A distributed mechanism for power saving in IEEE 802.11 wireless LANs.
The finite battery power of mobile computers represents one of the greatest limitations to the utility of portable computers. Furthermore, portable computers often need to perform power consuming activities, such as transmitting and receiving data by means of a random-access, wireless channel. The amount of power consumed to transfer the data on the wireless channel os negatively affected by the channel congestion level, and significantly depends on the MAC protocol adopted. This paper illustrates the design and the performance evaluation of a new mechanism that, by controlling the accesses to the shared transmission channel of a wireless LAN, leads each station to an optimal Power Consumption level. Specifically, we considered the Standard IEEE 802.11 Distributed Coordination Function (DCF) access scheme for WLANS. For this protocol we analytically derived the optimal average Power Consumption levels required for a frame transmission. By exploiting these analytical results, we define a Power Save, Distributed Contention Control (PS-DCC) mechanism that can be adopted to enhance the performance of the Standard IEEE 802.11 DCF protocol from a power saving standpoint. The performance of an IEEE 802.11 network enhanced with the PS-DCC mechanism has been investigated by simulation. Results show that the enhanced protocol closely approximates the optimal power consumption level, and provides a channel utilization close to the theoretical upper bound for the IEEE 802.11 protocol capacity. In addition, even in low load situations, the enhanced protocol does not introduce additional overheads with respect to the standard protocol.
Introduction
The finite battery power of mobile computers represents one of the greatest limitations to the
utility of portable computers [10, 17]. Projections on the expected progress in battery technology
show that only a 20% improvement in the battery capacity is likely to occur over the next 10 years
[14]. Despite this fact, in Ad-Hoc network scenarios, portable computers often need to transmit and
receive data by means of a random-access, wireless transmission channel. These activities are among
some of the most power consuming operations to perform [11, 15]. If the battery capacity cannot
be improved, it is vital that power utilization is managed efficiently by identifying any way to use
less power preferably with no impact on the applications, nor on the resources' utilization. Several
studies have been carried out in order to define mechanisms useful for Power Saving (PS) in wireless
LANs [1, 11]. Strategies for power saving have been proposed and investigated at several layers
including the physical-layer, the MAC layer, the transport and the application levels [1, 11, 17].
Transmitter Power Control strategies to minimize power consumption, mitigating interference and
increasing the cell capacity have been proposed, and the design aspects of power-sensitive wireless
network architectures have been investigated [1, 13, 18]. The impact of network technologies and
interfaces on power consumption has been investigated in depth in [15]. The power saving features
of the emerging standards for wireless LANs have been analyzed in [12, 17].
In this paper we investigate a power saving strategy at the MAC level. Specifically, we focus
on the wireless ad-hoc network paradigm, and on the Carrier Sense Multiple Access with Collision
Avoidance (CSMA/CA) access mechanism adopted, for example, in the IEEE 802.11 WLANs
[9]. The IEEE 802.11 access scheme is based on two access methods: Distributed Coordination
Function (DCF) for asynchronous, contention-based, distributed accesses to the channel, and Point
Coordination Function (PCF) for centralized, contention-free accesses. We will concentrate our
analysis over DCF, which may be significantly affected by the congestion problem, due to distributed
random access characteristics.
For these CSMA/CA protocols the amount of power consumed by transmissions is negatively
affected by the congestion level of the network. Indeed, by increasing the congestion level, a
considerable power is wasted due to the collisions. To reduce the collision probability, the stations
perform a variable time-spreading of accesses, which results in additional power consumption, due
to Carrier Sensing 1 . Hence, these protocols suffer a power wastage caused both from transmissions
resulting in a collision and from the amount of Carrier Sensing (active reception time) introduced
by the time-spreading of the accesses. Furthermore, the transmission phase can be considered at
least twice more power-consuming than the reception (or idle) phase. This fact could introduce
some kind of transmission policy optimization, by evaluating the risks (i.e. the costs/benefits) of
transmission attempts to be performed, given the current congestion conditions, and the system's
Power Consumption parameters. As the reduction of the time-spreading periods generally produces
an increase in the number of collisions, to minimize the power wastage the access protocol should
balance these two costs. Therefore the power saving criterion we adopt throughout this paper is
based on balancing the power consumed by the network interface in the transmission and reception
(e.g. Physical Carrier Sensing) phases. Since these costs change dynamically, depending on the
network load, a power-saving protocol must be adaptive to the congestion variations in the system.
In addition, a Power Saving strategy should balance the need for high battery lifetime with the
need to maximize the channel utilization and the QoS perceived by the network users [11].
In this paper, we propose a Power-Save, Distributed Contention Control (PS-DCC) mechanism
which can be used on top of the IEEE 802.11 DCF access method to maximize the power saving
while accessing the wireless channel. The proposed mechanism dynamically adapts the behavior of
each station to the congestion level of the system and, beyond providing power saving, it contributes
to obtain an optimal channel utilization, see [5].
The work is organized as follows: in Section 2 we present the actual Standard 802.11 DCF
access scheme, and critical aspects connected to the contention level of the system; in Section 3 the
DCC mechanism proposed in [2] is summarized; in Section 4 the analytical model of the system is
presented; in Section 5 the new PS-DCC mechanism is defined an analyzed; in Section 6 simulation
results are presented and commented; in Section 7 conclusions and future researches are given.
For the detailed explanation of the IEEE 802.11 Standard we address interested readers to [9].
Throughout we denote as active station a station with at least a frame to transmit. The Basic
Access method in the IEEE 802.11 MAC protocol is the Distributed Coordination Function (DCF)
