Efficient Distributed Query Processing

Abstract

Abstract-A variety of wireless networks, including applications of Wireless Sensor Networks, Internet of Things, Cyberphysical Systems, etc., 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, 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 to 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:Abstract-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 Internet of Things. However, due to the inherent difficulty in building theses systems, technically and in terms of balancing the trade-offs between (economic) cost and performance (energy, latency, reliability, 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 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 centralised storage and management platform, to decentralised 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; a method to store static attributes in a distributed m...

Energy-Efficient Communication in Wireless Networks

“…Other approaches like Energy Aware Routing (EAR) [71] use a routing table to store several alternative routes to the base-station so a node can choose alternative routes in order to beter distribute network load. Kolcun et al proposed Dragon [72], where every node in the network stores a path to every other node in the network. The platform also includes algorithms for quick update of the routing table in the case of a node failure while keeping the network overhead low.…”

“…Kolcun et al introduced the Static Atribute Propagation algorithm as a part of their Dragon platform [72]. The algorithm eliminates unnecessary re-broadcasts of the message by overhearing the messages of its neighbours.…”

“…Collection CTP [44], RPL [23], BCP [52], LEACH [53], HEED [55], PEGASIS [54], LWB [77] Dissemination SPIN [74], RR [75], Static Atribute Propagation [72], RPL [23], LWB [77], Trickle [76] Peer-to-peer GEAR [62], GPSR [60], Geometric Ad hoc Routing [61], ORPL [64], Innet [66], AODV-BR [69], Dragon [72], LWB [77], Chaos [78] The protocol is also prepared to support new types of headers in the future.…”

Efficient In-Network Processing for a Hardware-Heterogeneous IoT

“…One such fully distributed framework, DRAGON [10,11], proposed by Kolcun et al (2014), supports peer-to-peer routing by storing a routing table on every node and using hop count as the routing metric. In DRAGON, every node has a list of static attributes (SA) associated with it.…”

“…For each network, 10 experiments were executed and the overall average is presented. The evaluation environment is the same as was used in DRAGON [10] and PND [9].…”