RETRACTED ARTICLE: Skyline Query Optimization for Preferable Product Selection and Recommendation System

Many social marketing systems use decision-making strategies for implementing product dominance analysis. The objective of the proposed work is to classify on-time issues in observing highly preferable market products, which is newer in online market places. Existing researches are interested to be useful for customers to identify the best possible products groups from the vast product details. To deal with this main objective, different types of product instances are reviewed. In this case, the price of popular products and the product groups are evaluated. This proposed system analyses the need for online market growth using novel skyline query analysis. The proposed system monitor user-based ratings affect the sales of various products. After finding the desirable products, the market prices are predicted. Once products are predicted, the new packages are assigned with optimal prices and added to the package database. Moreover, the proposed Skyline Query Optimization and Security Management System (SQOSMS) approach is focused on authorized user ratings and ensures they are more secured. The review system validates each and every user identities with the user activities involved with in review system. This is considered as major objective of this proposed system. The implementation section shows that the proposed system provides 10–15% of reduced movie lists than other systems. This illustrates the proposed SQOSMS’s controlled performance over the selection of preferable products.

     

A conceptual framework for network and client adaptation

Modern networks are extremely complex, varying both statically and dynamically. This complexity and dynamism are greatly increased when the network contains mobile elements. A number of researchers have proposed solutions to these problems based on dynamic adaptation to changing network conditions and application requirements. This paper summarizes the results of several such projects and extracts several important general lessons learned about adapting data flows over difficult network conditions. These lessons are then formulated into a conceptual framework that demonstrates how a few simple and powerful ideas can describe a wide variety of different software adaptation systems. This paper describes an Adaptation Framework in the context of the several successful adaptation systems and suggests how the framework can help researchers think about the problems of adaptivity in networks.     

NEST: novel eMBMS scheduling technique

In order to meet the growing demand for mobile multimedia broadcast services 3GPP includes evolved multimedia broadcast and multicast (eMBMS) services in LTE systems. The high data rates, low latency and QoS provisioning makes LTE systems more suitable for mobile broadcast and multicast services than legacy wireless networks. However, the 3GPP standards has not specified any scheduling strategy for this broadcast and multicast services. In this paper, we propose a novel eMBMS scheduling technique (NEST) which focuses on reducing the average waiting time (latency) of the broadcast services offered by LTE system. This paper has twofold contributions. We proffer NEST considering two types of impatience that is user equipment (UE) departure and UE request repetition. Our proposed scheduling strategy estimates the effects originating from the departure of the mobile UEs and UE request repetition case. It intelligently combines the advantages of both flat scheduling and on-demand scheduling in such a way that the overall latency of the system is reduced. We design a suitable modeling framework to analyze the performance of the system. Simulation experiments on typical LTE systems support the performance analysis and demonstrates 10 % gains while comparing with existing eMBMS scheduling available in present LTE systems.     

PRESTO: Feedback-Driven Data Management in Sensor Networks

This paper presents PRESTO, a novel two-tier sensor data management architecture comprising proxies and sensors that cooperate with one another for acquiring data and processing queries. PRESTO proxies construct time-series models of observed trends in the sensor data and transmit the parameters of the model to sensors. Sensors check sensed data with model-predicted values and transmit only deviations from the predictions back to the proxy. Such a model-driven push approach is energy-efficient, while ensuring that anomalous data trends are never missed. In addition to supporting queries on current data, PRESTO also supports queries on historical data using interpolation and local archival at sensors. PRESTO can adapt model and system parameters to data and query dynamics to further extract energy savings. We have implemented PRESTO on a sensor testbed comprising Intel Stargates and Telos Motes. Our experiments show that in a temperature monitoring application, PRESTO yields one to two orders of magnitude reduction in energy requirements over on-demand, proactive or model-driven pull approaches. PRESTO also results in an order of magnitude reduction in query latency in a 1% duty-cycled five hop sensor network over a system that forwards all queries to remote sensor nodes.      