which is a CSMA/CA MAC protocol. Every active station is required to perform a Carrier Sensing
activity to determine the current state of the channel (idle or busy). If the medium is found busy, the
1 The latter point has been faced in some cases; for example, IEEE 802.11 networks try to reduce the amount of
Physical Carrier Sensing (CS), by exploiting Virtual CS based on Network Allocation Vectors' (NAV) updating [9].
station defers transmission. Whenever the channel becomes idle for at least a Distributed Interframe
Space time interval (DIFS), the station (re)starts its Basic Access mechanism. To avoid collisions
as soon as an idle DIFS is sensed on the channel, the Collision Avoidance mechanism adopted in the
Standard 802.11 DCF is based on a Binary Exponential Backoff scheme [6, 7, 9]. When the channel
is idle, time is measured in units of constant length indicated as slots in the following. Throughout
Slot Time will be used to denote the length of a slot. The Binary Exponential Backoff scheme is
implemented by each station by means of the Backoff Counter parameter, which maintains the
number of empty slots the tagged station must observe on the channel, before performing its own
transmission attempt. At the time a tagged station needs to schedule a new transmission, it selects
a particular slot among those of its own Contention Window, whose size is maintained in the local
parameter CW Size. Specifically, the Backoff value is defined by the following expression [9]:
Backoff Counter(CW
where Rnd() is a function returning pseudo-random numbers uniformly distributed in [0.1]. The
Backoff Counter is decreased as long as a slot is sensed idle, it is frozen when a transmission is
detected, and reactivated after the channel is sensed idle for at least a further DIFS. As soon as the
Backoff Counter reaches the value Zero the station transmits its own frame. Positive acknowledgements
are employed to ascertain a successful transmission. This is accomplished by the receiver
(immediately following the reception of the data frame) which initiates the transmission of an acknowledgement
frame (ACK) after a time interval Short InterFrame Space (SIFS), which is less
than DIFS. If the transmission generates a collision 2 , the CW Size parameter is doubled for the
scheduling of the retransmission attempt, thus obtaining a further reduction of the contention. The
Binary Exponential Backoff is then characterized by the expression which gives the dependency of
the CW Size parameter by the number of unsuccessful transmission attempts (Num
performed for a given frame. In [9] it is defined that CW Size is set equal to CW Size min
(assuming low contention), when a new frame is transmitted, and doubled each time a collision
occurs up to a maximum value CW Size MAX , as follows:
The increase of the CW Size parameter value after a collision is the reaction that the 802.11
Standard provides to make the access mechanism adaptive to channel conditions. This mechanism
could introduce a low utilization of the channel bandwidth, due to high collision rates in congested
scenarios [2]. The choice to initially assume a low level of congestion in the system avoids a great
A collision is assumed whenever the ACK from the receiver is missing [9].
access delay when the load is light. Unfortunately this also represents a problem in bursty arrival
scenarios, and in congested systems, because it introduces a concentration of accesses in a reduced
time window, and hence it causes a high collision probability. Moreover, Collision Detection (CD)
results not practicable in wireless channels, and this makes the cost of each collision proportional
to the maximum size among colliding frames.
3 The DCC mechanism
The reasons explained in the previous section, motivated the studies to improve the performance
of a random access scheme, by exploiting early and meaningful information concerning the actual
state of the channel congestion. The idea presented in [2] involves an estimate of the resource's
congestion level, which can be given by the utilization rate of the slots (Slot Utilization) observed
on the channel by each station. The estimate of the Slot Utilization has to be maintained and
updated by each active station, during the defer phase that precedes a transmission attempt, also
indicated as Backoff interval. Specifically, during its own Backoff interval, every active station
counts the number of transmission attempts it observes on the channel (Num Busy Slots), and
then divides this number by the total number of slots available for transmission observed on the
channel. Hence, a simple and intuitive definition of the Slot Utilization estimate is given by:
Slot U tilization = Num Busy Slots
Available Slots
The Slot Utilization provides a normalized lower bound for the actual contention level of the
channel. In fact, as some stations may transmit in the same slot, it provides a lower bound to the
effective number of stations trying to access the channel during the last observed Backoff interval.
By assuming a time-locality of contention, such an information is significant about the state of the
channel in immediately successive slots.
A station which knows there are few possibilities for a successful transmission, should defer its
transmission attempt. Such a behavior could be achieved in an IEEE 802.11 network by exploiting
the DCC mechanism proposed in [2]. According to DCC, each station controls its transmission
attempts via a new parameter named Probability of Transmission (P T (:::)) which is dependent on
the contention level (Slot Utilization) of the channel [2]:
where Num Att is the number of transmission attempts already performed for a given frame (in-
cluding the current one). Each station, after the Slot Utilization estimate, computes the Probability
of Transmission value, and with the same probability performs a real access to the shared channel.
If the station decides to defer the transmission, it reschedules a new attempt, as in the case of
a collision occurred. The Slot Utilization is interpreted here as the inhibition power of the DCC
mechanism on the accesses, depending on the contention level it represents. Num Att is used in
the DCC mechanism as an indicator of the dynamic level of privilege achieved by a station. The
lowest privilege is given to stations performing, for a given frame, the first transmission attempt,
while the privilege level linearly increases with the number of collisions experienced. The aim is to
privilege old transmission requests, obtaining a queue-emptying behavior for the system. To better
understand what it has been obtained, we can observe the Figure 1. The proposed DCC mechanism0.20.61
Probability
of
Transmission:
P_T(.)
Slot_Utilization
Probability of Transmission (Slot_Utilization, Num_Att)

Figure

1: Probability of Transmission
has the effect to asymptotically reduce the Slot Utilization level induced on the system, when the
congestion level grows indefinitely (Figure 1). If the Slot Utilization asymptotically approximates
the maximum value (One), then the mechanism's effect reduces the Probability of transmission to
Zero, for every station in the system. This means no accesses in the next slot. Hence, a Slot Utilization
equal to One can only be asymptotically obtained over a CW size MAX backoff interval.
This fact can be exploited by opportunely modifying the Probability of Transmission expression,
in order to induce an arbitrary upper limit (SU limit) to the Slot Utilization of the system:
Slot U tilization
SU limit
By adopting the expression (5), the DCC mechanism would perform asymptotically by reducing

Table

1: System parameters
Number of stations from 2 to 200
Max channel
Average Payload size 2.5 and 100 Slot Units
size 4 Slot Units
Header size 2.72 Slot Units
Slot Time 50 -S
SIFS 0.56 Slot Units (28 -S)
DIFS 2.56 Slot Units (128 -S)
Propagation Time (-) ! 1-S
all the probabilities of transmission in correspondence of Slot Utilization values equal to or greater
than the SU limit value. All remaining characteristics of the DCC mechanism are maintained.
4 Power Consumption Analysis
In this section the IEEE 802.11 DCF MAC power consumption is analytically estimated by developing
an approximated model with a finite number, M , of active stations operating in asymptotic
conditions (i.e. stations always have a packet ready for transmission). Once obtained the power
consumption expression, we minimize it to identify the optimal power consumption level for the
given network and load configurations. In the following we assume the physical and protocol pa-
rameters' values reported in Table 1.
Among the considered system's parameters, we also define PTX , indicating the power consumed
(in mW) by the Network Interface (NI) during the transmission phases, and PRX indicating the
power consumed (in mW) by the NI during the reception (or carrier sensing) phases.
Our model is based on the assumption that, for each transmission attempt, a station uses a
backoff interval sampled from a geometric distribution with parameter p, where
and E[B] is the average backoff time (in slot units). In the real IEEE 802.11 backoff algorithm, the
protocol behavior depends on the past history, however, results presented in [5] have shown that
a model of the protocol behavior based on the geometric assumption provides accurate estimates
(at least from a capacity analysis standpoint) of the IEEE 802.11 DCF protocol behavior. In our
model, we also assume that for all stations the payload length of transmitted frames is sampled
from a geometric distribution with parameter q, such that Pfframe payload
The general scenario would require to assume a general distribution of the payload length, with
the estimation of the mean and the variance (using techniques similar to the RTT estimation in [16]).
The assumption of a constant payload distribution implies a constant collision length distribution
characterized by the same parameter q. In order to obtain a more realistic approximated model
we consider the geometric distribution which allows to consider the additional length of a collision
with respect to the average payload. This introduces in the model a characterization of the collision
overhead, which could be easily substituted by the corresponding analytical definition related to
any other considered traffic distribution. The obtained model results robust for each distribution
type of the payload size, and it could be defined for a deterministic distribution, obtaining a close
form definition [3].
To perform our analysis we focus on a tagged station and we observe the system at the end of
each successful transmission of the tagged station. From the geometric backoff assumption, all the
processes which define the occupancy pattern of the channel (i.e. empty slots, collisions, successful
are regenerative with respect to the sequence of time instants corresponding to the
completion of tagged-station successful transmissions. By using the regenerative behavior of the
system, we derive a closed formula for the IEEE 802.11 DCF energy consumption. Specifically, by
defining as the th renewal period the time interval between the th and (j th successful
th virtual transmission time) of the tagged station, from renewal theoretical
arguments [8] it follows that:
where Energy is the energy required to a station to perform a successful transmission, and Energy j
is the tagged station energy consumption during the j-th renewal period (i.e., the j-th successful
transmission). By exploiting (6), the power consumption analysis can thus be performed by studying
the system behavior in a generic renewal period also referred to as virtual transmission time.
When more than one station is active, during a virtual transmission time the tagged station is
involved in a successful transmission and in some collisions (see Figure 2). Specifically, Figure 2
shows that before the tagged station performs a successful transmission, it may experience a number
of collisions and a number of not used slots. A not used slot is both a time interval in which
the transmission medium remains idle due to the backoff algorithm, and a time interval in which
the tagged station does not transmit but the transmission medium is busy due to the transmission
attempts of some of the other stations. During a not used slot the tagged station is in
the receiving state, hence to determine the tagged-station power consumption during this period
Virtual Transmission Time
Tagged_Collision DIFS Tagged_Success
Not_used_slot
Subinterval 1 Subinterval 2 Subint. Nc+1
Subinterval 3

Figure

2: Structure of a virtual transmission time
we need to estimate its length. By denoting with NC the number of collisions experienced by a
tagged station in a virtual transmission time, we can subdivide a virtual transmission time into
Figure 2. NC subintervals terminate with a transmission attempt of the
tagged station which results in a collision, while the last subinterval (i.e., (NC th subinterval)
terminates with a successful transmission of the tagged station. In each subinterval, there are a
number, N not used slot , of not used slots (from the tagged station standpoint) before the transmission
attempt of the tagged station. The number of not used slots in successive subintervals are
i.i.d. random variables sampled from a geometric distribution. Specifically, by considering that the
tagged station transmits in a slot with probability p, it can be shown that
E[N not used slot
To simplify the presentation it is useful to introduce the following random variable definitions,
which make reference to a general th virtual transmission time (we will omit the index j). We
denote with
number of consecutive not used slots during the k \Gamma th subinterval in which the
tagged station is in the receive state
consumption during the N nus k slots of the th subinterval in which
the tagged station is in the receive state
ffl Energy tagged collision k : power consumption experienced by the tagged station while it experiences
the th collision during the th virtual transmission time
ffl Energy tagged success : power consumption experienced by the tagged station when it obtains
the th successful transmission
By exploiting the above definitions, the tagged-station's power consumption (6) can be expressed
as:
(Energy nus n +Energy tagged collision
The above formula (8) can be re-written as:
Energy nus n
Energy tagged collision n ] +E[Energy tagged success
By exploiting the definition of conditioned averages:
Energy nus n
x
Energy nus n
x
Furthermore, by noting that the random variables Energy nus i have the same distribution,
which does not depend on the NC value, and by denoting with E[Energy nus ] their common average
value, it follows that:
Energy nus n
where E[Energy nus used slot ] \Delta E[Energy not used slot ], and E[Energy not used slot ] is the
average power consumption of the tagged station while it senses a sequence of not used slot.
In a similar way we can show that:
Energy tagged collision n
where E[Energy tagged collision ] is the average power consumption of the tagged station while it
experiences a collision during a transmission.
Hence, by exploiting (11) and (12) the formula (9) can be written as:
used slot ] \Delta E[Energy not used slot ]+
where E[NC ]; E[Energy not used slot ]; E[Energy tagged collision ]; E[Energy tagged success ] are derived in
the following lemmas 3 .In this work we don't consider the energy consumed in on/off, Rx/Tx and Tx/Rx transitions of the network
interface. However, our analytical model can be easily extended including these costs in the Formula (13).
Lemma 4.1 Assuming that for each station the backoff interval is sampled from a geometric
distribution with parameter p:
It must be noted that some protocol overheads follow both a collision and a successful trans-
mission: i) the maximum propagation delay - which is required (in the worst case) to sense the
channel idle after a transmission, and ii) the DIFS idle interval to be sensed after a transmission.
Let us denote with Collision and with S the average length of a collision (not involving the tagged
station) and of a successful transmission, including their overheads. Hence, by denoting with - the
maximum propagation delay between two WLAN stations
tagged
where E[Coll not tagged ] (i.e. the average length of a collision not involving the tagged station) has
been derived in [5]:
E[Coll not tagged
A successful transmission in the IEEE 802.11 WLAN includes the time interval between the start
of a transmission which does not experience a collision and the end of the first DIFS which follows
the successful transmission, hence [5]:
where, by denoting with q the parameter of the geometric distribution for the payload size, the
average length of the transmission (payload) in slot units, can be expressed as [5]:
As - is a bound on the propagation delay, it follows the - in Collision and S formulas.
Lemma 4.2 By denoting with p the parameter of the geometric distribution which defines the
backoff interval, the tagged station average power consumption during a not used slot is:
E[Energy not used slot
The analytical study of the average energy required for the frame transmission of a tagged station
does not consider the energy consumption required for the transmission of acknowledgements.
This is acceptable given the fact that acknowledgements are not subject to contention because they
are transmitted immediately after the SIFS following the end of the received frame, see Section 2.
Lemma 4.3 By denoting with p the parameter of the geometric distribution which defines the
backoff interval, the tagged station average power consumption, when it performs a successful
transmission in a slot, is:
E[Energy tagged success
Lemma 4.4 By denoting with p the parameter of the geometric distribution which defines the
backoff interval, and with q the parameter of the geometric distribution which defines the payload
size, the tagged station average power consumption, when it experiences a collision while
is:
E[Energy tagged collision
By assuming that all the times are expressed in SlotTime units, and that the PTX and PRX values
are expressed in mW/SlotTime units, the average energy requirement for a frame transmission
is given (in mJ units) by:
The proofs of previous lemmas can be found in [3]. We define p opt as the value of p (i.e. the average
backoff value) which minimizes the Energy consumption, fixed M , q (i.e. the average payload size)
and the PTX , PRX system's parameters. The p opt values for various combinations of the proposed
parameters have been calculated. In Section 5 we will exploit the results of the analytical model,
to define the PS-DCC mechanism.
5 The PS-DCC Mechanism
In Section 3 we presented a mechanism, named DCC, which could be used to control the contention
level in an IEEE 802.11-like network. Furthermore, we have shown that the DCC approach can
guarantee, given a threshold value SU limit, that the Slot Utilization in the network is bounded
by the threshold value. In Section 4 we defined an approximated analytical model for an IEEE
802.11-like protocol, to study the tuning of the protocol parameters, in order to minimize the power
consumption required to successfully transmit a message. In this section, by putting together the
above results, we define a mechanism named Power Save Distributed Contention Control (PS-DCC),
that can be used to enhance an IEEE 802.11 network from the Power Consumption standpoint.
Specifically, we first show that the optimal parameter setting for power consumption can be mapped
in a boundary value for the network Slot Utilization, named AsymptoticalContentionLimit(ACL).
Then, we define the PS-DCC mechanism by adequately inserting the ACL value into the DCC
mechanism.
In Section 5.1 we show that a strong relationship exists between the Slot U tilization and the
values. Such a relationship is useful in the definition of the PS-DCC mechanism.
5.1 The relationship between Slot U tilization and M \Delta p opt
In the following we investigate the meaning of the (M \Delta p opt ) values, and its relationship with the
Slot U tilization, in a considered system. As we seen in Section 4, we assume M active stations
scheduling their respective transmission attempts in a slot selected following a geometric distribution
with parameter p. Under the optimality assumption it has been obtained the expression which
defines the optimal value p opt of the p parameter. Let us now assume that each station uses the
optimal backoff value p opt . The (M \Delta p opt ) value is an upper bound of the Slot Utilization in the
system, in fact:
Slot U tilization
when p opt is small. Moreover, the negative second order
that M \Delta p opt is a tight upper bound of the Slot U tilization in a system operating with the optimal
p value from the power consumption viewpoint.0.10.30.50.72 20 40
M*Popt
Number of active stations (M)
The M*Popt values with respect to M and Payload
2.5 slots, PTX/PRX=2
100 slots, PTX/PRX=2
2.5 slots, PTX/PRX=100
100 slots, PTX/PRX=100
Standard 802.11 Slot Utilization
DCC Slot Utilization

