1285513
A distributed approach to solving overlay mismatching problem
In unstructured peer-to-peer (P2P) systems, the mechanism of a peer randomly joining and leaving a P2P network causes topology mismatching between the P2P logical overlay network and the physical underlying network, causing a large volume of redundant traffic in the Internet. In order to alleviate the mismatching problem, we propose adaptive connection establishment (ACE), an algorithm of building an overlay multicast tree among each source node and the peers within a certain diameter from the source peer, and further optimizing the neighbor connections that are not on the tree, while retaining the search scope. Our simulation study shows that this approach can effectively solve the mismatching problem and significantly reduce P2P traffic. We further study the tradeoffs between the topology optimization rate and the information exchange overhead by changing the diameter used to build the tree.
12060317
DiCAS: An Efficient Distributed Caching Mechanism for P2P Systems
Peer-to-peer networks are widely criticized for their inefficient flooding search mechanism. Distributed hash table (DHT) algorithms have been proposed to improve the search efficiency by mapping the index of a file to a unique peer based on predefined hash functions. However, the tight coupling between indices and hosting peers incurs high maintenance cost in a highly dynamic network. To properly balance the tradeoff between the costs of indexing and searching, we propose the distributed caching and adaptive search (DiCAS) algorithm, where indices are passively cached in a group of peers based on a predefined hash function. Guided by the same function, adaptive search selectively forwards queries to "matched" peers with a high probability of caching the desired indices. The search cost is reduced due to shrunk searching space. Different from the DHT solutions, distributed caching loosely maps the index of a file to a group of peers in a passive fashion, which saves the cost of updating indices. Our simulation study shows that the DiCAS protocol can significantly reduce the network search traffic with the help of small cache space contributed by each individual peer
6911930
LANDMARC: Indoor Location Sensing Using Active RFID
Growing convergence among mobile computing devices and embedded technology sparks the development and deployment of “context-aware” applications, where location is the most essential context. In this paper we present LANDMARC, a location sensing prototype system that uses Radio Frequency Identification (RFID) technology for locating objects inside buildings. The major advantage of LANDMARC is that it improves the overall accuracy of locating objects by utilizing the concept of reference tags. Based on experimental analysis, we demonstrate that active RFID is a viable and cost-effective candidate for indoor location sensing. Although RFID is not designed for indoor location sensing, we point out three major features that should be added to make RFID technologies competitive in this new and growing market.
35965067
Dynamic Layer Management in Superpeer Architectures
Superpeer unstructured P2P systems have been found to be very effective by dividing the peers into two layers, superlayer and leaf-layer, in which message flooding is only conducted among superlayer and all leaf-peers are represented by corresponding superpeers. However, current superpeer systems do not employ any effective layer management schemes, so the transient and low-capacity peers are allowed to act as superpeers. Moreover, the lack of an appropriate size ratio maintenance mechanism on superlayer to leaf-layer makes the system's search performance far from being optimal. We present one workload model aimed at reducing the weighted overhead of a network. Using our proposed workload model, a network can determine an optimal layer size ratio between leaf-layer and superlayer. We then propose a dynamic layer management algorithm, DLM, which can maintain an optimal layer size ratio and adaptively elect and adjust peers between superlayer and leaf-layer. DLM is completely distributed in the sense that each peer decides to be a superpeer or a leaf-peer independently without global knowledge. DLM could effectively help a superpeer P2P system maintain the optimal layer size ratio and designate peers with relatively long lifetime and large capacities as superpeers, and the peers with short lifetime and low capacities as leaf-peers under highly dynamic network situations. We demonstrate that the quality of a superpeer system is significantly improved under the DLM scheme by comprehensive simulations.
848425
Location awareness in unstructured peer-to-peer systems
Peer-to-peer (P2P) computing has emerged as a popular model aiming at further utilizing Internet information and resources. However, the mechanism of peers randomly choosing logical neighbors without any knowledge about underlying physical topology can cause a serious topology mismatch between the P2P overlay network and the physical underlying network. The topology mismatch problem brings great stress in the Internet infrastructure. It greatly limits the performance gain from various search or routing techniques. Meanwhile, due to the inefficient overlay topology, the flooding-based search mechanisms cause a large volume of unnecessary traffic. Aiming at alleviating the mismatching problem and reducing the unnecessary traffic, we propose a location-aware topology matching (LTM) technique. LTM builds an efficient overlay by disconnecting slow connections and choosing physically closer nodes as logical neighbors while still retaining the search scope and reducing response time for queries. LTM is scalable and completely distributed in the sense that it does not require any global knowledge of the whole overlay network. The effectiveness of LTM is demonstrated through simulation studies.
