Reliable distributed data stream management in mobile environments

The proliferation of sensor technology, especially in the context of embedded systems, has brought forward novel types of applications that make use of streams of continuously generated sensor data. Many applications like telemonitoring in healthcare or roadside traffic monitoring and control particularly require data stream management (DSM) to be provided in a distributed, yet reliable way. This is even more important when DSM applications are deployed in a failure-prone distributed setting including resource-limited mobile devices, for instance in applications which aim at remotely monitoring mobile patients. In this paper, we introduce a model for distributed and reliable DSM. The contribution of this paper is threefold. First, in analogy to the SQL isolation levels, we define levels of reliability and describe necessary consistency constraints for distributed DSM that specify the tolerated loss, delay, or re-ordering of data stream elements, respectively. Second, we use this model to design and analyze an algorithm for reliable distributed DSM, namely efficient coordinated operator checkpointing (ECOC). We show that ECOC provides lossless and delay-limited reliable data stream management and thus can be used in critical application domains such as healthcare, where the loss of data stream elements cannot be tolerated. Third, we present detailed performance evaluations of the ECOC algorithm running on mobile, resource-limited devices. In particular, we can show that ECOC provides a high level of reliability while, at the same time, featuring good performance characteristics with moderate resource consumption.     

Using cooperative mobile agents to monitor distributed and dynamic environments

Monitoring the changes in data values obtained from the environment (e.g., locations of moving objects) is a primary concern in many fields, as for example in the pervasive computing environment. The monitoring task is challenging from a double perspective. First and foremost, the environment can be highly dynamic in terms of the rate of data changes. Second, the monitored data are often not available from a single computer/device but are distributed; moreover, the set of data providers can change along the course of time. Therefore, obtaining a global snapshot of the environment and keeping it up-to-date is not easy, especially if the conditions (e.g., network delays) change.In this article, a decentralized, loose, and fault-tolerant monitoring approach based on the use of mobile agents is described. Mobile agents allow easy tracking of the involved computers, carrying the monitoring tasks to wherever they are needed. A deadline-based mechanism is used to coordinate the cooperative agents, which strive to perform their continuous tasks in time while considering data as recent as possible, constantly adapting themselves to new environmental conditions (changing communication and processing delays). This approach has been successfully used in a real environment and experiments were carried out to prove its feasibility and benefits.     

Clustering techniques for dynamic location management in mobile computing

This paper presents a novel approach based on clustering algorithms in combination with the location area (LA) scheme to solve the mobility management problem. Users’ movement history is used by the network to predict future paging decisions. This approach integrates the LAs scheme and efficient clustering algorithms to find a network topology which can lead to massive savings in the number of signals made to locate users in the network. The approach is tested with several networks to show its advantages to the current GSM standards. The results provide new insights into the mobility management problem.     

Role of big data management in enhancing big data decision-making capability and quality among Chinese firms: A dynamic capabilities view

This study examines the antecedents and influence of big data decision-making capabilities on decision-making quality among Chinese firms. We propose that such capabilities are influenced by big data management challenges such as leadership, talent management, technology, and organisational culture. By using primary data from 108 Chinese firms and utilising partial least squares, we tested the antecedents of big data decision-making capability and its impact on decision-making quality. Findings suggest that big data management challenges are the key antecedents of big data decision-making capability. Furthermore, the latter is vital for big data decision-making quality.     

Proactive workload management in dynamic virtualized environments

Recently, with the improvement of Cloud systems technologies and the essential advantages they can provide such as availability, scalability, and costs saving; massive domains in the IT industry are directing their business to the Cloud. To fit the computing demands of this trend along with nowadays fluky applications (e.g. social networks, media contents), Cloud systems require rapid resource changes. As a result, the workload management in a virtualized environment becomes a complex task. In this paper we propose a new proactive workload management model for virtualized resources to inspect the workload behavior of the running Virtual Machines, and to assent an appropriate scheduling and resource consolidation schema in order to improve the system efficiency, utilization, and throughput. We have carried out our model by modifying Xen Cloud Platform, then we tested the model performance through different representative benchmarks. The results show that the Proactive model can decrease the average response time remarkably.     

Living in a big data world: Predicting mobile commerce activity through privacy concerns

As advertisers increasingly rely on mobile-based data, consumer perceptions regarding the collection and use of such data becomes of great interest to scholars and practitioners. Recent industry data suggests advertisers seeking to leverage personal data offered via mobile devices would be wise to acknowledge and address the privacy concerns held by mobile users. Utilizing the theoretical foundation of communication privacy management (CPM), the current study investigates commonly understood privacy concerns such as collection, control, awareness, unauthorized secondary use, improper access and a newly adapted dimension of location tracking, trust in mobile advertisers, and attitudes toward mobile commerce, to predict mobile commerce engagement. Data from this study indicate that control, unauthorized access, trust in mobile advertisers, and attitude toward mobile commerce significantly predicted 43% of the variance in mobile commerce activity.     