Figure

3: The M \Delta p opt values and the steady-state Slot Utilization
Given the system's parameters of Table 1, in Figure 3 we compare the optimal Slot U tilization
values (represented by the (M \Delta p opt ) values), with the steady-state Slot U tilization level estimated
(via simulation) in a IEEE 802.11 network with or without the DCC mechanism. The number
of active stations M is variable, representing the variable contention level of the channel. The
considered systems are characterized by the average payload parameter (considered values for the
average payload size: 2.5 and 100 SlotTimes) and the PTX=PRX ratio (considered values: 2
and 100). By adopting the IEEE 802.11 protocol the Slot U tilization level does not depend on
the payload parameter value, while it is connected only to the number of active stations, M .
Results reported in Figure 3 show that in the standard protocol the Slot U tilization values are
generally greater than the optimal values. This result is marked when the mean frame size is large
because the standard protocol produces a Slot U tilization level which
does not depend on the frame size. On the other hand, in the optimal case, the increase of the
frame size (which means an increase in the collision-cost) is balanced by a decrease of the collision
probability, achieved by decreasing the Slot U tilization value. Even if the DCC mechanism [2]
correctly reduces, with respect to Standard 802.11, the Slot U tilization (i.e. the contention level)
under high-load conditions, the results presented in Figure 3 indicate that DCC does not produce
the optimal contention level. Furthermore, these results indicate that an algorithm which wishes
to drive the system to the optimal power consumption must take into consideration the average
value of the payload parameter.
5.2 Theoretical Power Saving limits: the ACL invariant figures
The M \Delta p opt values allow us to define the optimal contention limits to guarantee the power-saving
optimality in the considered systems. Looking at Figure 3 and fixed a given value of payload,
it can be observed that: i) if the PTX/PRX ratio is low (e.g. 2), then the (M \Delta p opt ) product
results quasi-constant for M greater than 2, and ii) if the PTX/PRX ratio is high (e.g. 100), then
the (M \Delta p opt ) values are significantly affected by the value of M . Observation i) (PTX/PRX=2)
means that, fixed the system's parameters of Table 1, it is possible to define a single quasi-optimal
value for the product (M \Delta p opt ), as a function of the payload parameter. Hence, fixed the value
2 for the PTX=PRX ratio, it is possible to define an Asymptotical Contention Limit function
ACL PTX=PRX (payload); payload 2 [2::MPDU ] 5 such that ACL 2 (payload) - (M \Delta p opt ), for the
considered system. This function can be defined off-line depending on the system's parameters,
and represents the indication of the optimal level of Slot Utilization the system should obtain under
the given access scheme, to guarantee the power consumption optimality. This definition does not
depend on M . In the scenario where PTX=PRX is high (e.g. 100), the optimal definition of a
function ACL 100 (payload) - (M \Delta p opt ) is not possible given the significant influence of M . Anyway,
it is possible to define a function ACL 100 (payload) considering only the high values of M (e.g. 100),
and evaluating the overhead introduced by using such a definition in a scenario with few stations.
This analysis has been done [3] and the results have shown that the overhead introduced (with
respect to the optimal power consumption level) is low. This fact is justified because we potentially
introduce a Slot Utilization limit higher than the optimal limit in a scenario with few stations, but
in this case the collision probability is low. This encourages us to assume that such an analytical
definition of the function ACL PTX=PRX (payload) would give results near to the optimality in terms
of power consumption, for each considered system.Here we assume that the payload size of transmitted frames is - 2 Slot Times, and - than the maximum protocol
data unit (MPDU) expressed in slot units.
5.3 The PS-DCC Mechanism
The previous considerations allow us to set the limit for the Slot Utilization in the considered
system, which guarantees a reduced influence of collisions on the power consumption. Specifically,
it results possible to incorporate the optimality in the reaction performed by the DCC mechanism,
by limiting the Slot Utilization by its optimal upper bound Asymptotic Contention Limit (ACL).
Assuming the ACL PTX=PRX (payload) function to be known, in Section 3 we defined the new
Probability of Transmission (P T ) definition which realizes the expected effect:
Slot U tilization
The PS-DCC mechanism requires the payload and the Slot U tilization estimations to determine
the value of the transmission probability (24). Details regarding the implementation
of the estimation algorithms can be found in [3, 4]. The Figure 4 shows an example of the
ACL PTX=PRX (payload) functions obtained for the system considered, for
ACLptx/prx(payload)
Payload size (slot units)
The functions ACLptx/prx(payload)
Analytical
Analytical

