14844081
Constructing battery-aware virtual backbones in sensor networks
A critical issue in wireless sensor networks is to construct energy efficient virtual backbones for routing, broadcasting and data propagating. The minimum connected dominating set (MCDS) has been proposed as a backbone to reduce power dissipation and prolong network lifetime. However, we find that an MCDS cannot guarantee maximum network lifetime as it does not consider the battery discharging behavior. Recent study in battery technology reveals that the discharging of a battery is not linear. Batteries tend to discharge more power than needed, and reimburse the over-discharged power later if they have sufficiently long recovery time. In order to optimize network performance and construct an energy efficient virtual backbone in sensor networks, battery-awareness should be considered. In this paper we first study the mathematical battery discharging model and provide a simplified battery model suitable for implementation in sensor networks. We then introduce the concept of battery-aware connected dominating set (BACDS) and show that in general the BACDS can achieve longer lifetime than the MCDS. Then we show that finding a minimum BACDS (MBACDS) is NP-hard and give a distributed approximation algorithm to construct the BACDS. The resulting BACDS constructed by our algorithm is at most (8+/spl Delta/)opt size where /spl Delta/ is the maximum node degree and opt is the size of an optimal BACDS. The time and message complexities of the algorithm are O(n) and O(n(/spl radic/n+logn+/spl Delta/)), respectively, where n is the number of nodes in the network. The simulation results show that the BACDS constructed by our algorithm can save a significant amount of energy and achieve up to 30% longer network lifetime than the MCDS. To the best of our knowledge, this is the first work considering battery-awareness in the construction of connected dominating sets.
46660413
Optimal Scheduling Algorithms in WDM Optical Interconnects with Limited Range Wavelength Conversion Capability
In this paper we study optimal scheduling algorithms to resolve output contentions in time slotted WDM optical interconnects with wavelength conversion ability. We consider the general case of limited range wavelength conversion with arbitrary conversion capability, as it is easier to implement and more cost effective than full range wavelength conversion, and also includes full range wavelength conversion as a special case. We consider the conversion scheme in which each wavelength can be converted to multiple wavelengths belongs to an interval and the intervals for different wavelengths are “ordered”. To be specific, the conversion range of λ i can be written as [begin(i), end(i)], where begin(i) and end(i) are positive integers and if i < j then begin(i) ≤ begin(j) and end(i) ≤ end(j). We will present linear time optimal scheduling algorithms for both buffered and unbuffered WDM switches. We will also give performance studies of these switches when scheduled by these algorithms.
18081212
A novel analytical model for electronic and optical switches with shared buffer
Switches with shared buffer have lower packet loss probabilities than other types of switches when the sizes of the buffers are the same. In the past, the performance analysis for electronic shared buffer switches has been carried out extensively. However, due to the strong dependencies of the output queues in the buffer, it is very difficult to find a good analytical model. Existing models are either accurate but have exponential complexities or not very accurate. In this paper, we propose a novel analytical model called the aggregation model for switches with shared buffer. This model can be used for analyzing both electronic and optical switches, and has perfect accuracies under all tested conditions and has polynomial time complexity. It is based on the idea of induction: first find the behavior of 2 queues, then aggregate them into one block; then find the behavior of 3 queues while regarding 2 of the queues as one block, then aggregate the 3 queues into one block; then aggregate 4 queues and so on. When a sufficient number of queues have been aggregated, the behavior of the entire switch is found. We believe that the new model represents the best analytical model for shared buffer switches so far.
15006226
Bounds on the sizes of constant weight covering codes
Motivated by applications in universal data compression algorithms we study the problem of bounds on the sizes of constant weight covering codes. We are concerned with the minimal sizes of codes of lengthn and constant weightu such that every word of lengthn and weightv is within Hamming distanced from a codeword. In addition to a brief summary of part of the relevant literature, we also give new results on upper and lower bounds to these sizes. We pay particular attention to the asymptotic covering density of these codes. We include tables of the bounds on the sizes of these codes both for small values ofn and for the asymptotic behavior. A comparison with techniques for attaining bounds for packing codes is also given. Some new combinatorial questions are also arising from the techniques.
