Adaptive protocols for information dissemination in wireless sensor networks

By Wendi Rabiner Heinzelman, Joanna Kulik, Hari Balakrishnan. 1999

In this paper, we present a family of adaptive protocols, called SPIN (Sensor Protocols for Information via Negotiation), that efficiently disseminates information among sensors in an energy-constrained wireless sensor network. Nodes running a SPIN communication protocol name their data using high-level data descriptors, called meta-data. They use meta-data negotiations to eliminate the transmission of redundant data throughout the network. In addition, SPIN nodes can base their communication decisions both upon application-specific knowledge of the data and upon knowledge of the resources that are available to them. This allows the sensors to efficiently distribute data given a limited energy supply. We simulate and analyze the performance of two specific SPIN protocols, comparing them to other possible approaches and a theoretically optimal protocol. We find that the SPIN protocols can deliver 60% more data for a given amount of energy than conventional approaches. We also find that, in terms of dissemination rate and energy usage, the SPlN protocols perform close to the theoretical optimum.

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Citations in the corpus

A Multi-Agent Framework for Packet Routing in Wireless Sensor Networks (2015, background): “[12,13] proposed a family of adaptive protocols, called sensor protocols for information via negotiation (SPIN).”
Gossip-based ad hoc routing (2002, methodology): “[10] have applied gossiping in data dissemination in wireless sensor networks, using techniques similar in spirit to those of [22].”
Efficient algorithms for maximum lifetime data gathering and aggregation in wireless sensor networks (2003, methodology): “Other previous works [9,10,14,15] in the related area aim at reducing the energy expended by the sensors during the process of data gathering.”
J-Sim: a simulation and emulation environment for wireless sensor networks (2006, background): “Any in-networking processing mechanism such as that discussed in [32] can be implemented in the sensor application layer.”
Efficient broadcasting protocols for regular wireless sensor networks (2003, background): “SPIN [9] is the first data-centric routing mechanism.”
CODA: congestion detection and avoidance in sensor networks (2003, background): “, based on the data dissemination protocol [6] [3]) without the intervention of closed loop sink regulation.”
A survey on routing protocols in Wireless Sensor Networks (2012, background): “There are some location based protocols which are designed for wireless ad hoc networks, such as Cartesian and trajectory-based routing [7].”
Understanding packet delivery performance in dense wireless sensor networks (2003, background): “Wireless sensor networks [5, 7] are predicted on ad-hoc wireless communications.”
Sensor information networking architecture and applications (2001, methodology): “By integrating SPIN into SINA, the architecture will achieve higher level of resource conservation.”
Overview of Data Routing Approaches for Wireless Sensor Networks (2012, methodology): “M-SPIN (Modified-SPIN) [44] is an improved version of SPIN (Sensor Protocols for Information via Negotiation) protocol [8] in which like in SPIN, data negotiation among the nodes is taken into consideration.”
Middleware to support sensor network applications (2004, background): “For example, both Limbo [17] and FarGo [18] reorder data exchanges or relocate components to respond to changing network conditions such as bandwidth availability or link reliability.”
A taxonomy of wireless micro-sensor network models (2002, background): “In-network data processing [5, 7, 8] is an example of co-operative sensors.”
A Survey on Routing Protocols for Large-Scale Wireless Sensor Networks (2011, background): “The routing protocols belonging in this category include Sensor Protocols for Information via Negotiation (SPIN [2,3]), Directed Diffusion (DD [4]), Rumor Routing [5], Gradient-based routing (GBR [6]), Energy-Aware Routing (EAR [7]), and the Minimum Cost Forwarding Algorithm (MCFA [8]), etc.”
Hyrax: Cloud Computing on Mobile Devices using MapReduce (2009, background): “of the applications of mobile-cloud computing, such as distributed image search, have been studied in a sensor network context Yan et al. [2008]. Considering all of these compatibilities, it would be worthwhile to investigate the usage of sensor network software for mobile-cloud computing in future ”
Sensor relocation in mobile sensor networks (2005, background): “Due to many attractive characteristics of sensor nodes such as small size and low cost, sensor networks [10], [13], [15], [17], [1] have become adopted to many military and civil applications including military surveillance, smart homes [18], remote environment monitoring, and in-plant robotic contr”