Managing Uncertain Complex Events in Web of Things Applications

Abstract

A critical issue in the Web of Things (WoT) is the need to process and analyze the interactions of Web-interconnected real-world objects. Complex Event Processing (CEP) is a powerful technology for analyzing streams of information about real-time distributed events, coming from different sources, and for extracting conclusions from them. However, in many situations these events are not free from uncertainty, due to either unreliable data sources and networks, measurement uncertainty, or to the inability to determine whether an event has actually happened or not. This short research paper discusses how CEP systems can incorporate different kinds of uncertainty, both in the events and in the rules. A case study is used to validate the proposal, and we discuss the benefits and limitations of this CEP extension.

Multi-dimensional Probabilistic Regression over Imprecise Data Streams

“…Stream mining and analytics are becoming increasingly important in the Web community [4,24,25]. Recently, WoT technology has been applied to uncertain/imprecise data [8,9]. Thus, there is an unmet need to extend current WOLAP techniques and engines to imprecise streaming sensor data from WoT devices.…”

“…However, the streaming data in WoT and WoE applications are often imprecise and inaccurate, the socalled veracity challenge. According to [8][9][10][11][12], data imprecision in WoT is inherent, and is caused by various reasons, including measurement inaccuracies [13,14], interpolation errors [10], and transmission latencies [11]. Nevertheless, in WoE, events are usually nondeterministic due to unreliable data sources and networks [8].…”

“…According to [8][9][10][11][12], data imprecision in WoT is inherent, and is caused by various reasons, including measurement inaccuracies [13,14], interpolation errors [10], and transmission latencies [11]. Nevertheless, in WoE, events are usually nondeterministic due to unreliable data sources and networks [8]. R2C2: To tackle the veracity challenge, probabilistic modeling has been applied for capturing the imprecision of WoT streaming items [8,9], in order to get the confidence of upper level event and query evaluation [8][9][10][11][12].…”

“…Nevertheless, in WoE, events are usually nondeterministic due to unreliable data sources and networks [8]. R2C2: To tackle the veracity challenge, probabilistic modeling has been applied for capturing the imprecision of WoT streaming items [8,9], in order to get the confidence of upper level event and query evaluation [8][9][10][11][12]. In this work, we model the imprecision of streaming data items by the general and commonly accepted tuple-uncertainty model in probabilistic data management [15], and study the problem of multidimensional probabilistic regression.…”

Managing Measurement and Occurrence Uncertainty in Complex Event Processing Systems

“…This paper is an extension of [26], where we sketched the initial ideas behind our approach. We have extended the original paper in several directions.…”