Transmitter adaptation in multicode DS-CDMA systems

The problem of transmitter adaptation in the form of adapting the spreading sequences and the transmission powers of different users for a multicode direct-sequence code division multiple access (DS-CDMA) system is considered. Particular attention is given to a distributed algorithm, which updates each pair of transmitter and receiver without information from other users. The transmitter adaptation problem and the algorithm are studied from the viewpoint of a single user, as well as the viewpoint of the whole system. The algorithm is shown to give either the optimal sequences or a choice of sequences that is close to the optimal one. Simulation results show that major improvement in performance can be obtained with the proposed transmission adaptation scheme. The effect of restricting the choice of sequences to polyphase sequences is also considered     

Algebra-Based Scalable Overlay Network Monitoring: Algorithms, Evaluation, and Applications

Overlay network monitoring enables distributed Internet applications to detect and recover from path outages and periods of degraded performance within seconds. For an overlay network with end hosts, existing systems either require measurements, and thus lack scalability, or can only estimate the latency but not congestion or failures. Our earlier extended abstract [Y. Chen, D. Bindel, and R. H. Katz, ldquoTomography-based overlay network monitoring,rdquo Proceedings of the ACM SIGCOMM Internet Measurement Conference (IMC), 2003] briefly proposes an algebraic approach that selectively monitors linearly independent paths that can fully describe all the paths. The loss rates and latency of these paths can be used to estimate the loss rates and latency of all other paths. Our scheme only assumes knowledge of the underlying IP topology, with links dynamically varying between lossy and normal. In this paper, we improve, implement, and extensively evaluate such a monitoring system. We further make the following contributions: i) scalability analysis indicating that for reasonably large n (e.g., 100), the growth of k is bounded as O(n log n), ii) efficient adaptation algorithms for topology changes, such as the addition or removal of end hosts and routing changes, iii) measurement load balancing schemes, iv) topology measurement error handling, and v) design and implementation of an adaptive streaming media system as a representative application. Both simulation and Internet experiments demonstrate we obtain highly accurate path loss rate estimation while adapting to topology changes within seconds and handling topology errors.     

iSMS: an integration platform for short message service and IPnetworks

This article describes iSMS, a platform that integrates IP networks with the short message service in mobile telephone systems. iSMS provides a generic gateway for creating and hosting wireless data services for mobile stations. Our approach does not require any modification to the mobile telephone system architecture. The iSMS system can be quickly developed and operated by a third party or end user without involvement of mobile equipment manufacturers and telecom operators. Based on the iSMS platform, we illustrate services such as e-mail delivery/forwarding, Web access (e.g., stock and train schedule query) and handset music services. The iSMS platform and the services have been implemented for GSM networks. With iSMS, users are able to use standard GSM handsets to access wireless Internet services, while other approaches like the Wireless Application Protocol and SIM Toolkit services require function-enabled MSs     

Decentralized formation control for small-scale robot teams with anonymity

This paper presents decentralized formation controls for a team of anonymous mobile robots performing a task through cooperation. Robot teams are required to generate and maintain various geometric patterns adapting to environmental changes in many cooperative robotics applications. In particular, all robots must continue to strive toward achieving the team’s mission even if some members fail to perform their role. Toward this end, formation control approaches are proposed under the conditions that robot teams are initially not allowed to have individual identification numbers (IDs), a predetermined leader, and agreement on coordinate systems. Therefore, all members are required first to reach agreement on their coordinate system and obtain unique IDs for role allocations in a self-organizing way. Then, employing IDs within a common coordinate system, two formation control approaches can be realized: leader-referenced and neighbor-referenced formations. Both approaches are verified using an in-house simulator and physical mobile robots. We detail and evaluate each formation control approach, whose common features include self-organization, robustness, and flexibility.     

