Demo Abstract: A Traveling Wave-based Self-Organizing
Communication Mechanism for WSNs
Yoshiaki Taniguchi

Naoki Wakamiya

Masayuki Murata

Graduate School of Information
Science and Technology
Osaka University

Graduate School of Information
Science and Technology
Osaka University

Graduate School of Information
Science and Technology
Osaka University

y-tanigu@ist.osaka-u.ac.jp

wakamiya@ist.osaka-u.ac.jp

murata@ist.osaka-u.ac.jp

Abstract
We have proposed a simple and energy-efficient communication mechanism which can organize a variety of communication depending on dynamically changing application
requirements. In this demonstration, we show that our mechanism can gather or diffuse information in accordance withapplication requirements in a dynamic wireless sensor network.

Categories and Subject Descriptors
C.2.1 [Computer Communication Networks]: Network
Architecture and Design — Wireless Communications

General Terms
Algorithms, Design

Keywords
Wireless Sensor Networks, Traveling Wave

1 Introduction
In wireless sensor networks (WSNs), due to several restrictions including limited battery capacity, random deployment, and a large number of fragile sensor nodes, a communication mechanism should be energy efficient, adaptive,
robust, fully distributed, and self-organizing. Furthermore,
it should be able to handle various types of communication,i.e., diffusion and gathering, involving the whole networkin accordance with application requirements. For example,
a sensor node detecting an emergency would distribute thenotification over the whole WSN to alert the other nodes andmake them cooperatively react to the emergency. On the contrary, a sensor node detecting an uncertain condition would
collect and aggregate sensor information of the other nodes
to have a more precise view of the environment from collected information.
To accomplish the above-mentioned goal, we have proposed a simple and energy-efficient communication mechanism which can organize a variety of communication, i.e.,
diffusion and gathering, depending on dynamically changing
application requirements [1]. The desired pattern of message propagation emerges through reactions of sensor nodes
to surrounding conditions and local and mutual interactions
among sensor nodes, that is, by self-organization. For thispurpose, we adopt a pulse-coupled oscillator (PCO) model
Copyright is held by the author/owner(s).
SenSys’07, November 6–9, 2007, Sydney, Australia.
ACM 1-59593-763-6/07/0011

based on biological mutual synchronization such as that observed in flashing fireflies [2]. In a PCO model, oscillator i
has a timer, whose phase is denoted as φi ∈ [0, 1]. When thephase reaches one, oscillator i fires. Oscillators coupled withthe firing oscillator are stimulated and they shift their phaseby small amount Δ(φ j ), where j is an identifier of stimulated oscillator. The function Δ(φ) is called Phase Response
Curve (PRC). Through mutual interactions by stimuli amongoscillators, the global synchronization where all oscillators
fire synchronously, or a traveling wave, where oscillators behave synchronously keeping fixed phase difference, appears.
In [1], we considered a PRC function generating a travelingwave from random initial condition to organize a preferredcommunication pattern on demand in WSNs.
In this demonstration, we show implementation of ourtraveling wave-based communication mechanism. We also
demonstrate that our mechanism can gather or diffuse information in accordance with application requirements in a dynamic WSN.

2 A Traveling Wave-based Communication
Mechanism
We now briefly introduce our communication mechanism
for WSNs. In our mechanism, any of sensor nodes can become a point, called a core node, from which messages are
disseminated or to which messages are gathered. When there
is no session, sensor nodes emit messages at their own timing
and independently from the others.
Sensor node i has a timer with phase φi ∈ [0, 1], dφi /dt =1/T , where T is a cycle of data diffusion or gathering. Itmaintains PRC function Δ(φi ), level value li , session identifier si , direction δi , and offset τi (τmin ≤ τi ≤ τmax < 0.5). A
level value indicates the number of hops from a core nodeand it is used to define the relationship among sensor nodes.
Direction δi is a parameter which controls the direction of
information propagation, and it is set at 1 for diffusion and−1 for gathering. The offset defines the interval of message
emission between a node of level l − 1 and that of level l.
The maximum offset τmax is determined taking into accountthe density of sensor nodes in the whole WSN. Offset τi ischosen randomly to avoid synchronous message emissions
among same hop sensor nodes. In this paper, we use the following PRC function for all sensor nodes.
Δ(φi ) = a sinπ
φi + b(gi − φi ),gi

(1)

