Efficient Distributed Query Processing

doi:10.1109/TASE.2016.2530941

Efficient Distributed Query Processing

2016-07-01

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DOI：10.1109/TASE.2016.2530941

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A variety of wireless networks, including applications of Wireless Sensor Networks, Internet of Things, and Cyber-physical Systems, increasingly pervade our homes, retail, transportation systems, and manufacturing processes. Traditional approaches communicate data from all sensors to a central system, and users (humans or machines) query this central point for results, typically via the web. As the number of deployed sensors, and thus generated data streams, is increasing exponentially, this traditional approach may no longer be sustainable or desirable in some application contexts. Therefore, new approaches are required to allow users to directly interact with the network, for example, requesting data directly from sensor nodes. This is difficult, as it requires every node to be capable of point-to-point routing, in addition to identifying a subset of nodes that can fulfil a user's query. This paper presents DRAGON, a platform that allows any node in the network to identify all nodes that satisfy user queries, i.e., request data from nodes, and relay the result to the user. The DRAGON platform achieves this in a fully distributed way. No central orchestration is required, network overheads are low, and latency is improved over existing comparable methods. DRAGON is evaluated on networks of various topologies and different network densities. It is compared with the state-of-the-art algorithms based on summary trees, like Innet and SENS-Join. DRAGON is shown to outperform these approaches up to 88% in terms of network traffic required, also a proxy for energy efficiency, and 84% in terms of processing delay. Note to Practitioners-This work is motivated by the continuing deluge of constrained, wirelessly connected sensing and control devices. Networks of communicable sensors and actuators are finding increased applicability across a range of industries and application scenarios. They are often thought of as a subset of the 'nternet of Things. However, due to the inherent difficulty in building theses systems technically and in terms of balancing the tradeoffs between (economic) cost and performance (e.g., energy, latency, reliability, and determinism), uptake has been slow. The community is relatively small and therefore has not overcome all of the problems that present themselves considering required functionality of industrial applications. There is a need to find new ways to interact with these devices, particularly those with heterogeneous attributes. There is also clear motivation to progress from traditional system architectures, whereby all data sensed are transmitted to centralized storage and management platform, to decentralized means of interrogation and control. This work proposes a solution to this problem, describing and evaluating a novel framework to query constrained networked devices based on two key improvements over the current art. The first is construction and management of a dynamic routing mechanism that facilitates the second, which is a method to store static attributes in a distributed manner, which can be queried by a user-man or machine-in a decentralized way. In combination, they are presented as a platform, essentially a middleware, implementable in embedded firmware that sits between the lower (i.e., physical and medium access control) and upper (i.e., application) layers of the stack. The algorithms are presented in full, and extensively evaluated with respect to existing approaches. It is shown that the proposed platform significantly outperforms the existing art considering efficiency (latency and energy), maintaining modest implementation overheads in computation and memory. Ongoing and future work concerns extending this capability to continuous operation, considered essential for distributed control and autonomous systems applications.

Keywords:

Autonomous and automated sensing and control systems

cyber-physical systems

distributed query processing

distributed storage

routing algorithm

wireless sensor networks

Efficient Distributed Query Processing

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