ANTS: Efficient Vehicle Locating Based on Ant Search in ShanghaiGrid

Intelligent transportation systems (ITSs) have become increasingly important for public transportation in Shanghai, China. In response, ShanghaiGrid (SG) aims to provide abundant intelligent transportation services to improve traffic conditions. A fundamental service in SG is to locate the nearest desirable vehicles for users. In this paper, we propose an innovative protocol called ANTS to locate a desirable vehicle close to the querying user. The protocol finely mimics the efficient searching strategy adopted by a lost ant searching for its nest. Taking query locality into account, ANTS can retrieve the closest vehicles satisfying the query with high probability but incurs small query latency and modest network traffic. ANTS is a fully distributed and robust protocol and, therefore, has good scalability. Extensive simulations based on the real road network and the trace data of vehicle movements in Shanghai demonstrate the efficacy of ANTS.     

Evaluation of relevance feedback schemes in content-based in retrieval systems

Multimedia content modeling, i.e., identification of semantically meaningful entities, is an arduous task mainly due to the fact that (a) humans perceive the content using high-level concepts and (b) the subjectivity of human perception, which often interprets the same content in a different way at different times. For this reason, an efficient content management system has to be adapted to current user's information needs and preferences through an on-line learning strategy based on users’ interaction. One adaptive learning strategy is relevance feedback, originally developed in traditional text-based information retrieval systems. In this way, the user interacts with the system to provide information about the relevance of the content, which is then fed back to the system to update its performance. In this paper, we evaluate and investigate three main types of relevance feedback algorithms; the Euclidean, the query point movements and the correlation-based approaches. In the first case, we examine heuristic and optimal techniques which are based either on the weighted or the generalized Euclidean distance. In the second case, we survey single and multipoint query movement schemes. As far as the third type is concerned, two different ways for parametrizing the normalized cross-correlation similarity metric are proposed. The first scales only the elements of the query feature vector and called query-scaling strategy, while the second scales both the query and the selected samples (query-sample scaling strategy). All the examined algorithms are evaluated using both subjective and objective criteria. Subjective evaluation is performed by depicting the best retrieved images as response of the system to a user's query. Instead, objective evaluation is obtained using standard criteria, such as the precision–recall curve and the average normalized modified retrieval rank (ANMRR). Furthermore, a newly objective criterion, called average normalized similarity metric distance is introduced which exploits the difference among the actual and ideal similarity measure among all best retrievals. Discussions and comparisons of all the aforementioned relevance feedback algorithms are presented.     

Adaptive wireless thin‐client model for mobile computing

The thin‐client computing model has the potential to significantly increase the performance of mobile computing environments. By delivering any application through a single, small‐footprint client (called a thin client) implemented on a mobile device, it is possible to optimize application performance without the need for building wireless application gateways. We thus present two significant contributions in the area of wireless thin‐client computing. Firstly, a mathematical performance model is derived for wireless thin‐client system. This model identifies factors that affect the performance of the system and supports derivation and analysis of adaptation strategies to maintain a user‐specified quality of service (QoS). Secondly, a proxy‐based adaptation framework is developed for wireless thin‐client systems, which dynamically optimizes performance of a wireless thin client via dynamically discovered context. This is implemented with rule‐based fuzzy logic that responds to variations in wireless link bandwidth and client processing power. Our fuzzy inference engine uses contextual data to dynamically optimize tradeoffs among different quality of service parameters offered to the end users. Additionally, our adaptation framework uses highly scalable wavelet‐based image coding to provide scalable QoS that can degrade gracefully. Our thin‐client adaptation framework shields the user from ill effects of highly variable wireless network quality and mobile device resources. This improves performance of active applications, in which the display changes frequently. Further, active application behaviour may produce high transmission latency for screen updates, which can adversely affect user perception of QoS, resulting in poor interactivity. We report measured adaptive performance under realistic mobile device and network conditions for several different clients and servers. Copyright © 2008 John Wiley & Sons, Ltd.     

