面向情景感知计算的时空数据管理、查询、分析与相关算法研究
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摘要
情景感知计算：情景感知计算作为一种新的计算形态,与普适计算、移动计算和智能计算密切相关。由于普适计算、协同计算、计算智能化和虚拟现实等前沿研究方向都可以归为情景感知计算,这使得情景感知计算具有广阔的研究前景与应用领域,成为了未来发展的重要方向。随着传感网、物联网、嵌入式系统、通信网络、分布式计算和移动计算等技术的发展,情景感知计算受到国内外专家学者和业界的广泛关注。与此同时,越来越多的情景感知应用也被开发出来。情景感知计算通过赋予系统感知周围环境的能力,来优化系统内部(调整自身行为、优化资源利用),简化用户与系统的交互,提升用户体验,使系统变得更加易用、智能和友好。
情景信息与时空数据的契合：情景感知应用产生和积累了海量、动态、异构、无规律、分布在系统各处的情景信息。时空数据研究的最终目的是回答：“在何时(When)、何地(Where)、时空对象(Who或What)发生了什么样的变化(What)以及如何变化的(How)”,这与情景感知计算研究中的4W(Who、When、Where和What)非常契合。因此可以从时空特性角度,通过借鉴时空数据已有成果,来研究情景感知应用中的海量数据。
情景信息生命周期：从情景信息生命周期角度来说,情景感知计算主要涉及情景信息的采集、管理和使用三个主要部分。情景信息的采集主要是通过用户界面分析/日志分析/数据语义分析或者传感器感知等方法。情景信息的管理主要包括情景的存储和处理两部分：(1)情景信息的存储是指根据情景信息的特征采取合适的表示方式来存储数据,并通过索引来保证有效的访问；(2)情景信息处理是通过将智能信息处理技术融入情景感知计算中,来获得更加准确、高级的情景信息。情景信息的使用则主要包括查询、分析等。本文深入研究面向情景感知计算的时空数据管理、查询、分析和相关算法,以期这些研究成果能对情景感知技术最终的推广起到重要的作用。
研究内容：虽然情景感知计算和时空数据的研究已经取得一定成果,然而情景信息采集设备的数量和种类的越来越多,对用户隐私保护的越来越重视,对查询性能要求的越来越高,新的应用场景的引入,以及更深入智能洞察的需求,对本文的研究内容提出了更高的要求。本文主要对以下六个方面的内容进行了研究和讨论：
(1)对情景感知计算和时空数据的研究现状进行了分析,简要回顾了情景感知计算和时空数据研究的发展过程,并详细分析了当前研究中存在的问题。(第1章)
(2)对情景感知计算框架进行了研究,以达到有效地采集情景信息、屏蔽情景数据源的异构性、提高系统的可扩展性、保护用户隐私等目的。并以原型系统实现的方式验证了所提出OWS-MA框架(Open Web Service based Multi-Agent framework)的特性,该原型系统也用于实现、验证和展示后续提出的技术。(第2章)
(3)通过分析情景感知应用中海量数据的时空特性,利用时态数据库、空间数据库、关系数据库和No SQL数据库技术,设计了适合情景感知应用的数据存储方案。并结合情景感知应用对时空查询种类的需求,提出了HSTI (Hybrid Spatial-Temporal Index)时空索引,提升了查询性能。(第3章)
(4)由于存在多种位置采集策略,因此需要对于采集到的原始时空轨迹进行正确处理,以提高数据准确性。本文以时空轨迹匹配算法为例对时空数据处理进行了研究,所提出的DTW算法(a Dynamic Time Warping based algorithm for trajectory matching)能够有效地减弱多种位置采集策略的影响,提高数据准确性。(第4章)
(5)源于情景感知计算中对群组集结点的实际需求,本文对群组最近邻查询进行了研究,针对查询对象移动、有障碍阻挡、位置信息不确定和隐私保护等新的应用场景,提出了基于区域的概率群组最近邻查询算法,并通过实验验证了所提出算法的有效性、高效性和可扩展性。(第5章)
(6)对于特定应用领域(本文选择公共卫生领域-上海地区主要气象相关疾病预报服务)中的海量信息,通过分析多种情景信息之间关系,来发现其中蕴含的规律和知识。在这个应用实例中,在时间特性和空间特性之外,还考虑了气象因素和环境因素,定量地确定了气象因素与蚊虫密度、蚊虫活性之间关系。并通过具体应用实现和验证了本文所提出的情景感知计算框架和数据存储方案,以及在时空数据存储、处理、查询、分析方面提出的技术。(第6章)
其中,每章研究工作的侧重点各不相同。第4章的时空轨迹研究侧重于讨论时间特性；第5章的时空查询算法侧重于讨论空间特性；第6章多情景数据分析中,在时间特性和空间特性之外,还考虑了气象因素和环境因素。
主要创新点概括如下：
(1)提出了OWS-MA情景感知计算框架,并通过原型系统实现的方式验证了所提出框架的特性。
(2)设计了适合情景感知应用的数据存储方案,并通过所提出的HSTI索引技术提升了查询性能。
(3)提出了基于DTW的时空轨迹匹配算法,并通过实验验证了算法的有效性,同时与IMHD和OWD算法相比,还增加了对时间顺序敏感、以及允许对时间维度进行一定程度放缩的特性。
(4)提出了基于区域的概率群组最近邻查询算法,并通过实验验证了所提出查询算法的有效性,同时与PSPM和PMPM方法相比,降低了计算复杂度,提高了查询处理速度,并具有更好的可扩展性。
(5)以公共卫生领域应用(虫媒传染病预防控制)为实例,将时空应用扩展到多属性的综合情景数据分析。通过深入地分析多种情景信息之间关系,定量地确定了气象因素与蚊虫密度、蚊虫活性之间的关系。并验证了本文所提出的情景感知计算框架和数据存储方案,以及在时空数据处理、查询和分析方面提出的技术。验证了本文中多属性综合情景数据分析的可行性与有效性。对该应用领域的信息化而言,也是首次重大突破。
