The case for a multi-hop wireless local area network
We propose a multi-hop wireless LAN architecture and demonstrate its benefits to wireless clients. For this architecture, we define implementation paths that allow interoperation with existing wireless LANs which can lead to an incremental deployment of this system. We quantify the performance benefits of the proposed schemes through measurements in realistic wireless LAN environments. We also examine the performance of such multi-hop wireless LANs through detailed simulation studies. Our results show that these multi-hop extensions can significantly improve the wireless access experience (in terms of data throughput, latency, etc.) for clients who enable such mechanisms. More interestingly, when multi-hop extensions are enabled by some of the clients, it also positively impacts the performance at other clients that are completely unaware of these extensions.

title: Cooperative peer groups in NICE
abstract: A distributed scheme for trust inference in peer-to-peer networks is presented. Our work is in context of the NICE system, which is a platform for implementing cooperative applications over the Internet. We describe a technique for efficiently storing user reputation information in a completely decentralized manner, and show how this information can be used to efficiently identify noncooperative users in NICE. We present a simulation based study of our algorithms, in which we show our scheme scales to thousands of users using modest amounts of storage, processing, and bandwidth at any individual node. Lastly, we show that our scheme is robust and can form cooperative groups in systems where the vast majority of users are malicious.

title: Resilient multicast using overlays
abstract: We introduce Probabilistic Resilient Multicast (PRM): a multicast data recovery scheme that improves data delivery ratios while maintaining low end-to-end latencies. PRM has both a proactive and a reactive components; in this paper we describe how PRM can be used to improve the performance of application-layer multicast protocols especially when there are high packet losses and host failures. Through detailed analysis in this paper, we show that this loss recovery technique has efficient scaling properties-the overheads at each overlay node asymptotically decrease to zero with increasing group sizes. As a detailed case study, we show how PRM can be applied to the NICE application-layer multicast protocol. We present detailed simulations of the PRM-enhanced NICE protocol for 10 000 node Internet-like topologies. Simulations show that PRM achieves a high delivery ratio (>97%) with a low latency bound (600 ms) for environments with high end-to-end network losses (1%-5%) and high topology change rates (5 changes per second) while incurring very low overheads (<5%).

title: Scalable resilient media streaming
abstract: We present a low-overhead media streaming system, called SRMS (Scalable Resilient Media Streaming) that can be used to scalably deliver streaming data to a large group of receivers. SRMS uses overlay multicast for data distribution. to a large group of users. SRMS leverages a probabilistic loss recovery technique to provide high data delivery guarantees even under large network losses and overlay node failures. The clients in the SRMS system are able to interoperate with existing media streaming servers that use RTP for data transport. One of the interesting features of SRMS is that it can simultaneously support clients with disparate access bandwidths. It enables the necessary bandwidth adaptations using standard Real-time Transport Protocol (RTP) mechanisms, e.g. RTP translators. We have implemented and evaluated the SRMS system in detail on an emulated network as well as on a wide-area testbed with up to 128 clients. Our results show that clients using SRMS achieve high (97%) data delivery ratios with low overheads (<5%) even for a very dynamic network (up to five membership changes per minute).

title: Robust routing in wireless ad hoc networks
abstract: A wireless ad hoc network is a collection of mobile nodes with no fixed infrastructure. The absence of a central authorization facility in dynamic and distributed environments requires collaboration among nodes. When a source searches for a route to a destination, an intermediate node can reply with its cached entry. To strengthen correctness of such a routing discovery process, we propose a method in which the intermediate node requests its next hop to send a confirmation message to the source. After receiving both a route reply and confirmation message, the source determines the validity of a path according to its policy. As a result, this strategy discourages malicious nodes from intercepting packets. Simulation results show a remarkable improvement in throughput (30% higher delivery ratio and 10% less data transmission overhead) with a moderate increase of control messages.

title: Design and implementation of a multi-threaded TMN agent system
abstract: A telecommunications management network adopts the OSI manager-agent model in which an agent system plays a more important role than a manager system. Because the existing agent systems sequentially perform a CMIS operation on selected managed objects, it cannot guarantee quick response time when many managed objects are selected. We propose a multi-threaded process structure for the agent system which performs CMIS operations concurrently on managed objects. We implemented our agent system using OSIMIS-4.O TMN platform in Solaris. We measured response time to a CMIS operation to evaluate the performance of our system. Experimental results show that the performance of our system is not so good when network resources reside within the agent system, but very good when network resources reside outside the agent system.