Joint Scheduling and Resource Allocation with Fairness Based on the Signal-to-Leakage-plus-Noise Ratio in the Downlink of CoMP Systems

Recent research has shown that coordinated multi point (CoMP) transmission can provide significant gains in terms of the overall cell capacity and cell-edge user throughput [1]. The main purpose of this paper is to enhance the overall cell throughput, the cell-edge user’s throughput, and the fairness among user equipment terminals (UEs) in LTE-Advanced (LTE-A) systems using CoMP. Towards that end, we propose two novel resource allocation (RA) strategies based on the Signal-to-Leakage-plus-Noise-Ratio (SLNR) for the downlink of CoMP transmission in LTE-A systems. The proposed RA strategies select the UEs that can efficiently share the same resource block (RB) without degrading the overall throughput by using the SLNR metric. Moreover, a fairness algorithm is proposed to achieve certain level of fairness among the UEs and to improve the cell-edge UEs throughput. In addition, we compare the proposed strategies to the RA based on the more common Signal-to-Interference-plus-Noise-Ratio (SINR) strategy. The SLNR-based RA is shown to provide significant gains in throughput reaching up to 80 % in the overall system and is shown to have even less complexity than the typical SINR-based RA. Moreover, by evaluating the proposed strategies in terms of the average cell throughput, cell-edge user throughput, and fairness among UEs, simulations show that the proposed strategies present superior performance compared to the more common SINR strategy. With such advantages as enhanced throughput and lower complexity, the proposed schemes are suitable for application in practical cellular systems.     

Non-Intrusive Online Quality of Experience Assessment for Voice Communications

Recently user quality of experience (QoE) is employed in evaluating end user satisfaction in communications systems. Generally, current approaches for QoE assessment are obtrusive, laboratory based and offline. Estimation of user satisfaction in static manner based on mean opinion score is not directly related to instantaneous individual end user contentment. In this paper, based on correlations between user’s physiological signals and her/his feelings about the service quality, a non-intrusive and user centric QoE assessment system for voice communications is developed. The findings of this study indicate that the emotional patterns in response to the changes in channel quality can be adapted to estimate the level of satisfaction in a QoE assessment system in a live manner. Based on experimental results, two categories of users are identified: sensitive and insensitive towards quality degradations. The results indicate that for the sensitive users, our non-intrusive subjective quality assessment method outperforms ITU-T P.563 standard with respect to root mean square error; while, the results are much better among the insensitive users.     

Autonomous Dynamic Power Control for Wireless Networks: User-Centric and Network-Centric Consideration

Dynamic adaptation of transmission power has been researched as a technique for improving the performance and capacity of wireless networks. In this paper an estimator-based algorithm is presented for distributed power control. The proposed power control policy is optimal with respect to users dynamically allocating transmit power so as to minimize an objective function consisting of the user's performance degradation and the network interference. The policy enables a user to address various user-centric and network-centric objectives by adapting power in either a greedy or energy efficient manner. The algorithm is predictive, with a user performing autonomous interference estimation and prediction prior to adapting transmit power. Also, closed-loop implementation of the algorithm is of reasonable complexity thus allowing for distributed online operation. Subsequently, the robustness of the algorithm to stochastic detriments such as a time varying channel and noisy measurements is investigated.     

Adaptive Radio Resource Allocation for a Mobile Packet Service in Multibeam Satellite Systems

In this paper, we introduce an adaptive radio resource allocation for IP‐based mobile satellite services. We also present a synchronous multibeam CDMA satellite system using an orthogonal resource sharing mechanism among downlink beams for the adaptive packet transmission. The simulation results, using a Ka‐band mobile satellite channel and various packet scheduling schemes, show that the proposed system and resource allocation scheme improves the beam throughput by more than two times over conventional systems. The simulation results also show that, in multibeam satellite systems, a system‐level adaptation to a user's channel and interference conditions according to user locations and current packet traffic is more efficient in terms of throughput improvement than a user‐level adaptation.     

