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Towards Developing Attentive Wireless Sensor Networks

The large, rapidly growing field of wireless sensor networks (WSNs) offers the ability to collect and process massive amounts of information from various environments. This distributed data gathering and computation with the help of tiny, power-limited devices enables their use in surveillance, target detection and various other monitoring applications. In this context, the role of a sensor network can be viewed as that of a system that pays attention to a phenomenon of interest. Thus, the current body of literature on WSNs falls into two major categories: developing networks that a) pay attention to the environment to detect the phenomenon under consideration and b) improving the quality of attention paid by WSNs to these phenomena. In this paper, we summarize a theoretical framework for the context of attention in WSNs. This paper is the first step to develop a foundation for understanding the association between the nature of attention in WSNs and their real-world applications. In this paper, we introduce the concept of attention in wireless sensor networks by framing a relationship between the nature of attention at the cognitive level and the parallel datagathering and processing functions carried out by WSNs. Wireless sensor networks are aptly named for their ability to sense the deployment region, gather data and use it for higher levels of processing. Multi-hop links or a single direct link is used to route this gathered data to a central base station (sink) in order to reconstruct the desired parameters of the deployment region [1]. The power-limited nature of sensor nodes effectively constrains the processing and data dissemination that are necessary to achieve sensing objectives of reliable network operation with the objective of prolonging network lifetime. This constraint has spawned research in deployment, signal processing, communication and networking within WSNs. In particular, these issues can be classified within the context of attention into two main categories. The first category deals with developing networks that pay attention to the environment: i.e. the range of WSN applications. This is evident in the study of WSNs developed for habitat monitoring [2], weather detection [3] and structural monitoring [4] to name a few. The other category deals with improving the quality of attention paid by the WSN to the phenomenon under consideration. Deployment, density control, routing, data processing and security are themes used to improve the quality of attention paid by the WSN to the environment. Our work unifies current research in terms attention: the fundamental ability of sensor networks to pay attention and process data gathered from attentive sensing to fulfill sensing objectives. In our knowledge this is the first work that addresses WSN applications and performance as a function of attention paid by the network. Below, we provide a brief