The development of low-carbon power systems has not only elevated the investment costs enterprises, but also generated a vast amount electricity data. data trading holds promising potential as primary means to cover costs. However, there is lack research on trading. To address this issue, article designs an method based price game and blockchain for systems. It encompasses framework corresponding mechanism. proposed contains providers, consumers, blockchain-based information system that...

The dynamic gas flow model with static electric-driven compressor (EDC) has been widely studied in coordinated analysis of integrated electricity-gas system (IEGS). However, as a crucial coupling unit, the boost characteristics EDC change dynamically state, which may lead to unstable operation mode and then affect safe operating IEGS. Meanwhile, its nonlinear greatly increases difficulty analysis. This paper proposes reduced-order transfer function that considers EDCs for an accurate...

Multidimensional database technology is a key factor in the interactive analysis of large amounts data for decision making purposes. In contrast to previous technologies, these databases view as multidimensional cubes that are particularly well suited analysis. models categorize either facts with associated numerical measures or textual dimensions characterize facts. Queries aggregate measure values over range dimension provide results such total sales per month given product. being applied...

Online Analytical Processing (OLAP) systems considerably ease the process of analyzing business data and have become widely used in industry. Such primarily employ multidimensional models to structure their data. However current fall short abilities model complex found some real world application domains. The paper presents nine requirements models, each which is exemplified by a world, clinical case study. A survey existing reveals that not currently met include support for many-to-many...

With wireless communications and geo-positioning being widely available, it becomes possible to offer new e-services that provide mobile users with information about other objects. This paper concerns active, ordered k-nearest neighbor queries for query data objects are moving in road networks. Such may be of use many services.Specifically, we present an easily implementable model serves well as a foundation such queries. We also the design prototype system implements based on model. The...

This paper surveys the most relevant research on combining Data Warehouse (DW) and Web data. It studies XML technologies that are currently being used to integrate, store, query retrieve web data, their application DWs. The reviews different DW distributed architectures use of languages as an integration tool in these systems. also introduces problem dealing with semi-structured data a DW. repositories, design multidimensional databases for sources extensions On-Line Analytical Processing...

This paper describes the convergence of some most influential technologies in last few years, namely data warehousing (DW), on-line analytical processing (OLAP), and Semantic Web (SW). OLAP is used by enterprises to derive important business-critical knowledge from inside company. However, interesting queries can no longer be answered on internal alone, external must also discovered (most often web), acquired, integrated, (analytically) queried, resulting a new type OLAP, exploratory OLAP....

Self-service business intelligence is about enabling non-expert users to make well-informed decisions by enriching the decision process with situational data, i.e., data that have a narrow focus on specific problem and, typically, short lifespan for small group of users. Often, these are not owned and controlled maker; their search, extraction, integration, storage reuse or sharing should be accomplished makers without any intervention designers programmers. The goal this paper present...

Widespread use of advanced mobile devices has led to the emergence a new class crowdsourcing called spatial crowdsourcing. Spatial advances potential crowd perform tasks related real-world scenarios involving physical locations, which were not feasible with conventional methods. The main feature is presence that require workers be physically present at particular location for task fulfillment. Research this paradigm gained momentum in recent years, necessitating comprehensive survey offer...

Age of Information (AoI) has become an important concept in communications, as it allows system designers to measure the freshness information available remote monitoring or control processes. However, its definition tacitly assumes that new is used at any time, which not always case: instants collected and may be dependent on a certain query process, resource-constrained environments such most Internet Things (IoT) use cases require precise timing fully exploit limited transmissions. In...

The widespread deployment of smartphones, net-worked in-vehicle devices with geo-positioning capabilities, and vessel tracking technologies renders it feasible to collect the evolving geo-locations populations land- sea-based moving objects. continuous clustering such data can enable a variety real-time services, as road traffic management collision risk assessment. However, little attention has so far been given quality moving-object clusters-for example, is beneficial smooth short-term...

Compressed bitmap indexes are increasingly used for efficiently querying very large and complex databases. The Word Aligned Hybrid (WAH) compression scheme is commonly recognized as the most efficient in terms of CPU efficiency. However, WAH compressed bitmaps use a lot storage space. This paper presents Position List (PLWAH) that improves significantly over by better utilizing available bits new instructions. For typical bit distributions, PLWAH often half size and, at same time, offer an...

The collection of time series data increases as more monitoring and automation are being deployed. These deployments range in scale from an Internet things (IoT) device located a household to enormous distributed Cyber-Physical Systems (CPSs) producing large volumes at high velocity. To store analyze these vast amounts data, specialized Time Series Management (TSMSs) have been developed overcome the limitations general purpose Database (DBMSs) for times management. In this paper, we present...

Massive volumes of uncertain trajectory data are being generated by GPS devices. Due to the limitations data, these trajectories generally uncertain. This state affairs renders it is attractive be able compress and query efficiently without need for (full) decompression. Unlike existing studies that target accurate trajectories, we propose a framework accommodates in road networks. To address large cardinality instances single trajectory, exploit similarity between provide referential...

The widespread diffusion of smartphones offers a capable foundation for the deployment Spatial Crowdsourcing (SC), where mobile users, called workers, perform location- dependent tasks assigned to them. A key issue in SC is how best assign tasks, e.g., delivery food and packages, appropriate workers. Specifically, we study problem Fairness-aware Task Assignment (FTA) SC, are be manner that achieves some notion fairness across In particular, aim minimize payoff difference among workers while...

The deployment of vehicle location services generates increasingly massive trajectory data, which incurs high storage and transmission costs. A range studies target offline compression to reduce the cost. However, enable online such as real-time traffic monitoring, it is attractive also costs by being able compress streaming trajectories in real-time. Hence, we propose a framework called TRACE that enables compression, transmission, querying network-constrained fully fashion. We compact...

Big time series are increasingly available from an ever wider range of IoT-enabled sensors deployed in various environments. Significant insights can be gained by mining temporal patterns these series. Temporal pattern (TPM) extends traditional adding event intervals into extracted patterns, making them more expressive at the expense increased and space complexities. Besides frequent (FTPs), which occur frequently entire dataset, another useful type so-called <italic...

Time series data from a variety of sensors and IoT devices need effective compression to reduce storage I/O bandwidth requirements. While most time databases systems rely on lossless compression, lossy techniques offer even greater space-saving with small loss in precision. However, the unknown impact downstream analytics applications requires semi-manual trial-and-error exploration. We initiate work that provides guarantees complex statistical features (which are strongly correlated...

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