Figure

4: The ACL PTX=PRX (payload) functions
6 Simulation results
The behavior of the proposed PS-DCC mechanism has been studied from the Power Consumption
viewpoint, by means of discrete-event simulation. Our interest was to investigate the advantages
of the new PS-DCC mechanism, with respect to the actual Standard 802.11 DCF access scheme
(STND) and the optimal values (OPT). Specifically, we focused our investigation on the average
Power Consumption for a frame transmission, and on the channel Utilization level, when varying
the Contention Level on the transmission channel. The implementation of the Contention Level has
been obtained in each simulation by means of a variable number of active stations with continuous
transmission requirements. The number of stations has been set variable from 2 to 200, in order to
i) stress the system, ii) show the system's scalability, and iii) point out the absence of overheads
introduced. The physical characteristics and parameters of the investigated system are reported
in

Table

1. Simulations consider only two extreme power consumption scenarios with PTX=PRX
According to the studies of TCP traffic [16] we consider either systems with "long
messages" (average payload length of 100 SlotTimes, 1250 Bytes), or systems with "short messages"
(average payload length of 2.5 SlotTimes, Bytes). The RTS/CTS option of the IEEE 802.11
protocol [9] has not been explicity considered in our analysis and simulations because the contention
phase is restricted to the RTS transmission. After the RTS/CTS transmission all stations not
involved in the transmission are frozen. The payload transmission is optimized from the Power
Saving point of view because the contention has been solved. Given these consideration, the
RTS/CTS option is optimized when short messages transmission is optimized. Simulations will
show that the PS-DCC gives advantages with short messages (32 Bytes) that are comparable with
RTS messages. Since the RTS threshold is usually greater than 32 Bytes, the PS-DCC mechanism
is effective also implementing the RTS/CTS option. The effect of Hidden Terminals [9] or any
other spatial inequities have not been considered here. We assume that the only cause of collision
between two or more transmissions is given by the selection of the same slot. This allowed us to
study the problem of the optimal power consumption in random access schemes, with respect to
the contention level influence. If spatial inequities or Hidden Terminals are present in the system,
all the enhancements obtained with the proposed PS-DCC mechanism would be in any case lower
bounded by the Standard 802.11 DCF results. Simulations performed with a deterministic payload
distribution have shown a reduction of the Energy parameters of 8 \Gamma 10% with long messages and
no significant modifications with short messages. All the investigated parameters presented show
their confidence intervals, with a confidence level of 95%. To derive these statistics we adopted the
independent replication techniques.
6.1 Energy required

Figures

5-8 show the average energy required for a successful frame transmission, in a system
characterized by the payload parameter values 2:5 and 100 slots, and two (extreme) values for
the network interface power consumption ratio PTX=PRX (equal to 2 in Figures 5-6, and equal
to 100 in

