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A Clean-Slate Architecture for Reliable Data Delivery in Wireless Mesh Networks

05 Apr 2009-pp 2565-2570

TL;DR: A clean-slate architecture for improving the delivery of data packets in IEEE 802.11 wireless mesh networks is introduced, proposing a unitary layer approach that combines both routing and transport functionalities in a single layer.

AbstractIn this paper, we introduce a clean-slate architecture for improving the delivery of data packets in IEEE 802.11 wireless mesh networks. Opposed to the rigid TCP/IP layer architecture which exhibits serious deficiencies in such networks, we propose a unitary layer approach that combines both routing and transport functionalities in a single layer. The new Mesh Transmission Layer (MTL) incorporates cross-interacting routing and transport modules for a reliable data delivery based on the loss probabilities of wireless links. Due to the significant drawbacks of standard TCP over IEEE 802.11, we particularly focus on the transport module, proposing a pure rate-based approach for transmitting data packets according to the current contention in the network. By considering the IEEE 802.11 spatial reuse constraint and employing a novel acknowledgment scheme, the new transport module improves both goodput and fairness in wireless mesh networks. In a comparative performance study, we show that MTL achieves up to 48% more goodput and up to 100% less packet drops than TCP/IP, while maintaining excellent fairness results.

Topics: Wireless mesh network (66%), IEEE 802.11s (66%), Goodput (61%), Network packet (59%), Wireless network (59%)

Summary (2 min read)

Introduction

  • Within this context, wireless mesh networks possess unique characteristics compared with the wired Internet, raising key challenges which must be addressed for achieving a reliable operation of such networks.
  • Opposed to the rigid TCP/IP stack, the authors design a unitary layer architecture, in which the routing and transport functionalities are both merged in a single layer.
  • While the routing module relies on such probabilities to determine the best route to a destination, the transport module integrates them for determining the optimum transmission rate of data packets.

A. Unitary Layer Architecture

  • Due to such deficiencies associated with the classic TCP/IP architecture the authors introduce a new unitary layer design, in which they merge the transport and routing functionalities into a single Mesh Transmission Layer (MTL).
  • By sharing information between routing and transport on the current condition of wireless links, a more reliable end-to-end data delivery can be achieved.
  • On the other hand, the transport module provides the routing module with information on end-to-end connections to maintain information on accessibility of nodes in the routing table.
  • Thereby, the authors focus on the novel congestion control algorithm employed in the transport module since the standard TCP congestion control accounts for the most significant performance deficiencies in IEEE 802.11 mesh networks ([4], [7]).

B. Routing Module

  • The routing module implements proactive route determination similar to the Optimized Link State Routing Protocol (OLSR) [2].
  • It uses HELLO and Topology Control (TC) messages to proactively discover and disseminate link state information throughout the mesh network.
  • Such probability is derived by calculating the expected transmission count (ETX) [3] at each link: 1 = ⋅f r ETX d d , (1) where df and dr denote the forward and reverse packet delivery ratios, respectively.
  • Such delivery ratios are determined using probe packets of a fixed size that are broadcasted by each node in fixed time intervals.
  • Hence, in case a peer is not responding, the routing module is notified, and the corresponding peer is temporarily labeled as inaccessible for data exchange.

C. Transport Module

  • The transport module within the Mesh Transmission layer is responsible for a reliable data transport between end-to-end hosts in the mesh network.
  • This link layer contention may lead to packet drops due to the hidden and exposed terminal problems [6].
  • The adaptive transmission rate accounts for the spatial reuse constraint of IEEE 802.11 and proactively identifies incipient congestion, i.e. before congestion-related losses actually occur.
  • Once the requested EGN has been received, the sender transmits the held packet and empties the entire buffer.
  • In order to use Rmax as an upper bound for the transmission rate, the authors need to measure the 4-hop propagation delay FHD of the data packets.

A. Chain Topology

  • The first topology the authors consider is an equally spaced chain comprising h+1 nodes (h hops) with a single FTP flow and a 200m inter-node distance.
  • TCP packets traverse along the chain from the leftmost node (i.e., the source) to the rightmost node (i.e., the destination).
  • Figures 2 and 3 show the goodput as well as the number of packets dropped at link layer versus number of hops for MTL and TCP/IP, respectively.
  • Goodput vs. simulation time for TCP/IP, also known as Parallel chains topology.

B. Parallel Chains Topology

  • To evaluate the fairness of MTL versus TCP/IP the authors consider a parallel chains topology comprising two parallel chains, each consisting of 6 nodes with a 200m inter-node distance.
  • The distance between both chains is 400m, which means that they lie within each other's interference range.
  • Figure 4 shows the goodput achieved by each flow as well as the aggregate goodput over both.
  • The authors can observe that while MTL shares the available bandwidth equally between both flows, TCP/IP favors flow 1 which achieves over 100% more goodput than flow 2.
  • The authors choose such an interval in the middle of the simulation to ensure that both FTP flows have already reached their steady-states.

C. Grid Topology

  • As a more complex topology, the authors consider a 6x6 grid (36 nodes) with multiple FTP flows.
  • This simulates a scenario where multiple users perform several downloads back to back.
  • Figure 7 shows the cumulative distribution function (CDF) of the corresponding individual goodput.
  • The authors introduced the Mesh Transmission Layer (MTL), a novel clean-slate architecture for reliable data delivery in wireless mesh networks.
  • A comparative performance study with MTL versus the classic TCP/IP architecture using several network topologies showed that MTL achieves up to 48% more goodput and up to 100% less packet drops.

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A Clean-Slate Architecture for Reliable Data Delivery
in Wireless Mesh Networks
Sherif M. ElRakabawy and Christoph Lindemann
University of Leipzig
Department of Computer Science
Johannisgasse 26
04103 Leipzig, Germany
AbstractIn this paper, we introduce a clean-slate architecture
for improving the delivery of data packets in IEEE 802.11
wireless mesh networks. Opposed to the rigid TCP/IP layer
architecture which exhibits serious deficiencies in such networks,
we propose a unitary layer approach that combines both routing
and transport functionalities in a single layer. The new Mesh
Transmission Layer (MTL) incorporates cross-interacting routing
and transport modules for a reliable data delivery based on the
loss probabilities of wireless links. Due to the significant
drawbacks of standard TCP over IEEE 802.11, we particularly
focus on the transport module, proposing a pure rate-based
approach for transmitting data packets according to the current
contention in the network. By considering the IEEE 802.11
spatial reuse constraint and employing a novel acknowledgment
scheme, the new transport module improves both goodput and
fairness in wireless mesh networks. In a comparative
performance study, we show that MTL achieves up to 48% more
goodput and up to 100% less packet drops than TCP/IP, while
maintaining excellent fairness results.
Keywords: Congestion control, IEEE 802.11, TCP, Wireless
network protocols
I. INTRODUCTION
Since the emergence of the IEEE 802.11 standard [8],
wireless networks have become enormously popular. The
freedom of wireless Internet access provided by IEEE 802.11
has been mushrooming the number of wireless hotspots around
the globe as a rapidly rising trend. Besides conventional single-
cell wireless hotspots, wireless mesh networks ([1], [11])
comprising multiple IEEE 802.11 nodes have gained increased
attention in recent years, both in academia and industry. Such
networks typically aim to provide cost-efficient Internet access
with minimal infrastructure expenditure, which makes it
particularly attractive for suburban areas with little or no
broadband availability. Mesh nodes, which are typically
wireless routers mounted on buildings, form a multihop
backbone to forward packets hop-by-hop between the Internet
and other mesh nodes. Mesh participants with mesh gateways,
which have direct access to the Internet, can share it with other
participants.
Within this context, wireless mesh networks possess unique
characteristics compared with the wired Internet, raising key
challenges which must be addressed for achieving a reliable
operation of such networks. Opposed to wired networks, in
IEEE 802.11 networks, the wireless channel is a scarce
resource shared among nodes within their radio range.
Furthermore, channel capture, hidden and exposed terminal
effects, and the IEEE 802.11 medium access control constitute
features of wireless mesh networks not present in a wired IP
network. Along with the unique characteristics of the wireless
channel, mobility-related problems can occur when mobile
mesh clients move at a certain speed, resulting in dropped
packets at link layer. In such a case, standard TCP interprets
the packet loss as a sign of congestion and reduces throughput.
One of the key causes of such deficiencies in wireless mesh
networks is the fact that the current TCP/IP protocol stack has
been originally designed for wired IP networks. Specifically,
the strict layered architecture of the TCP/IP stack has proven to
be inflexible due to the exclusive restriction of crucial
information about the network on the respective layer. While
assigning a special service to each layer reduces the complexity
of the network design, other layers are perceived as black
boxes, holding critical information about the network state.
Such inaccessible information is required by all layers to adapt
to the special characteristics of wireless mesh networks such as
route breaks and lossy links.
Due to such fundamental deficiencies in the basic design of
the classic TCP/IP stack, it seems more reasonable to consider
designing a new network stack from scratch rather than
improving the existing one incrementally. Such a trend, which
is referred to as clean-slate network design, has been becoming
increasingly popular within the research community ([13], [17],
[18]). To this end, we propose a clean-slate architecture for
reliable data delivery in wireless mesh networks. Thereby, we
focus on the routing and transport functionalities within the
network stack in order to avoid modifications of the widely
deployed IEEE 802.11 protocol. Opposed to the rigid TCP/IP
stack, we design a unitary layer architecture, in which the
routing and transport functionalities are both merged in a single
layer. The new layer, which is denoted as the Mesh
Transmission Layer (MTL), incorporates a routing and a
transport module which aim to achieve reliable packet delivery
using feedback information from the network. We particularly
focus on the aspect of congestion control within our newly
designed Mesh Transmission Layer. Opposed to classic TCP,
the new transport module operates purely rate-based, omitting
the congestion window which has been criticized in several
works ([4], [9]) for causing unfairness between competing
flows. Besides the fairness problem, the new transport module
also considers the spatial reuse constraint of IEEE 802.11,
which significantly degrades the end-to-end goodput over
multiple hops. Similar to [3], the new layer MTL determines
the quality of the wireless links based on their loss

probabilities. Such loss probabilities are then adopted for both
the routing and transport modules. While the routing module
relies on such probabilities to determine the best route to a
destination, the transport module integrates them for
determining the optimum transmission rate of data packets. In a
comparative performance study, we show that MTL achieves
up to 48% more goodput and up to 100% less packet drops
than TCP/IP while maintaining excellent fairness results.
The remainder of this paper is organized as follows. Section
II summarizes related work on challenges in wireless mesh
networks, specifically considering the default TCP/IP stack. In
Section III we introduce our clean-slate architecture for reliable
data delivery, while providing a comprehensive performance
study of MTL versus the standard TCP/IP stack in Section IV.
Finally, concluding remarks are given.
II. R
ELATED WORK
Although most of the research in the networking field still
builds on the classic TCP/IP architecture, the trend is
increasingly moving towards the clean-slate approach. In [13],
Feldmann gave an overview on the challenges that must be
addressed for a reliable future Internet, and discussed the clean-
slate approach as a possible solution. Scott et al. [15] addressed
the problem of the current TCP/IP architecture in
infrastructure-less mobile environments. The authors
introduced a non-layered mobile architecture in pocket
switched networks to support reliable communication in mobile
environments. In [9], the authors proposed ATP, a transport
protocol specially tailored for multihop wireless networks. ATP
employs pure rate-based transmission of packets, where the
transmission rate is determined using feedback from
intermediate nodes along the path. In contrast to [15], we focus
on the reliable data delivery through effective congestion
control in static wireless mesh networks. Opposed to [9], our
approach considers a unitary layer architecture rather than an
autonomous transport protocol.
Several congestion control mechanisms have been proposed
for wireless mesh networks. In [6], Fu et al. pointed out the
hidden terminal problem in wireless multihop networks and
experimentally showed that for a chain topology the optimal
windows size, for which TCP achieves best throughput, is
roughly given by 1/4 of the hop count of the path. Gambiroza
et al. [7] studied TCP performance and fairness in wireless
mesh networks comprising numerous wireless relay nodes
(there called Transit Access Points, TAPs) and a connection to
the wired Internet. They introduced TAP-fairness to
characterize the idealized goodput and fairness objective for
such networks, and proposed a distributed link layer algorithm
for achieving TAP-fairness among active TCP flows. Shi et al.
[12] addressed the unfairness problem which occurs between
one-hop flows contending with two-hop flows for gateway
access. The authors proposed a solution based on a contention
window policy in IEEE 802.11e. Chen et al. [14] proposed a
cross-layer approach for congestion control, routing, and
scheduling in multihop wireless networks. The authors
proposed an algorithm which is based on a utility maximization
problem with predefined rate and scheduling constraints. Our
work builds on findings in [4], in which TCP with Adaptive
Pacing has been introduced. The results showed that adaptive
pacing yields significant performance improvement with
respect to standard TCP. Opposed to previous approaches for
congestion control, we propose a novel unitary layer
architecture in which we combine routing and rate-based
congestion control rather than incrementally building on the
existing TCP congestion control algorithm.
Path metrics based on link qualities have been studied in
the context of routing protocols for wireless mesh networks
([3], [16]). In [3], the authors introduced the Expected
Transmission Count (ETX) as a new metric for multihop
wireless networks. The metric considers the packet delivery
probability at each link and determines the path with the
minimum loss rate and highest throughput. Draves et al. [16]
introduced the Expected Transmission Time (ETT) metric,
which considers the bandwidth of a link along with its ETX
weight. In this paper, we incorporate the ETX metric in our
Mesh Transmission Layer. Specifically, we use ETX
measurements both for routing decision as well as for adjusting
the transmission rate of data packets according to the current
contention on the path.
III. C
LEAN-SLATE DATA DELIVERY
A. Unitary Layer Architecture
As discussed in [13] and [17], the classic TCP/IP layer
model faces significant challenges coupled with future Internet
technologies such as wireless mesh networks. In particular, the
TCP/IP layer architecture is inflexible due to the restriction of
useful information on certain layers, and does not consider the
unique characteristics of IEEE 802.11 such as the spatial reuse
constraint [6] and unfairness problems [10]. Specifically the
congestion control algorithm of TCP at layer 4 possesses
serious deficiencies over IEEE 802.11 mesh networks, since it
considers each network as a black box and thus provokes
packet loss to identify spare bandwidth. Thus, in this paper, we
focus on congestion control and introduce a novel transport
module in Section III.C that considers the unique challenges of
IEEE 802.11.
Due to such deficiencies associated with the classic TCP/IP
architecture we introduce a new unitary layer design, in which
we merge the transport and routing functionalities into a single
Mesh Transmission Layer (MTL). As shown in Figure 1,
routing and transport are embedded as modules within MTL.
Such unitary architecture enables embedded exchange of
feedback information of the network between both modules
rather than considering the network as a black box. The
background of such a merge is the fact that the performance of
both routing and transport over IEEE 802.11 mesh networks
depend on the same key factor, which is the quality of the
wireless links. By sharing information between routing and
transport on the current condition of wireless links, a more
reliable end-to-end data delivery can be achieved. Similar to
Figure 1. The Mesh Transmission Layer comprising a transport and a routing
module

[3], link quality is determined by measuring the packet loss
probability at each link. The routing module uses information
on link quality for route determination and simultaneously
shares such information with the transport module, which
adjusts its packet transmission rate accordingly. On the other
hand, the transport module provides the routing module with
information on end-to-end connections to maintain information
on accessibility of nodes in the routing table.
Subsequently, we discuss the detailed operation of the
routing and transport modules and how they interact to achieve
reliability. Thereby, we focus on the novel congestion control
algorithm employed in the transport module since the standard
TCP congestion control accounts for the most significant
performance deficiencies in IEEE 802.11 mesh networks ([4],
[7]).
B. Routing Module
The routing module implements proactive route
determination similar to the Optimized Link State Routing
Protocol (OLSR) [2]. It uses HELLO and Topology Control
(TC) messages to proactively discover and disseminate link
state information throughout the mesh network. HELLO
messages are broadcasted to determine 1-hop and 2-hop
neighbors and add them to the routing table. TC messages are
propagated throughout the network to disseminate such
neighbor information. