scispace - formally typeset
Open AccessProceedings ArticleDOI

The dynamic behavior of a data dissemination protocol for network programming at scale

Reads0
Chats0
TLDR
It appears very hard to significantly improve upon the rate obtained by Deluge and it is argued that the rates obtained for dissemination are inherently lower than that for single path propagation.
Abstract
To support network programming, we present Deluge, a reliable data dissemination protocol for propagating large data objects from one or more source nodes to many other nodes over a multihop, wireless sensor network. Deluge builds from prior work in density-aware, epidemic maintenance protocols. Using both a real-world deployment and simulation, we show that Deluge can reliably disseminate data to all nodes and characterize its overall performance. On Mica2-dot nodes, Deluge can push nearly 90 bytes/second, one-ninth the maximum transmission rate of the radio supported under TinyOS. Control messages are limited to 18% of all transmissions. At scale, the protocol exposes interesting propagation dynamics only hinted at by previous dissemination work. A simple model is also derived which describes the limits of data propagation in wireless networks. Finally, we argue that the rates obtained for dissemination are inherently lower than that for single path propagation. It appears very hard to significantly improve upon the rate obtained by Deluge and we identify establishing a tight lower bound as an open problem.

read more

Content maybe subject to copyright    Report

Citations
More filters
Journal Article

Dynamic Reconfiguration of Wireless Sensor Networks

TL;DR: This paper is an attempt to devise an efficient, robust and stable solution for the problem of remote reprogramming of wireless sensor networks and trying to address some of the problems associated with attempts taken by other researchers such as Network Reprogramming, Sensor reconfiguration and Supporting Tools.
Journal ArticleDOI

Reliable and efficient reprogramming in sensor networks

TL;DR: This work proposes a reprogramming/retasking framework for sensor networks that is energy efficient, responsive, and reliable, while maintaining a stable network.
Journal ArticleDOI

Towards a flexible global sensing infrastructure

TL;DR: This work proposes a software architecture that encodes applications as malleable, platform-independent, high-level mobile scripts, and allows applications to function in diverse settings by employing dynamic rebinding of mobile scripts to different services as they execute over extended intervals across different types of networks.
Proceedings ArticleDOI

RMTool: Component-Based Network Management System for Wireless Sensor Networks

TL;DR: A component-based network management system, RMTool, which allows developers to easily monitor and analyze the network status and interactively configure the network over unexpected problems while running applications over it.
Proceedings ArticleDOI

An efficient code update solution for wireless sensor network reprogramming

TL;DR: An incremental code update strategy used to efficiently reprogram wireless sensor nodes and achieves reductions of 99.987% for simple changes and between 86.95% and 94.58% for more complex changes, leading to significantly lower energy costs for wireless sensor network reprogramming.
References
More filters
Proceedings ArticleDOI

The broadcast storm problem in a mobile ad hoc network

TL;DR: This paper proposes several schemes to reduce redundant rebroadcasts and differentiate timing of rebroadcast to alleviate the broadcast storm problem, which is identified by showing how serious it is through analyses and simulations.
Proceedings ArticleDOI

TOSSIM: accurate and scalable simulation of entire TinyOS applications

TL;DR: TOSSIM, a simulator for TinyOS wireless sensor networks can capture network behavior at a high fidelity while scaling to thousands of nodes, by using a probabilistic bit error model for the network.
Proceedings ArticleDOI

Epidemic algorithms for replicated database maintenance

TL;DR: This paper descrikrs several randomized algorit, hms for dist,rihut.ing updates and driving t,he replicas toward consist,c>nc,y.
Journal ArticleDOI

The broadcast storm problem in a mobile ad hoc network

TL;DR: This paper proposes several schemes to reduce redundant rebroadcasts and differentiate timing of rebroadcast to alleviate the broadcast storm problem, which is identified by showing how serious it is through analyses and simulations.
Proceedings ArticleDOI

Maté: a tiny virtual machine for sensor networks

TL;DR: Maté's concise, high-level program representation simplifies programming and allows large networks to be frequently reprogrammed in an energy-efficient manner; in addition, its safe execution environment suggests a use of virtual machines to provide the user/kernel boundary on motes that have no hardware protection mechanisms.
Related Papers (5)
Frequently Asked Questions (19)
Q1. What are the contributions in "The dynamic behavior of a data dissemination protocol for network programming at scale" ?

To support network programming, the authors present Deluge, a reliable data dissemination protocol for propagating large data objects from one or more source nodes to many other nodes over a multihop, wireless sensor network. Using both a real-world deployment and simulation, the authors show that Deluge can reliably disseminate data to all nodes and characterize its overall performance. 

Because the cost of end-to-end repair is exponential with the path length, both protocols emphasize hop-by-hop error recovery where loss detection and recovery is limited to a small number of hops (ideally one). 

By opening up sockets to each node from a desktop computer, the authors timestamp each UART message with precision on the order of milliseconds and track the propagation of each page. 

spatial multiplexing limits a node’s broadcast rate to no greater than onethird the maximum rate due to the single-channel, broadcast medium. 

One might suggest that starting the propagation in the centermight help to eliminate the behavior of following the edge and also decrease the propagation time by about half. 

The authors experimented with suppressing the transmission of data packets if k redundant data packets were overheard while in TX, where lower values of k represented more aggressive suppression. 

One cause is Deluge’s depth-first tendency, where propagation of a single page along good links is not blocked by delays caused by poor links. 

By doubling τr, the propagation rate along the diagonal improves by about 2.7 times while the propagation rate along the edge remains nearly identical, leading to an improvement in overall propagation performance. 

Even though placing the source at the center effectively reduces the the diameter by about half, Deluge is unable to take advantage of the quick edges since nodes in the center experience a greater number of collisions. 

The expected time required to transmit just the data packets isE[Ttx] = E[NtPkt] · TtPkt ·N, (2)where TtPkt is the transmission time for a single packet. 

The only trigger that causes R to request data from S is the receipt of an advertisement stating the availability of a needed page. 

the rate of requests from R will decrease with the decreasing advertisement rate in the steady state since S will not know that R is not up-to-date. 

The main advantage with simulating at the bit-level is that the transmission and reception of bits govern the actions of each layer, rather than modeling each layer with its own set of parameters. 

the authors used TOSSIM to evaluate and investigate the behavior of Deluge with network sizes on the order of hundreds of nodes and tens of hops. 

For the linear case, the simulations show that Deluge takesabout 40 seconds to disseminate each page to 152 nodes across 15 hops. 

Because requests are unicast to the node that most recently advertised, it is unlikely for many senders in a region to begin transmitting data. 

With this topology, the propagation behaves as expected: the propagation progresses at a fairly constant rate in a nice wavefront pattern from corner to corner. 

This structured approach should improve the propagation time for a single page, but inhibits the use of pipelining since it is more difficult to minimize interference between transfers of different pages. 

Using the transmission count information on advertisements, the authors plot a histogram of the average advertisement rate for each node by dividing the count by the completion time.