Two-wheeled mobile robot motion control in dynamic environments

In this paper, a feedback control scheme of a two-wheeled mobile robot is explored in dynamic environments. In the existence of local minima, the design of controller is based on Lyapunov function candidate and considers virtual forces information including detouring force. Simulation results are presented to show the effectiveness of the proposed control scheme.     

The expressive task specification and adaptive image data handling for mobile applications

An efficient multimedia data handling is a fundamental requirement of mobile multimedia applications. To accommodate this requirement, issues of the available technologies as well as mobile multimedia data access and transfer processes, and the characteristics of the medium to be handled should all be taken into consideration. For this end, these aspects are investigated. The results of the investigation lead to the conclusion that an expressive task specification and adaptive multimedia data handling should be provided. With an expressive task specification, a demand for accessing multimedia object can be described flexibly to enable a minimum handling overhead (thus high performance) and an optimal compromise between performance, cost and quality. Adaptive media handling functionality adapts the service performance according to the medium to be accessed, the available resources and compromise preference of a mobile client, etc. This paper presents the new concepts and methods for these two aspects.     

Data management issues in mobile and peer-to-peer environments

Mobile computing is a revolutionary technology, born as a result of remarkable advance in the development of computer hardware and wireless communication. It enables us to access information anytime and anywhere even in the absence of physical network connection. More recently, there has been increasing interest in introducing ad hoc network into mobile computing, resulting in a new distributed computing style known as peer-to-peer (P2P) computing. In this paper, we discuss the data management issues in mobile and P2P environments. The use of wireless communication makes the data availability the most important problem here, so we focus on the problem of data availability and provide detailed discussion about replicating mobile databases. Not only that, we extend our discussion to mobile–P2P environment. At the end, we discuss the general data management issues in P2P environment.     

Movement-based checkpointing and logging for failure recovery of database applications in mobile environments

In this paper, we present an efficient failure recovery scheme for mobile database applications based on movement-based checkpointing and logging. Current approaches take checkpoints periodically without regard to the mobility behavior of mobile users. Our movement-based checkpointing scheme takes a checkpoint only after a threshold of mobility handoffs has been exceeded. The optimal threshold is governed by the failure rate, log arrival rate, and the mobility rate of the mobile host. This allows the tuning of the checkpointing rate on a per-user basis. We identify the optimal movement threshold which will minimize the recovery cost per failure as a function of the mobile node’s mobility rate, failure rate and log arrival rate. We derive the mobile database application recoverability, i.e., the probability that the recovery can be done by a specified recovery time deadline. Numeric data are presented to demonstrate the feasibility of our approach with its applicability given.     

Adaptive per-user per-object cache consistency management for mobile data access in wireless mesh networks

We propose and analyze an adaptive per-user per-object cache consistency management (APPCCM) scheme for mobile data access in wireless mesh networks. APPCCM supports strong data consistency semantics through integrated cache consistency and mobility management. The objective of APPCCM is to minimize the overall network cost incurred due to data query/update processing, cache consistency management, and mobility management. In APPCCM, data objects can be adaptively cached at the mesh clients directly or at mesh routers dynamically selected by APPCCM. APPCCM is adaptive, per-user and per-object as the decision regarding where to cache a data object accessed by a mesh client is made dynamically, depending on the mesh client’s mobility and data query/update characteristics, and the network’s conditions. We develop analytical models for evaluating the performance of APPCCM and devise a computational procedure for dynamically calculating the overall network cost incurred. We demonstrate via both model-based analysis and simulation validation that APPCCM outperforms non-adaptive cache consistency management schemes that always cache data objects at the mesh client, or at the mesh client’s current serving mesh router for mobile data access in wireless mesh networks.     

The DYNAMOS approach to support context-aware service provisioning in mobile environments

To efficiently make use of information and services available in ubiquitous environments, mobile users need novel means for locating relevant content, where relevance has a user-specific definition. In the DYNAMOS project, we have investigated a hybrid approach that enhances context-aware service provisioning with peer-to-peer social functionalities. We have designed and implemented a system platform and application prototype running on smart phones to support this novel conception of service provisioning. To assess the feasibility of our approach in a real-world scenario, we conducted field trials in which the research subject was a community of recreational boaters.     

Autonomic tracing of production processes with mobile and agent-based computing

Tracing items in a supply chain, across different enterprises and through the full processes scope, is today an inherently complex design task. Enterprises are typically comprised of hundreds of applications that are custom built at different times, acquired from third parties and parts of legacy systems, and also operating in multiple tiers of different manufacturing and information system platforms. Further, traceability is characterized by a goal-oriented approach, in which business-process analyses are driven by goal achievements rather than by systematic engineering processes. The use of a classical enterprise integration approach mostly needs tailoring to different applications. Due to the number and diversity of the systems and of their interactions, and to their dynamicity, it is difficult, costly, and therefore often not convenient to develop in large scale distributed systems.To overcome these issues, a supply chain traceability system with a high level of automation is discussed in this paper. In particular, the system adopts an agent-based approach, in which cooperative software agents find solutions to back-end tracing problems by self-organization. Such cooperative agents are based on a business process aware traceability model, and on a service-oriented composition paradigm. Furthermore, an interface agent assists each user to carry out the front-end tracking activities. Interface agents rely on the context-awareness paradigm to gain self-configurability and self-adaptation of the user interface, and on ubiquitous computing technology, i.e., mobile devices and radio-frequency identification, to perform agile and automatic lot identification. The paper comprises real-world experiences on the fashion supply chain.     

