Abstract
New applications based on wireless sensor networks (WSN), such as person-locator services, harvest a large amount of data streams that are simultaneously generated by multiple distributed sources. Specifically, in a WSN this paradigm of data generation/transmission is known as event-streaming. In order to be useful, all the collected data must be aligned so that it can be fused at a later phase. To perform such alignment, the sensors need to agree on common temporal references. Unfortunately, this agreement is difficult to achieve mainly due to the lack of perfectly synchronized physical clocks and the asynchronous nature of the execution. Some solutions tackle the issue of the temporal alignment; however, they demand extra resources to the network deployment since they try to impose global references by using a centralized scheme. In this paper, we propose a temporal alignment model for data streams that identifies temporal relationships and which does not require the use of synchronized clocks, global references, centralized schemes, or additional synchronization signals. The identification of temporal relationships without the use of synchronized clocks is achieved by translating temporal dependencies based on a time-line to causal dependencies among streams. Finally, we show the viability and the effectiveness of the model by simulating it over a sensor network with multihop communication.
Highlights
Emerging applications based on wireless sensor networks (WSN) such as remote monitoring of biosignals, multimedia surveillance systems and person locator services [1] ubiquitously1 harvest a large amount of continuous timebased data, as audio or video, that is generated from several sensor nodes in a distributed and concurrent way [10, 6, 18]
The HBR is a strict partial order on events, defined as follows: Definition 1 The happened-before relation, “→”, is the smallest relation on a set of events E satisfying the following conditions: 1. If a and b are events belonging to the same process, and a was originated before b, a → b
The Event-streaming logical mapping model (ES-LM) is the core of the data alignment scheme that we propose, which is presented
Summary
Emerging applications based on wireless sensor networks (WSN) such as remote monitoring of biosignals, multimedia surveillance systems and person locator services [1] ubiquitously harvest a large amount of continuous timebased data, as audio or video, that is generated from several sensor nodes in a distributed and concurrent way [10, 6, 18]. In order to avoid the use of synchronized clocks, a clockfree alignment approach for data streams was proposed in [14] This solution is based on the fact that in most sensor networks, some sensor nodes act as intermediate nodes to aggregate or to collect the data streams which are later sent to another sensor or sink. Assuming the previous communication scheme, the approach has shown that aligning the data streams on the intermediate nodes without synchronizing the clocks of all sensors is sufficient This solution requires a synchronization server that broadcasts synchronization signals to the sensors to establish a global reference, and it needs dedicated devices (data servers) to align the streams according to the broadcasted signals.
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