Figures

7-8). The energy required has been investigated as a function of the variable
number of active stations M , i.e. the congestion level. The analytically estimated optimal values
for the energy consumption are also reported. These optimal values are compared with the steady-state
values obtained by the simulations of the Standard 802.11 DCF access scheme, and by the
simulations of the same access scheme enhanced with the PS-DCC mechanism.200060001000014000
Energy
required
Number of active stations
Energy required with respect to optimum values
OPT: payload=2.5, PTX/PRX=2
PS-DCC: payload=2.5, PTX/PRX=2
STND: payload=2.5, PTX/PRX=2

Figure

5: Energy required: Payload=2.5,
Energy
required
Number of active stations
Energy required with respect to optimum values
OPT: payload=100, PTX/PRX=2
PS-DCC: payload=100, PTX/PRX=2
STND: payload=100, PTX/PRX=2

Figure

Results show that: i) the power consumption in the Standard 802.11 DCF access scheme is
negatively affected by the congestion level, and ii) the PS-DCC mechanism counterbalances the
congestion growth by maintaining the optimality in the power consumption. The energy saving
achieved by PS-DCC is significant and increases with the average frame size. No overheads are
introduced from the power consumption viewpoint in the considered systems, and the PS-DCC
results are very well approximating the optimum values analytically defined (the corresponding
Energy
required
Number of active stations
Energy required with respect to optimum values
OPT: payload=2.5, PTX/PRX=100
PS-DCC: payload=2.5, PTX/PRX=100
STND: payload=2.5, PTX/PRX=100

Figure

7: Energy required: Payload=2.5, PTX/PRX=10010002000300040005000
Energy
required
Number of active stations
Energy required with respect to optimum values
OPT: payload=100, PTX/PRX=100
PS-DCC: payload=100, PTX/PRX=100
STND: payload=100, PTX/PRX=100

Figure

8: Energy required: Payload=100, PTX/PRX=100
lines reported in the figures can not be easily distinguished).
6.2 99-th percentile of Energy required

Figures

show the 99-th percentile of the Energy considered above. This index is significant
about the power-consumption obtained in the "worst case" for a frame transmission in the
considered system. The PS-DCC mechanism allows a significant reduction of this performance in-
dex, with respect to the Standard. This fact also indicates the enhanced queue-emptying behavior
obtained in the considered system, which is related to the priority obtained by old transmission
requirements, and connected to the Num Att parameter.
99-th
percentile
of
the
Energy
required
Number of active stations
Energy: 99-th percentile with
PS-DCC: payload=2.5, PTX/PRX=2
STND: payload=2.5, PTX/PRX=2
PS-DCC: payload=100, PTX/PRX=2
STND: payload=100, PTX/PRX=2

Figure

9: 99-th percentile of Energy
99-th
percentile
of
the
Energy
required
Number of active stations
Energy: 99-th percentile with
PS-DCC: payload=2.5, PTX/PRX=100
STND: payload=2.5, PTX/PRX=100
PS-DCC: payload=100, PTX/PRX=100
STND: payload=100, PTX/PRX=100

Figure

10: 99-th percentile of Energy required: PTX/PRX=100
6.3 Channel Utilization level
We are interested in investigating the effect of the PS-DCC mechanism on the channel utilization
of the considered system. Specifically, we want to compare the channel utilization level when PS-
DCC is adopted in the system, with respect to the optimal channel utilization level defined in
[5].

Figure

11 shows the utilization level of the Standard 802.11 DCF with respect to the optimal
values analytically calculated in [5]. It is immediate to verify that the 802.11 Standard DCF access
scheme suffers the high contention situations that could arise in the system, leading to a low channel
Utilization with respect to the channel Capacity. The use of the PS-DCC mechanism shows its
effectiveness. The utilization curves obtained with PS-DCC, for the different values of PTX=PRX ,
are almost not distinguished, so only one is reported. It results clear that the proposed mechanism
leads to a quasi-optimal behavior of the system also from the Utilization viewpoint. This makes the
power consumption mechanism adopted a conservative method, leading to the quasi-optimality both
for the power saving and for the channel utilization. Only a 2% utilization reduction (overhead) is
introduced in the system with few stations and short frames, with respect to the actual Standard,
as we can see in the direct comparison.0.10.30.50.70.9
Channel
Utilization
Number of active stations
Channel Utilization: PS-DCC, Standard and optimal values
times
times
times
times
times
times

Figure

11: Channel utilization: optimal, Standard 802.11 and PS-DCC values
6.4 The Average Access Delay
About the user's performance indexes investigation, the average MAC access delay has been re-
ported. The average MAC access delay represents the time required between the first transmission
scheduling of a given frame, and the completion of its successful transmission. In the Figure 12
it has been reported the simulation data of the Mean Access Delay, with respect to the variable
contention level (M) and the average payload size of transmitted frames. It results that the new
PS-DCC mechanism leads to a reduction of the Mean Access Delay with respect to the actual
Standard access scheme. No overheads are introduced, confirming the adaptive behavior of the
proposed mechanism. The PS-DCC mechanism, with the implemented priority effect connected to
the Num Att value, makes stations with high Num Att values transmitting with high probability
of success, enhancing the fairness and the queue-emptying behavior of the system. Moreover, the
PS-DCC leads to a linear growth of the access delay, with respect to the number of active stations
in the system, which outperforms the Standard access scheme.
MAC
access
delay
(Slot
units)
Number of active stations
Average MAC access delay: PS-DCC vs. Standard values
times
times
times
times