Context Aware Computing:As a new computing form, context aware computing is closely related to pervasive computing, mobile computing and intelligent computing. Generally speaking, research frontiers such as pervasive computing, collaborative computing, intelligent computing and virtual reality are all context aware. This makes context aware computing a promising research area with vast applied prospects. With the developments of the Internet of things, sensor network, embedded system, communication network, distributed and mobile computing, context aware computing has drawn much attention from researchers both domestic and abroad. Meanwhile, more and more context aware applications have been developed. Through endowing the system the ability of sensing its surrounding environment, context aware computing optimizes the whole system (adjusting self behaviors, improving resource utilities), simplifies the interactions between the system and its users, improves users'experiences, makes the system intelligent, easy to use and user friendly.
Context and spatial-temporal data:A huge amount of dynamic, heterogeneous, erratic and distributed data is generated and accumulated in context aware applications. Since time and space are the two basic components of these data, the achievements on spatial temporal data can be used in the research of these data. The researches on spatial temporal data aims to answer questions like "What has happened on it (him)? When, where and how does it happen?" These are quite similar with the4W (Who, When, Where and What) in context aware computing. Based on this reason, the researches on the huge amounts of data in context aware applications can be conducted from the spatial temporal characteristic perspective and combing the achievements on spatial temporal data research.
The life circle of context:From the perspective of context life circle, context aware computing mainly involves context acquirement, management and usage. The context is acquired through analyzing user interfaces, logs, data semantic, physical and logic sensors. Storage and processing are the main parts of context management. In context storage, proper methods are used in representing, storing and indexing context. The integration of intelligent information processing technology and context aware computing provides more accurate and higher level information. Context usage is consisted of context query, analysis and etc. In this paper, researches on context awareness oriented spatial temporal data management, query processing, analysis and the related algorithms are conducted. The achievements will largely effect the application of context aware computing.
