We present work-in-progress developing a communication framework that addresses the communication challenges of the decentralized multihop wireless environment. The main contribution is the combination of a fully distributed, asynchronous power save mechanism with adaptation of the timing patterns defined by the power save mechanism to improve the energy and bandwidth efficiency of communication in multihop wireless networks. The possibility of leveraging this strategy to provide more complex forms of traffic management is explored

Ahlgren, Bengt

Feeney, Laura Marie

Gunningberg, Per

English

Software institutes' Online Digital Archive

Enabling adaptive traffic scheduling in asynchronous multihop
wireless networks
Laura Marie Feeney ∗
Swedish Institute of Computer Science
Bengt Ahlgren
Swedish Institute of Computer Science
Per Gunningberg
Uppsala University
We present work-in-progress developing a communi-
cation framework that addresses the communication
challenges of the decentralized multihop wireless en-
vironment. The main contribution is the combina-
tion of a fully distributed, asynchronous power save
mechanism with adaptation of the timing patterns
defined by the power save mechanism to improve the
energy and bandwidth efficiency of communication in
multihop wireless networks. The possibility of lever-
aging this strategy to provide more complex forms of
traffic management is explored.
1 Introduction
This abstract describes work-in-progress developing
a communication framework that is well attuned to
the resource limitations and dynamic nature of the
wireless multihop networking environment. The pro-
posed approach is interesting because it is provides
a completely localized, adaptive solution. In par-
ticular, there is no requirement for synchronization,
clustering or shared control elements. These char-
acteristics are especially important in the multihop
wireless environment, which has the unique problem
that disjoint flows – despite having no nodes in com-
mon – interfere with each other.
The framework is based on a simple CSMA un-
derlayer and a lightweight power saving mechanism.
The power saving protocol establishes local sleep-
wake schedules that reduce nodes’ energy consump-
tion. These schedules also implicitly create high level
transmission schedules defined by the intervals dur-
ing which pairs of communicating nodes are both
awake. We believe that the timing of these intervals
can be manipulated to improve the efficiency of the
CSMA access. Moreover, because the CSMA under-
layer is ultimately responsible for ensuring appro-
priate channel access, it is possible to use techniques
that are sometimes “imperfect” in their attempts to
adapt to a dynamic environment.
∗Contact: Laura Marie Feeney(lmfeeney@sics.se). This
work was supported in part by the Ambient Networks project,
which is supported in part by the European Commission un-
der its Sixth Framework Program. The views and conclusions
contained herein are those of the authors and should not be
interpreted as necessarily representing the official policies or
endorsements, either expressed or implied, of the Ambient
Networks project or the European Commission.
More speculatively, we suggest that these tech-
niques lead to the emergence of roughly periodic
traffic patterns, making it easier to assess and pre-
dict link and region capacity. This may make it pos-
sible to provide higher layer resource management
capabilities than are currently feasible in multihop
wireless networks.
2 CSMA in multihop networks
Any simple CSMA protocol that is distributed and
asynchronous can provide the lowest underlying
communication layer for our framework. The work
is currently based on IEEE 802.11 “demo ad hoc
mode”, but the communications interfaces found on
nodes used in many sensor networks are similarly
suitable.
CSMA MAC layers are generally proposed for de-
centralized wireless networks. The “sense and send”
operation, often combined with RTS/CTS to miti-
gate the problems of hidden and exposed terminals,
is distributed and asynchronous. Despite its flexibil-
ity and simplicity, CSMA is also relatively inefficient
due to the time spent in defer, channel assessment
and backoff states and failure to optimally schedule
all feasible simultaneous transmissions.
3 Power save protocol
It is well-known that the energy consumption of a
wireless network interface in the idle state is much
higher than its energy consumption in a sleep state.
However, it is only in the idle state that the inter-
face is able to receive incoming frames. In the case
of a network with an AP, the AP establishes a syn-
chronous traffic schedule and buffers incoming traffic
destined for sleeping nodes 1.
In a decentralized multihop wireless network, con-