title: Mammogram Analysis Using Two-Dimensional Autoregressive Models: Sufficient or Not?
abstract: Two-dimensional (2–D) autoregressive (AR) models have been used as one of the methods to characterise the textures of tumours in mammograms. Previously, the 2–D AR model coefficients were estimated for the block containing the tumour and the blocks in its 3 × 3 neighbourhood. In this paper, the possibility of having the estimated set of AR model coefficients of the block containing the tumour as a unique set of AR model coefficients for the entire mammogram is looked into. Based on the information given from the MiniMammography database, the possible number of blocks of the same size of the block containing the tumour is obtained from the entire mammogram and for each block a set of AR model coefficients is estimated using a method that combines both the Yule-Walker system of equations and the Yule-Walker system of equations in the third-order statistical domain. These sets of AR model coefficients are then compared. The simulation results show that 98.6% of the time we can not find another set of AR model coefficients representing the blocks of pixels in the possible neighbourhood of the entire mammogram for the data (95 mammograms with 5 of them having two tumours) available in the MiniMammography database.

title: Drug risk assessment with determining the number of sub-populations under finite mixture normal models
abstract: In some biological experiments, it is quite common that laboratory subjects may be different in their patterns of susceptibility to a treatment. In these situations, finite mixture model analysis becomes a useful tool. Under a finite mixture normal model, drug risk assessment problems are studied under the assumption that the population at risk consists of multiple sub-types of different susceptibilities. The EM algorithm and its extension are utilized to obtain the maximum likelihood estimates of the model. Particular discussion is given to the model selection problem based on Bayes factor, which is approximated by the Schwarz criterion. Meantime, the practical significance of the proposed method is illustrated with an actual dose–response data set.

title: A performance comparison study of ad hoc wireless multicast protocols
abstract: In this paper we investigate the performance of multicast routing protocols in wireless mobile ad hoc networks. An ad hoc network is composed of mobile nodes without the presence of a wired support infrastructure. In this environment, routing/multicasting protocols are faced with the challenge of producing multihop routes under host mobility and bandwidth constraints. In recent years, a number of new multicast protocols of different styles have been proposed for ad hoc networks. However, systematic performance evaluations and comparative analysis of these protocols in a common realistic environment has not yet been performed. In this study, we simulate a set of representative wireless ad hoc multicast protocols and evaluate them in various network scenarios. The relative strengths, weaknesses, and applicability of each multicast protocol to diverse situations are studied and discussed.

title: Blind signal separation and independent component analysis
abstract: Independent component analysis (ICA) is emerging as a new paradigm in signal processing and data analysis. ICA has been proposed as a solution to the blind source separation problem (BSS) in which sensory signals are given as mixtures of unknown source signals. Since neither the sources nor the mixing environment are known a priori there is no general analytical solution to this problem. However, since the last decade researchers have found good approximate solutions based on assumptions about the source statistics. They were able to formulate solutions or algorithms that were derived from well-known cost functions including maximum likelihood estimation, information maximization and higher-order cumulants. The ICA framework touches many theoretical research areas, and therefore receives attention in several research communities including machine learning, neural networks, statistical signal processing and Bayesian modeling. More recently, there have been numerous applications of ICA in adaptive 0ltering, speech signal processing, biomedical signal processing, computational neuroscience, image coding, text data modeling, and 0nancial data analysis. The standard ICA formulation has, in general, strong assumptions or simpli0cations such as: the number of sensors has to be equal or greater than the number of sources, there is no additive noise signal in the sensors, and the sources are modeled as random variables. However, when applying ICA to real-world problems it becomes evident that those restrictions are cumbersome and although the standard ICA algorithms give good approximate solutions, there is great need in going beyond the standard assumptions and develop new algorithms that can relax some of the assumptions. This special issue on ICA and BSS is a timely publication covering important recent 0ndings in ICA theory as well as new applications of ICA in data analysis. Leading researchers present their work to advance this 0eld beyond traditional borders and show how this 0eld can bridge disciplines and yield new methods that lead to mutual bene0ts and advances in science and engineering. This issue is composed of a review article and two parts: the 0rst part presents new theoretical 0ndings while the second part presents novel applications. Often, there is no such sharp division into these two parts since illustrative simulations support theoretical 0ndings and practical methods include algorithmic modi0cations to design and evaluate the application-speci0c methods. In “Frontiers of research in BSS=ICA”, V. David S: anchez A. formulates some of the basic concepts and problems in the areas of blind signal separation and independent component analysis. He then moves to a concise description of key methods of data preprocessing and algorithms that provide solutions to the instantaneous mixture and the