Research scope:Although some progresses have been made on context aware computing and spatial temporal data, the new emerging context sensing devices, the emphasizing of user privacy, the higher requirement on query performance, and new emerging application scenarios make context aware computing a more challenging task. The research contents are summarized as follows:
(1) The research statuses of context aware computing and spatial temporal data are surveyed. And through reviewing the history of context aware computing and spatial temporal data, existing problems are elaborated.(Chapter One)
(2) Researches on context aware framework are conducted for effective acquiring contexts, masking heterogeneous data sources, improving the scalability, and protecting users'privacy. A prototype system is implemented to validate the proposed framework, it is also used in the implementations, validations and exhibitions of subsequent proposed methods.(Chapter Two)
(3) Through the analysis of the characteristics of spatial temporal data, and the combination of existing achievements on temporal, spatial, relational and No SQL databases, a spatial temporal data management solution for context aware applications is designed. Based on the query requirements analysis of context aware applications, a spatial temporal index for context aware computing is proposed and validated to improve the query performance.(Chapter Three)
(4) Since multiple location update strategies are existed, the sampled trajectories of one single object are not identical. A matching algorithm is required to distinguish the different samples of one trajectory from another trajectory. A dynamic time warping based trajectory matching algorithm is proposed. The proposed method can effectively attenuate the side effect of various location update strategies and improve date accuracy.(Chapter Four)
(5) Since the rendezvous is a basic requirement in context aware computing, a thorough study of Group Nearest Neighbor query (GNN) is conducted. For emerging application scenarios, the Range based Probabilistic Group Nearest Neighbor query (RP-GNN) algorithm is proposed. Extensive experiments are conducted to validate the effectiveness, efficiency and scalability of the algorithm.(Chapter Five)
(6) For the huge amount of data in some specified application domain (Such as public health. In this paper, searches are conducted based on the reasch project named Prediction System of Meteorology Related Diseases for Shanghai), analysis are conducted on the relationship among multiple context factors to discover the pattern and knowledge implied in the huge amount of data. Besides spatial and temporal characteristics, meteorological and environmental factors are also considered. The relationship between meteorological factors and mosquito density&activity is quantified. Meanwhile, the proposed context aware framework, data storage solution and methods on data acquiring, storing, processing and analysis are implemented and validated.(Chapter Six)
The major contributions of our researches are summarized as follows:
(1) The OWS-MA context aware framework is proposed and validated through the implementation of associated prototype system.
(2) The design of data storage solution as well as the query performance improvement through the proposed HSTI spatial temporal index.
(3) The Dynamic Time Warping base trajectory matching algorithm (DTW) is proposed. Its efficiency is validated through extensive experiments. Comparing with IMHD and OWD, DTW is also time sequence sensitive and time scaling tolerating.
(4) The Range based Probabilistic Group Nearest Neighbor query (RP-GNN) algorithm is proposed. Its efficiency is validated through extensive experiments. RP-GNN reduces the computation complexity, speeds up the query processing, and acquires a better scalability.
(5) The specific application (mosquito-borne infectious diseases prevention and control) is taken as a case study to extend the spatial temporal application into a multivariate data analysis. Through the comprehensive analysis of the relationship among multiple context factors, the relationship between meteorological factors and mosquito density&activity is quantified. Meanwhile, the proposed context aware framework, data storage solution and methods on data acquiring, storing, processing, and analysis are implemented and validated. The extension of spatial temporal application into a multivariate data analysis is feasible and effective. It is also an informatization breakthrough for mosquito-borne infectious diseases prevention and control