10965839
Automatic eyeglasses removal from face images
In this paper, we present an intelligent image editing and face synthesis system that automatically removes eyeglasses from an input frontal face image. Although conventional image editing tools can be used to remove eyeglasses by pixel-level editing, filling in the deleted eyeglasses region with the right content is a difficult problem. Our approach works at the object level where the eyeglasses are automatically located, removed as one piece, and the void region filled. Our system consists of three parts: eyeglasses detection, eyeglasses localization, and eyeglasses removal. First, an eye region detector, trained offline, is used to approximately locate the region of eyes, thus the region of eyeglasses. A Markov-chain Monte Carlo method is then used to accurately locate key points on the eyeglasses frame by searching for the global optimum of the posterior. Subsequently, a novel sample-based approach is used to synthesize the face image without the eyeglasses. Specifically, we adopt a statistical analysis and synthesis approach to learn the mapping between pairs of face images with and without eyeglasses from a database. Extensive experiments demonstrate that our system effectively removes eyeglasses.
14053219
Distributed Algorithm for Service Replication in Service Overlay Network
The service overlay network (SON) is an effective mean to deploy end-to-end QoS guaranteed content delivery services on the current Internet. We model the content delivery service on a SON as a service delivery tree (SDT). Previous studies have addressed the optimal distribution tree formulation issues. In this paper, we focus on the problem of maximizing the total operation profit of the SON. In [1], authors introduced a cost model for optimal bandwidth provisioning in SON. In this paper, we extended this concept and propose an alternative approach to maximize the total effective throughput of SDT as well as to minimize the QoS violation penalty of the SON by service replication. We present both centralized and distributed algorithms for the placement of replicated servers on the SDT. Experiments are carried to quantify the merit, effectiveness and the scalability of the proposed service replication algorithm. In particular, the performance gain is very close to the exhaustive search. The algorithm performs well when we scale up the service overlay networks. Finally, we show that one only needs to perform a small number of replications to attain the optimal gain.
2128570
Peer-to-peer based multimedia distribution service
Recently, there are many research interests in providing efficient and scalable multimedia distribution service. However, stringent quality-of-service (QoS) requirements for media distribution, as well as dynamically changing and heterogeneous network capacity in today's best effort Internet, bring many challenges. In this paper, we introduce a novel framework for multimedia distribution service based on peer-to-peer (P2P) networks. A topology-aware overlay is proposed in which hosts self-organize into groups. End hosts within the same group have similar network conditions and can easily collaborate with each other to achieve QoS awareness. In order to improve media delivery quality and provide high service availability, we further propose two distributed heuristic replication strategies, intergroup replication and intragroup replication, based on this topology-aware overlay. Specifically, intergroup replication is aimed to improve the efficiency of media content delivery between the group where a request is issued and the group where the content is stored. Also, intragroup replication is targeted at improving the availability of the content. Extensive simulation results show that the latency in our proposed architecture is 20% less than that of the FreeNet and 50% less than that of the randomly replication system. Simulation results also show that the video quality in our system is much better than that in the other two systems. Our P2P-based approach is also distributed, scalable, cost effective, and aware of the performance.
46726594
False-Negative Frequent Items Mining from Data Streams with Bursting
False-negative frequent items mining from a high speed transactional data stream is to find an approximate set of frequent items with respect to a minimum support threshold, s. It controls the possibility of missing frequent items using a reliability parameter δ. The importance of false-negative frequent items mining is that it can exclude false-positives and therefore significantly reduce the memory consumption for frequent itemsets mining. The key issue of false-negative frequent items mining is how to minimize the possibility of missing frequent items. In this paper, we propose a new false-negative frequent items mining algorithm, called Loss-Negative, for handling bursting in data streams. The new algorithm consumes the smallest memory in comparison with other false-negative and false-positive frequent items algorithms. We present theoretical bound of the new algorithm, and analyze the possibility of minimization of missing frequent items, in terms of two possibilities, namely, in-possibility and out-possibility. The former is about how a frequent item can possibly pass the first pruning. The latter is about how long a frequent item can stay in memory while no occurrences of the item comes in the following data stream for a certain period. The new proposed algorithm is superior to the existing false-negative frequent items mining algorithms in terms of the two possibilities. We demonstrate the effectiveness of the new algorithm in this paper.