Here, gi is defined as (1 + δiτi ) mod 1.
As time passes, phase φi shifts toward one and, after
reaching it, sensor node i broadcasts a message and the phasejumps back to zero. A message that sensor node i emits contains level value li , session identifier si , direction δi , and its
information aggregated with other sensor’s information kept
in its buffer. To initiate a new communication, a core nodebroadcasts a message containing a new session identifier set
at the current value plus one, a level value of zero, the direction, and information to disseminate or gather.
Now, sensor node i receives a message from sensor node
j. If session identifier s j is larger than si , sensor node i considers that a new communication begins. Therefore, it sets
its level value li at l j + 1, session identifier si at s j , and direction δi at δ j . Then, it is stimulated to join a new traveling wave. This mechanism means that the current communication is terminated by a newly initiated communication.
If session identifiers are the same but the level value l j issmaller than li , sensor node i sets its level value li at l j + 1,direction δi at δ j , and it is stimulated. Stimulated sensor
node i shifts its phase based on the PRC function. As inthe PCO model, a sensor node is not stimulated by messages
from sensor nodes with a smaller level value during the following duration of τmax when it has already been stimulated,
to avoid being stimulated by deferred messages. If the session identifier is the same and level value l j is li − δi , sensor
node j is an upstream node of sensor node i. Therefore, torelay information of sensor node j to the next downstream
node, sensor node i deposits the received information in its
local buffer. If a message does not satisfy any of the above
conditions, sensor node i ignores it.
Through mutual interactions among neighboring sensor
nodes, they reach the state, called phase-lock, where thephase differences among sensor nodes are kept constant, andthey emit sensor information alternately. After reaching thephase-lock, a sensor node starts a sleep schedule. It wakes
up when its phase is at 1 − τmax to receive messages fromupstream nodes. Upstream nodes are scheduled to emit theirmessages from 1 − τmax to 1. When its phase reaches one, asensor node broadcasts a message. After that, it keeps awakefor τmax to receive messages from downstream nodes, andthen goes to sleep. Therefore, a node is awake for the duration of 2τmax in one communication cycle. An example oftiming of message emission where node i is a downstream
node of nodes j and k is illustrated in Fig. 1.
Although further details are note given in the paper due
to limitation of the space, our mechanism can adapt to additional deployment and removal of sensor nodes, multiple
core nodes, and node failures [1].

3 Demonstration
We implemented our mechanism on MICAz Motes. Tomaintain the stable multi-hop network topology on a table,
we introduce a filter with which a node ignores messages
from non-neighboring nodes based on their identifiers. Eachsensor node has a red LED and two push switches. The LED
flashes when the sensor node broadcasts a message. A sensor node becomes a core node for information diffusion orgathering when its switch is pushed.

broadcast
τmax
τmax

sleep

τj
tj

ti

ti

node itime level linode jlevel li+1

τktj
jnode klevel li+1

tkitkkFigure 1. Timing of Message Emission
Node#7

Node#1

Node#9Node#4
Node#6
Node#2

Node#5

Node#3

Node#8
Node#10Figure 2. Prototype Network
We can choose any sensor node as a core node for information diffusion or gathering. For example, consider a WSN
illustrated in Fig. 2, where dashed lines indicate neighbor relations. When node 6 becomes a core node for information
diffusion, a communication pattern centered at node 6 eventually emerges. First node 6 broadcasts a message. At thistime, nodes 4, 5, 7, and 8 are awake to receive the message.
Then, they broadcast a message at slightly different timing
based on their offset τi . The messages are received by theirdownstream nodes and then relayed further toward the edgeof the WSN. If we next choose node 7 as a core node for
information gathering, the previous diffusion pattern is firstbroken and a new pattern appears. In our preliminary experiments where 25 nodes are arranged in a grid layout, theaverage delivery ratio of 95% is accomplished.
The prototype can adapt to addition and removal of nodes.
When node 5 is removed from gathering type of session tonode 7 for example, node 3 does not receive any messageof lower level value any more. Then, node 3 sets its session
identifier to 0 and re-joins the session by receiving messages
from remaining neighboring nodes. In this case, node 2 becomes a downstream node of node 3. Now node 5 returns.
Since a level value of node 5 is 2 and that of node 2 is 3,
a level value of node 3 is changed from 4 to 3. Then, theformer traveling wave is established again.

4 Acknowledgment
This work was partly supported by “Global COE (Centersof Excellence) Program”, “Special Coordination Funds forPromoting Science and Technology: Yuragi Project”, Grantin-Aid for Scientific Research on Priority Areas 18049050,
and a Grant-in-Aid for Scientific Research (A)(2) 16200003
of the Ministry of Education, Culture, Sports, Science andTechnology in Japan.

5 References[1] Y. Taniguchi, N. Wakamiya, and M. Murata, “A selforganizing communication mechanism using travelingwave phenomena for wireless sensor networks,” in Proceedings of AHSP 2007, pp. 562–569, Mar. 2007.
[2] P. Goel and B. Ermentrout, “Synchrony, stability, andfiring patterns in pulse-coupled oscillators,” Physica D,
pp. 191–216, Mar. 2002.