siderable overhead is required to maintain synchro-
nization and dynamic clustering, especially in the
case of resource-limited devices and dynamic net-
works subject to partition and merge. Therefore,
the power save protocol we define is designed for
asynchronous distributed operation. It is based on
well-known quorum structures (see e.g. [1, 2, 3, 4])
1A ’sleeping node’ is a node whose network interface (not
necessarily other system components) is in a sleep state .
sleep
transfer
ε
0 ε 0.5
I = 1 
0.5+ε
time
m
o
de
broadcast sub−intervals
0.5+ε0.50
awake
sleep
awake
interval
Figure 1: Overlap principle: At most two transmissions
are needed to reach a neighbor.
to ensure that nodes are pair-wise able to determine
times at which they are both awake.
Sleep-wake patterns All nodes follow a common
sleep-wake pattern, with an unknown phase differ-
ence between each node pair. The pattern is de-
fined such that small known broadcast sub-intervals
for each node are guaranteed to overlap with the
awake intervals of its neighbors.
Formally, given a common period I (normalized to
1) and a value 0 < ² < 0.25, let each node maintain
an awake interval of length .5+², followed by a sleep
interval of length .5 − ². Either the first or the last
sub-interval ² of each awake interval (the broadcast
sub-intervals) will be fully contained in the awake
interval of each neighbor, regardless of the phase dif-
ference between them.
See Figure 1 above and [3] for a proof and see [2]
for a more general discussion of quorum based tech-
niques in energy management for ad hoc networks.
In particular, we note that more complex patterns
can be used to obtain lower duty cycles and addi-
tional energy saving.
Traffic announcements A message transmitted
during each of a node’s broadcast sub-intervals is
eventually received by all of its neighbors, providing
an effective mechanism for transmitting broadcast
messages.
A transmitter with pending unicast traffic also
uses this mechanism to broadcast a traffic announce-
ment (ATIM). The ATIM contains the transmitter’s
own interval clock and current estimate of its phase
difference with respect to each intended receiver.
Each receiver compares estimated phase difference
in the ATIM with the phase difference it observes
based on the time of packet arrival. If they differ, the
receiver sends an ATIM-ACK, with updated phase
information, to the transmitter. (Fig 2).
Data transfer The traffic announcement protocol
allows each transmitter and receiver pair to discover
the transfer window during which they are both
awake. Given a set of pending messages and their
transfer windows, the transmitter can then sched-
ule the transmissions appropriately (e.g. constrained
FIFO).
B
A
ATIM_ACK
ATIMATIMATIM ATIM ATIMdata data
data enqueueddata enqueued data enqueued
Figure 2: Traffic announcement: The transmitter sends
an ATIM in each broadcast sub-interval. The receiver
responds only if the estimate in the ATIM is bad.
All transmissions use the underlying CSMA chan-
nel access (e.g. IEEE 802.11), which is also respon-
sible for managing re-transmissions and other trans-
mit parameters. While the framework does not pre-
clude the use of cross-layer information in packet
scheduling, discussion [5] of the pros and cons of
cross-layer interaction suggests the potential value
of maintaining this abstraction barrier.
Network operation The operation of the power
save protocol can be transparent to the operation
of other protocols. In particular, ad hoc neighbor
discovery and routing protocols based on some com-
bination of broadcast and unicast traffic to discover
routes (e.g. RREQ and RREP) do not need to be
aware of the broadcast sub-intervals or ATIM ex-
change.
Naturally, the reduced duty cycle has some per-
formance impact, in that available transmit times
are restricted. In the following section, we suggest
that the impact is, in fact, likely to be minimal with
respect to network capacity. The effect on route la-
tency is likely to be more significant and study of
proper tuning of ad hoc routing parameters is fu-
ture work.
The effect on mobility management (e.g. route
repair) is similar. The response to link failure de-
tection is not altered, although the timing may be.
This effect is due to possible loss of ATIM/ACKmes-
sages, as well as reduced opportunity for “snooping”
(rarely a good idea in an energy constrained system!)
due to the reduced duty cycle.
Feasibility Performance evaluation has focused
on studying the impact of the power saving schedul-
ing on the the overall capacity of the network. The
simple Matlab-based probabilistic simulation results
are intended primarily as a feasibility study.
The simulation scenario is based on a static net-