18230
Indexable PLA for Efficient Similarity Search
Similarity-based search over time-series databases has been a hot research topic for a long history, which is widely used in many applications, including multimedia retrieval, data mining, web search and retrieval, and so on. However, due to high dimensionality (i.e. length) of the time series, the similarity search over directly indexed time series usually encounters a serious problem, known as the "dimensionality curse". Thus, many dimensionality reduction techniques are proposed to break such curse by reducing the dimensionality of time series. Among all the proposed methods, only Piecewise Linear Approximation (PLA) does not have indexing mechanisms to support similarity queries, which prevents it from efficiently searching over very large time-series databases. Our initial studies on the effectiveness of different reduction methods, however, show that PLA performs no worse than others. Motivated by this, in this paper, we re-investigate PLA for approximating and indexing time series. Specifically, we propose a novel distance function in the reduced PLA-space, and prove that this function indeed results in a lower bound of the Euclidean distance between the original time series, which can lead to no false dismissals during the similarity search. As a second step, we develop an effective approach to index these lower bounds to improve the search efficiency. Our extensive experiments over a wide spectrum of real and synthetic data sets have demonstrated the efficiency and effectiveness of PLA together with the newly proposed lower bound distance, in terms of both pruning power and wall clock time, compared with two state-of-the-art reduction methods, Adaptive Piecewise Constant Approximation (APCA) and Chebyshev Polynomials (CP).
903407
On integrating fluid models with packet simulation
Fluid models have been shown to he efficient and accurate in modelling large IP networks. However, unlike packet models, it is difficult to extract packet-level information from them. In this paper, we present a hybrid simulation method that maintains the performance advantage of fluid models while providing detailed packet level information for selected packet traffic flows. We propose two models to account for the interaction between background TCP traffic in a fluid network and foreground packet traffic of interest. The first assumes that the packet traffic poses a negligible load on the fluid network whereas the second accounts for the added load by transforming the packet traffic into fluid flows and solving the resulting enhanced fluid model. The first of these yields an efficient one pass solution algorithm whereas the second requires an additional pass to account for the packet traffic load. We establish the correctness of both approaches and present their implementation within ns-2. Comparisons between the hybrid models and a classical packet simulation show the two pass approach to be quite accurate and computationally efficient.
17725399
Regulating gene expression using optimal control theory
We described development of a novel genome-based model-driven strategy useful for regulating eukaryotic gene expression. In order to extract biologically meaningful information from a large volume of mRNA expression data, we built previously a PROmoter-Based Estimation (PROBE) model. The PROBE model allowed us to establish a quantitative relationship between transcription-factor binding motifs in regulatory DNA sequences and mRNA expression levels. Here, we extended PROBE formulation to derive an optimal control law for gene regulation. The responses to shear stress in human synovial cells were chosen as a model biological system, and the system dynamics was identified from the expression pattern of the genes involved in degradation and maintenance of extracellular matrix. In order to suppress the responses to mechanical stimuli, a Ricatti equation was solved and an admissible control law was derived. The approach presented here can be implemented in any biological process, and it would be useful to develop a transcription-mediated strategy for gene therapies and tissue engineering.
6717587
Capacity of memoryless channels and block-fading channels with designable cardinality-constrained channel state feedback
A coding theorem is proved for memoryless channels when the channel state feedback of finite cardinality can be designed. Channel state information is estimated at the receiver and a function of the estimated channel state is causally fed back to the transmitter. The feedback link is assumed to be noiseless with a finite feedback alphabet, or equivalently, finite feedback rate. It is shown that the capacity can be achieved with a memoryless deterministic feedback and with a memoryless device which select transmitted symbols from a codeword of expanded alphabet according to current feedback. To characterize the capacity, we investigate the optimization of transmission and channel state feedback strategies. The optimization is performed for both channel capacity and error exponents. We show that the design of the optimal feedback scheme is identical to the design of scalar quantizer with modified distortion measures. We illustrate the optimization using Rayleigh block-fading channels. It is shown that the optimal transmission strategy has a general form of temporal water-filling in important cases. Furthermore, while feedback enhances the forward channel capacity more effectively in low-signal-to noise ratio (SNR) region compared with that of high-SNR region, the enhancement in error exponent is significant in both high- and low-SNR regions. This indicates that significant gain due to finite-rate channel state feedback is expected in practical systems in both SNR regions.
8733679
Stochastic Fluid Theory for P2P Streaming Systems
We develop a simple stochastic fluid model that seeks to expose the fundamental characteristics and limitations of P2P streaming systems. This model accounts for many of the essential features of a P2P streaming system, including the peers' realtime demand for content, peer churn (peers joining and leaving), peers with heterogeneous upload capacity, limited infrastructure capacity, and peer buffering and playback delay. The model is tractable, providing closed-form expressions which can be used to shed insight on the fundamental behavior of P2P streaming systems. The model shows that performance is largely determined by a critical value. When the system is of moderate-to-large size, if a certain ratio of traffic loads exceeds the critical value, the system performs well; otherwise, the system performs poorly. Furthermore, large systems have better performance than small systems since they are more resilient to bandwidth fluctuations caused by peer churn. Finally, buffering can dramatically improve performance in the critical region, for both small and large systems. In particular, buffering can bring more improvement than can additional infrastructure bandwidth.
16346812
A hoare-style proof system for robot programs
Golog is a situation calculus-based logic programming language for high-level robotic control, This paper explores Hoare's axiomatic approach to program verification in the Golog context. We present a novel Hoare-style proof system for partial correctness of Golog programs. We prove total soundness of the proof system, and relative completeness of a subsystem of it for procedureless Golog programs. Examples are given to illustrate the use of the proof system.