大数据在机场综合管理数据库建设中的应用研究

把数据仓库、数据挖掘和可视化等大数据研究的关键技术应用到机场综合管理数据库建设中。利用数据仓库、数据挖掘和可视化等大数据研究的关键技术,实现机场在建设综合管理数据库过程中,各类型海量数据处理、数据仓库建设、数据的分析及价值发现。进而为机场建设综合管理数据库提供了设计方案。     

Evolutionary rule-based systems for imbalanced data sets

This paper investigates the capabilities of evolutionary on-line rule-based systems, also called learning classifier systems (LCSs), for extracting knowledge from imbalanced data. While some learners may suffer from class imbalances and instances sparsely distributed around the feature space, we show that LCSs are flexible methods that can be adapted to detect such cases and find suitable models. Results on artificial data sets specifically designed for testing the capabilities of LCSs in imbalanced data show that LCSs are able to extract knowledge from highly imbalanced domains. When LCSs are used with real-world problems, they demonstrate to be one of the most robust methods compared with instance-based learners, decision trees, and support vector machines. Moreover, all the learners benefit from re-sampling techniques. Although there is not a re-sampling technique that performs best in all data sets and for all learners, those based in over-sampling seem to perform better on average. The paper adapts and analyzes LCSs for challenging imbalanced data sets and establishes the bases for further studying the combination of re-sampling technique and learner best suited to a specific kind of problem.     

Building a validation measure for activity-based transportation models based on mobile phone data

Activity-based micro-simulation transportation models typically predict 24-h activity-travel sequences for each individual in a study area. These sequences serve as a key input for travel demand analysis and forecasting in the region. However, despite their importance, the lack of a reliable benchmark to evaluate the generated sequences has hampered further development and application of the models. With the wide deployment of mobile phone devices today, we explore the possibility of using the travel behavioral information derived from mobile phone data to build such a validation measure.Our investigation consists of three steps. First, the daily trajectory of locations, where a user performed activities, is constructed from the mobile phone records. To account for the discrepancy between the stops revealed by the call data and the real location traces that the user has made, the daily trajectories are then transformed into actual travel sequences. Finally, all the derived sequences are classified into typical activity-travel patterns which, in combination with their relative frequencies, define an activity-travel profile. The established profile characterizes the current activity-travel behavior in the study area, and can thus be used as a benchmark for the assessment of the activity-based transportation models.By comparing the activity-travel profiles derived from the call data with statistics that stem from traditional activity-travel surveys, the validation potential is demonstrated. In addition, a sensitivity analysis is carried out to assess how the results are affected by the different parameter settings defined in the profiling process.     

Multi-layer faults in the architectures of mobile, context-aware adaptive applications

Modern hand-held devices are equipped with multiple context sensors exploited by increasingly sophisticated software applications, called Context-Aware Adaptive Applications (CAAAs), that adapt automatically to changes in the surrounding environment, such as by responding to the location and speed of the user. The architecture of CAAAs is typically layered and incorporates a context-awareness component to support processing of context values and triggering of adaptive changes. While this layered architecture is very natural for the design and implementation of CAAAs, it exhibits new kinds of failures that arise as a result of faults that are specific to the choice of technology for specific layers. In this paper we investigate the occurrence of such faults and failures that manifest across architectural layers, and we describe samples of such failures in four CAAAs.     

A concurrency control scheme for mobile transactions in broadcast disk environments

Broadcast disk technique has been often used to disseminate frequently requested data efficiently to a large volume of mobile clients over wireless channels. In broadcast disk environments, a server often broadcasts different data items with differing frequencies to reflect the skewed data access patterns of mobile clients. Previously proposed concurrency control methods for mobile transactions in wireless broadcast environments are focused on the mobile transactions with uniform data access patterns. These protocols perform poorly in broadcast disk environments where the data access patterns of mobile transactions are skewed. In broadcast disk environments, the time length of a broadcast cycle usually becomes large to reflect the skewed data access patterns. This will often cause read-only transactions to access old data items rather than the latest data items. Furthermore, updating mobile transactions will be frequently aborted and restarted in the final validation stage due to the update conflict of the same data items with high access frequencies. This problem will increase the average response time of the update mobile transactions and waste the uplink communication bandwidth. In this paper, we extend the existing FBOCC concurrency control method to efficiently handle mobile transactions with skewed data access patterns in broadcast disk environments. Our method allows read-only transactions to access the more updated data, and reduces the average response time of updating transactions through early aborts and restarts. Our method also reduces the amount of uplink communication bandwidth for the final validation of the update transactions. We present an in-depth experimental analysis of our method by comparing with existing concurrency control protocols. Our performance analysis shows that it significantly decreases the average response time and the amount of uplink bandwidths over existing methods.