情景信息与时空数据的契合：情景感知应用产生和积累了海量、动态、异构、无规律、分布在系统各处的情景信息。时空数据研究的最终目的是回答：“在何时(When)、何地(Where)、时空对象(Who或What)发生了什么样的变化(What)以及如何变化的(How)”,这与情景感知计算研究中的4W(Who、When、Where和What)非常契合。因此可以从时空特性角度,通过借鉴时空数据已有成果,来研究情景感知应用中的海量数据。
情景信息生命周期：从情景信息生命周期角度来说,情景感知计算主要涉及情景信息的采集、管理和使用三个主要部分。情景信息的采集主要是通过用户界面分析/日志分析/数据语义分析或者传感器感知等方法。情景信息的管理主要包括情景的存储和处理两部分：(1)情景信息的存储是指根据情景信息的特征采取合适的表示方式来存储数据,并通过索引来保证有效的访问；(2)情景信息处理是通过将智能信息处理技术融入情景感知计算中,来获得更加准确、高级的情景信息。情景信息的使用则主要包括查询、分析等。本文深入研究面向情景感知计算的时空数据管理、查询、分析和相关算法,以期这些研究成果能对情景感知技术最终的推广起到重要的作用。
研究内容：虽然情景感知计算和时空数据的研究已经取得一定成果,然而情景信息采集设备的数量和种类的越来越多,对用户隐私保护的越来越重视,对查询性能要求的越来越高,新的应用场景的引入,以及更深入智能洞察的需求,对本文的研究内容提出了更高的要求。本文主要对以下六个方面的内容进行了研究和讨论：
(1)对情景感知计算和时空数据的研究现状进行了分析,简要回顾了情景感知计算和时空数据研究的发展过程,并详细分析了当前研究中存在的问题。(第1章)
(2)对情景感知计算框架进行了研究,以达到有效地采集情景信息、屏蔽情景数据源的异构性、提高系统的可扩展性、保护用户隐私等目的。并以原型系统实现的方式验证了所提出OWS-MA框架(Open Web Service based Multi-Agent framework)的特性,该原型系统也用于实现、验证和展示后续提出的技术。(第2章)
(3)通过分析情景感知应用中海量数据的时空特性,利用时态数据库、空间数据库、关系数据库和No SQL数据库技术,设计了适合情景感知应用的数据存储方案。并结合情景感知应用对时空查询种类的需求,提出了HSTI (Hybrid Spatial-Temporal Index)时空索引,提升了查询性能。(第3章)
(4)由于存在多种位置采集策略,因此需要对于采集到的原始时空轨迹进行正确处理,以提高数据准确性。本文以时空轨迹匹配算法为例对时空数据处理进行了研究,所提出的DTW算法(a Dynamic Time Warping based algorithm for trajectory matching)能够有效地减弱多种位置采集策略的影响,提高数据准确性。(第4章)
(5)源于情景感知计算中对群组集结点的实际需求,本文对群组最近邻查询进行了研究,针对查询对象移动、有障碍阻挡、位置信息不确定和隐私保护等新的应用场景,提出了基于区域的概率群组最近邻查询算法,并通过实验验证了所提出算法的有效性、高效性和可扩展性。(第5章)
(6)对于特定应用领域(本文选择公共卫生领域-上海地区主要气象相关疾病预报服务)中的海量信息,通过分析多种情景信息之间关系,来发现其中蕴含的规律和知识。在这个应用实例中,在时间特性和空间特性之外,还考虑了气象因素和环境因素,定量地确定了气象因素与蚊虫密度、蚊虫活性之间关系。并通过具体应用实现和验证了本文所提出的情景感知计算框架和数据存储方案,以及在时空数据存储、处理、查询、分析方面提出的技术。(第6章)
其中,每章研究工作的侧重点各不相同。第4章的时空轨迹研究侧重于讨论时间特性；第5章的时空查询算法侧重于讨论空间特性；第6章多情景数据分析中,在时间特性和空间特性之外,还考虑了气象因素和环境因素。
主要创新点概括如下：
(1)提出了OWS-MA情景感知计算框架,并通过原型系统实现的方式验证了所提出框架的特性。
(2)设计了适合情景感知应用的数据存储方案,并通过所提出的HSTI索引技术提升了查询性能。
(3)提出了基于DTW的时空轨迹匹配算法,并通过实验验证了算法的有效性,同时与IMHD和OWD算法相比,还增加了对时间顺序敏感、以及允许对时间维度进行一定程度放缩的特性。
(4)提出了基于区域的概率群组最近邻查询算法,并通过实验验证了所提出查询算法的有效性,同时与PSPM和PMPM方法相比,降低了计算复杂度,提高了查询处理速度,并具有更好的可扩展性。
(5)以公共卫生领域应用(虫媒传染病预防控制)为实例,将时空应用扩展到多属性的综合情景数据分析。通过深入地分析多种情景信息之间关系,定量地确定了气象因素与蚊虫密度、蚊虫活性之间的关系。并验证了本文所提出的情景感知计算框架和数据存储方案,以及在时空数据处理、查询和分析方面提出的技术。验证了本文中多属性综合情景数据分析的可行性与有效性。对该应用领域的信息化而言,也是首次重大突破。
Context Aware Computing:As a new computing form, context aware computing is closely related to pervasive computing, mobile computing and intelligent computing. Generally speaking, research frontiers such as pervasive computing, collaborative computing, intelligent computing and virtual reality are all context aware. This makes context aware computing a promising research area with vast applied prospects. With the developments of the Internet of things, sensor network, embedded system, communication network, distributed and mobile computing, context aware computing has drawn much attention from researchers both domestic and abroad. Meanwhile, more and more context aware applications have been developed. Through endowing the system the ability of sensing its surrounding environment, context aware computing optimizes the whole system (adjusting self behaviors, improving resource utilities), simplifies the interactions between the system and its users, improves users'experiences, makes the system intelligent, easy to use and user friendly.
Context and spatial-temporal data:A huge amount of dynamic, heterogeneous, erratic and distributed data is generated and accumulated in context aware applications. Since time and space are the two basic components of these data, the achievements on spatial temporal data can be used in the research of these data. The researches on spatial temporal data aims to answer questions like "What has happened on it (him)? When, where and how does it happen?" These are quite similar with the4W (Who, When, Where and What) in context aware computing. Based on this reason, the researches on the huge amounts of data in context aware applications can be conducted from the spatial temporal characteristic perspective and combing the achievements on spatial temporal data research.