个性化搜索中一种基于位置服务的隐私保护方法

在基于位置服务的个性化搜索中,利用可信第三方服务器以及对等节点是保护用户隐私的主要方法,但在现实生活中,它们却是不完全可信的。为了解决这一问题,该文提出一种个性化搜索中基于位置服务的隐私保护方法。该方法通过转换用户的位置信息,并根据用户的查询类型生成用户模型,进而形成带有用户位置信息的查询矩阵,然后利用矩阵加密用户的查询,隐藏查询矩阵中的用户信息,最后根据安全内积计算返回相关性得分最高的前K个查询文件给用户。安全性分析表明该方法能有效地保护用户的查询隐私和位置隐私,通过分析与实验表明,该方法大幅度地缩短了索引构建时间,降低了通信开销,同时为用户提供了基于位置的个性化搜索结果,一定程度上解决了移动设备屏幕小带来的弊端。     

ARMOR – A system for adjusting repair and media scaling for video streaming

To optimize scarce network resources and present the highest quality video, streaming video systems need adapt to the video content as well as the network conditions. This paper presents ARMOR, a video streaming system that dynamically adjusts repair and media scaling to meet current video and network conditions. In order to adapt effectively, ARMOR, and any dynamic video adaptation system, needs to predict the video quality as perceived by end users over the range of scaling and repair choices. Thus, this paper first proposes a novel video quality metric called distorted playable frame rate that provides estimation of user perceptual quality considering temporal and quality degradations. Comprehensive user studies show distorted playable frame rate is more accurate than other video quality metrics. Analytic experiments with distorted playable frame rate and the ARMOR optimization algorithm illustrate the predictive power of the metric in a dynamic, streaming video system. Lastly, implementation and experiments of a complete, fully-functioning ARMOR system show the effective practicality of the proposed approach.     

On Improving the Performance of Cache Invalidation in Mobile Environments

Many cache management schemes designed for mobile environments are based on invalidation reports (IRs). However, IR-based approach suffers from long query latency and it cannot efficiently utilize the broadcast bandwidth. In this paper, we propose techniques to address these problems. First, by replicating a small fraction of the essential information related to cache invalidation, the query latency can be reduced. Then, we propose techniques to efficiently utilize the broadcast bandwidth based on counters associated with each data item. Novel techniques are designed to maintain the accuracy of the counter in case of server failures, client failures, and disconnections. Extensive simulations are provided and used to evaluate the proposed methodology. Compared to previous IR-based algorithms, the proposed solution can significantly reduce the query latency, improve the bandwidth utilization, and effectively deal with disconnections and failures.     

Scheduling flows over LEO constellations on LMS channels

Satellite systems typically use physical and link layer reliability schemes to compensate the significant channel impairments, especially for the link between a satellite and a mobile end‐user. These schemes have been introduced at the price of an increase in the end‐to‐end delay, high jitter, or out‐of‐order packets. This is shown to have a negative impact both on multimedia and best‐effort traffic, decreasing the Quality of Experience (QoE) of users. In this paper, we propose to solve this issue by scheduling data transmission as a function of the channel condition. We first investigate existing scheduling mechanisms and analyze their performance for two kinds of traffic: VoIP and best‐effort. In the case of VoIP traffic, the objective is to lower both latency and jitter, which are the most important metrics to achieve a consistent VoIP service. We select the best candidate among several schedulers and propose a novel algorithm specifically designed to carry VoIP over LEO constellations. We then investigate the performance of the scheduling policies on internet‐browsing traffic carried by TCP, where the goal is now the maximize the users' goodput and select the best candidate in this case.     

Design of an FPGA based DPLL with fuzzy logic controllable loop filters with application customization capability

The carrier recovery loops are important in carrier tracking approaches particularly in the presence of high dynamic stress on user receivers and noisy environment applications. The precise carrier tracking techniques are proposed in systems that are sensitive to carrier mismatches, such as terrestrial or satellite tracking systems. The fading phenomenon, phase and frequency step changes and high user dynamics are currently most important challenges in the development of robust carrier tracking systems. In this work, a novel Digital Phase Locked Loop (DPLL) is proposed using type-2 fuzzy logic controller to improve noise immunity and handling user dynamic in digital receivers with application customization capability. Due to fast and accurate decision-making by proposed fuzzy logic controller, optimal loop filter coefficients are generated for DPLL. The proposed DPLL is simulated with Xilinx System Generator Software and can be implemented on FPGA. In comparison to traditional approaches, proposed new DPLL shows better performance in response to phase step, frequency step and frequency ramp signals with acceptable settling time alongside minimum complexity in implementation and customization.