Figure

12: Average MAC access delay
6.5 The dynamic Power Consumption
It is interesting to observe how the system behaves in transient scenarios. Figure 13 reports the
simulation traces of the average energy required for a frame transmission with and without the
PS-DCC mechanism. Simulation data are obtained by considering a system in steady-state, with
100 stations initially active. After some time, a burst of additional 100 stations activates, causing
the contention level to grow up, then it disappear. The additional burst occurs twice during the
simulation.10003000500070000 50 100 150 200 250
Average
Energy
Consumed
Time (1024 slot units)
Dynamic Power Consumption
PS-DCC, 100+100 stations
optimal energy required with 100 stations
optimal energy required with 200 stations
STND, 100+100 stations

Figure

13: Dynamic Energy requirements vs. contention level
The figure shows how the systems react to the contention variations under the power consumption
viewpoint. The Standard system enhanced with the PS-DCC mechanism obtains a lower Energy
requirement for the frame transmissions, with respect to the Standard system. The PS-DCC
mechanism is fast to adapt to new contention scenarios. Moreover, as expected from previous
results, the PS-DCC mechanism maintains an average Energy requirement which is close to the
optimal value in all contention conditions analyzed.
7 Conclusions and future research
We propose and evaluate a Power Save, Distributed Contention Control (PS-DCC) mechanism
which is effective in implementing a distributed and adaptive contention control, to guarantee the
optimal power consumption of a random-access MAC protocol for a wireless network. Specifically,
we considered the IEEE 802.11 DCF access scheme [9] as a testbed for our analysis. The PS-DCC
mechanism requires no additional hardware with respect to the Standard, but given the scarce
flexibility of the Standard implementations, it will be implementable only as a new protocol, in a
new release of the Standard devices or in devices with software radio technologies. The proposed
mechanism is completely distributed, and it can be tuned, for the power consumption optimality,
on the basis of an analytical model definition. The proposed mechanism dynamically adapts the
system to the optimal contention level by means of the Slot Utilization and the average Payload size
estimates. Each estimate is obtainable with low cost and with no overheads. The system maintains
a stable behavior, both during the steady-state congested phases and during bursty arrivals of
transmission requirements. The priority effect implemented by the PS-DCC mechanism, connected
to the Num Att parameter, allows a fair reduction of contention, and enhances the queue-emptying
behavior of the system. Simulations show that the proposed mechanism introduces a quasi-optimum
channel utilization and power consumption in the considered systems, without significant affection
of the contention level. Other system parameters like the Mean Access Delay, the 99-th percentile
of the power consumed, the risk of starvation and the transient behavior have been analyzed and
resulted enhanced by our mechanism, without overheads introduced. Future research involves the
study of further optimization connected to different classes of frame sizes. It also results possible
to obtain an external priority mechanism [2], which would allow each station to self-determine a
greater priority in the access right to the channel, without any kind of negotiation. The external
priority mechanism could be useful if adopted with RTS/CTS messages.
acknowledgements
The authors would like to thanks the anonymous referees that with their comments contribute to
improve the quality of the paper.



--R

"Toward Power-Sensitive Network Architectures in Wireless Communications: Concepts, Issues and Design Aspects"
"Design and Performance Evaluation of a Distributed Contention Control (DCC) Mechanism for IEEE 802.11 Wireless Local Area Networks"
"A Distributed Mechanism for Power Saving in IEEE 802.11 Wireless LANs"
"Design and Performance Evaluation of an Asymptotically Optimal Backoff Algorithm for IEEE 802.11 Wireless LANs"
''IEEE 802.11 Wireless LAN: Capacity Analysis and Protocol Enhancement
"Stability of Binary Exponential Backoff "
"Analysis of Backoff Protocols for Multiple Access Chan- nels"
"Stochastic models in operations research"
Wireless MAC and Physical Layer Working Group
"Wireless Computing"
"Software Strategies for Portable Computer Energy Management"
"A Short Look on Power Saving Mechanisms in the wireless LAN Standard Draft IEEE 802.11"
"Mobile Power Management for Wireless Communication Networks"
"A Portable Multimedia Terminal"
"Measuring and Reducing Energy Consumption of Network Interfaces in Hand-Held Devices"
"Power-Saving Mechanisms in Emerging Standards for Wireless LANs: The MAC Level Perspective"
"Energy Management in Wireless Communication"
--TR
On the stability of the Ethernet
TCP/IP illustrated (vol. 1)
Mobile wireless computing: challenges in data management
Analysis of Backoff Protocols for Mulitiple AccessChannels
Mobile power management for wireless communication networks
Design and performance evaluation of a distributed contention control(DCC) mechanism for IEEE 802.11 wireless local area networks
Design and Performance Evaluation of an Asymptotically Optimal Backoff Algorithm for IEEE 802.11 Wireless LANs

--CTR
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power saving;IEEE 80211;analytical modelling;simulation;wireless networks