The life circle of context:From the perspective of context life circle, context aware computing mainly involves context acquirement, management and usage. The context is acquired through analyzing user interfaces, logs, data semantic, physical and logic sensors. Storage and processing are the main parts of context management. In context storage, proper methods are used in representing, storing and indexing context. The integration of intelligent information processing technology and context aware computing provides more accurate and higher level information. Context usage is consisted of context query, analysis and etc. In this paper, researches on context awareness oriented spatial temporal data management, query processing, analysis and the related algorithms are conducted. The achievements will largely effect the application of context aware computing.
Research scope:Although some progresses have been made on context aware computing and spatial temporal data, the new emerging context sensing devices, the emphasizing of user privacy, the higher requirement on query performance, and new emerging application scenarios make context aware computing a more challenging task. The research contents are summarized as follows:
(1) The research statuses of context aware computing and spatial temporal data are surveyed. And through reviewing the history of context aware computing and spatial temporal data, existing problems are elaborated.(Chapter One)
(2) Researches on context aware framework are conducted for effective acquiring contexts, masking heterogeneous data sources, improving the scalability, and protecting users'privacy. A prototype system is implemented to validate the proposed framework, it is also used in the implementations, validations and exhibitions of subsequent proposed methods.(Chapter Two)
(3) Through the analysis of the characteristics of spatial temporal data, and the combination of existing achievements on temporal, spatial, relational and No SQL databases, a spatial temporal data management solution for context aware applications is designed. Based on the query requirements analysis of context aware applications, a spatial temporal index for context aware computing is proposed and validated to improve the query performance.(Chapter Three)
(4) Since multiple location update strategies are existed, the sampled trajectories of one single object are not identical. A matching algorithm is required to distinguish the different samples of one trajectory from another trajectory. A dynamic time warping based trajectory matching algorithm is proposed. The proposed method can effectively attenuate the side effect of various location update strategies and improve date accuracy.(Chapter Four)
(5) Since the rendezvous is a basic requirement in context aware computing, a thorough study of Group Nearest Neighbor query (GNN) is conducted. For emerging application scenarios, the Range based Probabilistic Group Nearest Neighbor query (RP-GNN) algorithm is proposed. Extensive experiments are conducted to validate the effectiveness, efficiency and scalability of the algorithm.(Chapter Five)
(6) For the huge amount of data in some specified application domain (Such as public health. In this paper, searches are conducted based on the reasch project named Prediction System of Meteorology Related Diseases for Shanghai), analysis are conducted on the relationship among multiple context factors to discover the pattern and knowledge implied in the huge amount of data. Besides spatial and temporal characteristics, meteorological and environmental factors are also considered. The relationship between meteorological factors and mosquito density&activity is quantified. Meanwhile, the proposed context aware framework, data storage solution and methods on data acquiring, storing, processing and analysis are implemented and validated.(Chapter Six)
The major contributions of our researches are summarized as follows:
(1) The OWS-MA context aware framework is proposed and validated through the implementation of associated prototype system.
(2) The design of data storage solution as well as the query performance improvement through the proposed HSTI spatial temporal index.
(3) The Dynamic Time Warping base trajectory matching algorithm (DTW) is proposed. Its efficiency is validated through extensive experiments. Comparing with IMHD and OWD, DTW is also time sequence sensitive and time scaling tolerating.
(4) The Range based Probabilistic Group Nearest Neighbor query (RP-GNN) algorithm is proposed. Its efficiency is validated through extensive experiments. RP-GNN reduces the computation complexity, speeds up the query processing, and acquires a better scalability.
(5) The specific application (mosquito-borne infectious diseases prevention and control) is taken as a case study to extend the spatial temporal application into a multivariate data analysis. Through the comprehensive analysis of the relationship among multiple context factors, the relationship between meteorological factors and mosquito density&activity is quantified. Meanwhile, the proposed context aware framework, data storage solution and methods on data acquiring, storing, processing, and analysis are implemented and validated. The extension of spatial temporal application into a multivariate data analysis is feasible and effective. It is also an informatization breakthrough for mosquito-borne infectious diseases prevention and control
引文
[1]顾君忠.情景感知计算[J].华东师范大学学报(自然科学版),2009,(5)：1-20.
[2]DEY A K. Providing Architectural Support for Building Context-aware Applications [D]. Atlanta:Georgia Institute of Technology,2000. PHD Dissertation.
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