobile ad hoc networks in civilian life, an efficient resource discovery service is needed in such networks for quickly locating resource providers. In addition, to improve user experience, QoS awareness is also crucial. In this paper, we identify the challenges when basic resource discovery techniques for the Internet are used in mobile ad hoc networks. We then propose a framework that provides a unified solution to the discovery of resources and QoS-aware selection of resource providers. The key entities of this framework are a set of self-organized discovery agents. These agents manage the directory information of resources using hash indexing. They also dynamically partition the network into domains and collect intra- and inter-domain QoS information to select appropriate providers. Simulation results show that our framework improves the QoS delivered to the clients, while the cost and response time are kept at a low level.
33401134
Distributed Group Management for Track Initiation and Maintenance in Target Localization Applications
The tradeoff between performance and scalability is a fundamental issue in distributed sensor networks. In this paper, we propose a novel scheme to efficiently organize and utilize network resources for target localization. Motivated by the essential role of geographic proximity in sensing, sensors are organized into geographically local collaborative groups. In a target tracking context, we present a dynamic group management method to initiate and maintain multiple tracks in a distributed manner. Collaborative groups are formed, each responsible for tracking a single target. The sensor nodes within a group coordinate their behavior using geographically-limited message passing. Mechanisms such as these for managing local collaborations are essential building blocks for scalable sensor network applications.
15792710
Markers improve clustering of CGH data
MOTIVATION
We consider the problem of clustering a population of Comparative Genomic Hybridization (CGH) data samples using similarity based clustering methods. A key requirement for clustering is to avoid using the noisy aberrations in the CGH samples.


RESULTS
We develop a dynamic programming algorithm to identify a small set of important genomic intervals called markers. The advantage of using these markers is that the potentially noisy genomic intervals are excluded during the clustering process. We also develop two clustering strategies using these markers. The first one, prototype-based approach, maximizes the support for the markers. The second one, similarity-based approach, develops a new similarity measure called RSim and refines clusters with the aim of maximizing the RSim measure between the samples in the same cluster. Our results demonstrate that the markers we found represent the aberration patterns of cancer types well and they improve the quality of clustering significantly.


AVAILABILITY
All software developed in this paper and all the datasets used are available from the authors upon request.
15520988
Multiscale Modeling and Simulation of Worm Effects on the Internet Routing Infrastructure
An unexpected consequence of recent worm attacks on the Internet was that the routing infrastructure showed evidence of increased BGP announcement churn. As worm propagation dynamics are a function of the topology of a very large-scale network, a faithful simulation model must capture salient features at a variety of resolution scales. This paper describes our efforts to model worm propagation and its affect on routers and application traffic. Using our implementations of the Scalable Simulation Framework (SSF) API, we model worm propagation, its affect on the routing infrastructure and its affect on application traffic using multiscale traffic models.
2696332
A boosting approach for motif modeling using ChIP-chip data
MOTIVATION
Building an accurate binding model for a transcription factor (TF) is essential to differentiate its true binding targets from those spurious ones. This is an important step toward understanding gene regulation.


RESULTS
This paper describes a boosting approach to modeling TF-DNA binding. Different from the widely used weight matrix model, which predicts TF-DNA binding based on a linear combination of position-specific contributions, our approach builds a TF binding classifier by combining a set of weight matrix based classifiers, thus yielding a non-linear binding decision rule. The proposed approach was applied to the ChIP-chip data of Saccharomyces cerevisiae. When compared with the weight matrix method, our new approach showed significant improvements on the specificity in a majority of cases.