work of uniformly distributed nodes, with fixed nom-
inal transmission and interference ranges. The MAC
layer is assumed to prevent transmissions within in-
terference range of a sender or receiver, while trans-
missions within communication range always suc-
ceed without error. Flows are assumed to be uni-
form size, periodic transmissions between randomly
selected source-destination pairs. All flows use fixed
shortest path routing.
The network is filled to capacity by adding flows to
0.7
0.75
0.8
0.85
0.9
0.95
1
o
c c
u
p a
n c
y  
( %
)
50 random topologies
15 nodes(uniform random distribution)/unit square (1.0 x 1.0)
 transmit range=.38, interference range=.45
60% duty cycle (81%)
80% duty cycle (85%)
always on (89%)
Figure 3: Channel occupancy: The proportion of usable
transmission time obtained by a set of random source-
destination pairs (50 random topologies and mean).
the network, until no more flows can be added. One
key metric is then the proportion of time that the
channel is occupied, which implies a “good” phase
distribution. Figure 3 shows the channel utilizations
that are obtained with different duty cycles in the
network. Results are shown for each of fifty ran-
domly generated topologies and source-destination
pairs, for each of three values of 0.5+² (0.6, 0.8, and
1.0).
The results suggest that there is a moderate de-
crease in channel occupancy (from 89% to 81%) as
the duty cycle decreases from 100% to 60%, suggest-
ing a fairly moderate performance impact from ob-
taining significant energy saving. Because the sim-
ulation does not take into account overhead associ-
ated with the MAC and power save protocol, it is not
appropriate to conclude more than that the results
suggest feasibility.
4 Traffic Management
The structure created by the power save mechanism
is useful in two ways. It be used to improve the
efficiency of the underlying CSMA and, by impos-
ing a roughly periodic traffic patterns, we further
speculate that it can be used to assist in capacity
assessment and traffic management.
Despite this structure, the system nevertheless re-
flects the fluid, asynchronous behavior of the under-
lying framework, so that overlying mechanics can-
not rely on fixed behavior. But because they are
not ultimately responsible for arbitrating channel ac-
cess, they are also free to use approximate or heuris-
tic techniques and rely on the CSMA underlay for
“backup”.
4.1 Packet scheduling
In an multihop wireless network, only a small frac-
tion of the nominal bandwidth is effectively available
on a link[6]. Interference effects extend over multiple
hops, leading to contention between disjoint flows, as
well as self-interference along a flow. The former sit-
transfer
A
C
B
A−B
B−Cwindow
Figure 4: A “nice” phase distribution. In flow A-B-C,
hops A-B and B-C cannot interfere with each other. No
transmission is likely to defer because of the others.
uation is especially challenging, because there is no
common element that can arbitrate between flows.
CSMA protocols deal with contention by forcing
nodes to backoff if they detect interference. This can
be inefficient, especially when interferers are not in
communication range and it is necessary to probe.
If the transfer windows are distributed such that in-
terfering transmissions are avoided and each trans-
mitter detects a clear channel, the CSMA channel
access becomes more efficient (i.e. less likely to re-
quire exponential backoff). Figure 4 shows a trivial
example of a nice distribution of transfer windows.
Phase adjustment It is easy for a node to ad-
just its phase relative to its neighbors, by remaining
awake for the union of the old and new schedules,
while the relevant phase estimates are updated via
the ATIM protocol. Although the phase adjustment
is locally cheap, it affects the distribution of transfer
windows not only at the adjusting node, but also at
its neighbors. It is therefore difficult to determine,
without non-local information, the impact of an ad-
justment.
Randomized adaptation It is hard to explic-
itly construct a “good” phase distribution in a dis-
tributed fashion: Some STDMA link assignment
problems are known to be NP-hard. Phase adjust-
ment also leaves open the problem of stability and
the risk of creating a feedback loop, especially with
multiple flows.
A randomized approach is for a node to adjust its
schedule by a random amount in response to locally
detected congestion. To avoid too frequent or com-
peting adjustments, the decision to perform phase
adjustment is also probabilistic, based on the time
since the last observed adjustment.
This heuristic has the advantage of being simple,
though randomization does not provide any guaran-
tee of improved efficiency. With respect to stability,
it provides a bound on the number and distribu-
tion of phase adjustments. This method seems to be
effective only in relatively lightly loaded networks,
where there is some improved configuration to be
discovered.
D2
Flow 2:  S−A−C−D2
Flow 1:  S−A−B−D1
S
D2
B
A 
D1
C
S
A
B
C
D1
Figure 5: Multi-interval adapatation: Transmissions
are distributed to avoid contention and self-interference.
The network accommodates a load of one packet per flow
in every six intervals without contention.
Multi-interval adaptation Because of the ca-
pacity limitations of ad hoc networks, especially due
to self-interference along a flow, it is useful if adap-
tation can extend over several awake intervals. For
example, if a transfer window proves congested be-
cause it overlaps with the transfer window used by an
interfering node pair, it may not be possible to find
a phase adjustment that resolves this state. It may
be preferable for the transmitters to access the chan-
nel during alternate transfer windows, allowing the
flows to adapt to a transmit rate better supported
by the network. Figure 5 shows an example of a
configuration in which transmissions are distributed
across several intervals.
Periodicity Transfer windows are periodic, so
there will be a tendency for transmission patterns to
develop some periodicity as well. But because the
offered load is not periodic and because transmis-
sions take place anytime during the transfer window
subject to unpredictable CSMA behavior, the result
is only partially predictable behavior.
4.2 Capacity Assessment
The ability to provide even a crude link capacity
estimate is useful in providing some higher level ser-
vices. We expect that the framework will simplify
this assessment, because the transfer window and
super-frame structures identify a small set of inter-
vals over which availability is considered. Two appli-
cations of such assessment are routing and admission
control.
Routing The framework is agnostic with respect
to ad hoc routing protocols. However, some reactive
routing methods accumulate various route parame-
ters during route discovery and the destination uses
this information in selecting a route. Capacity met-
rics like those described above can easily be used to
inform the route selection process. The problem of
jointly creating a route and a phase distribution is
much more challenging, however.
Admission control Given the decentralized
structure and severe capacity constraints in the ad
hoc environment, “soft” admission control is poten-
tially important, less in a traditional QoS context
than in ensuring a reasonable operating regime for
the network. Capacity assessment is useful for such
admission control. Given a route, each node can as-
sess its transfer window with respect to the next hop
node. If the transfer window (or super-frame) seems
“too congested” to support the new flow, it can be
deprecated.
5 Conclusion and Future Work
This abstract has outlined some elements that are
being used to build an energy efficient MAC frame-
work that combines the advantages of simple channel
access support for simple traffic scheduling and even-
tually for advanced traffic management functional-
ity.
Preliminary simulation results are moderately
promising in suggesting that the proposed approach
is feasible. There remains substantial future work
in developing more detailed and realistic simulation
of protocol performance, particularly with respect to
details of the underlying CSMA MAC protocol and
propagation environment. Many of the speculative
ideas presented here provide exciting opportunities
for future exploration.
References
[1] L. M. Feeney, “An asynchronous power save protocol
for wireless ad hoc networks,” Tech. Rep. T2002:09,
SICS – Swedish Institute of Computer Science, July
2002. revised February, 2003.
[2] Y.-C. Tseng, C.-S. Hsu, and T.-Y. Hsieh, “Power-
saving protocols for IEEE 802.11-based multi-hop ad
hoc networks,” Comput. Networks, vol. 43, no. 3,
pp. 317–337, 2003.
[3] L. M. Feeney, “A QoS aware power save protocol for
wireless ad hoc networks,” in Proceedings of the First
Mediterranean Workshop on Ad Hoc Networks(Med-
Hoc Net 2002), (Sardenga, Italy), Sept. 2002.
[4] T. Braun and L. M. Feeney, “Power saving in wire-
less ad hoc networks without synchronization,” in
Proceedings of the 5th Scandanavian Conference on
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[5] V. Kawadia and P. R. Kumar, “A cautionary per-
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2005.
[6] J. Li, C. Blake, D. S. J. DeCouto, H. I. Lee, and
R. Morris, “Capacity of ad hoc wireless networks,”
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Enabling limited traffic scheduling in asynchronous ad hoc networks

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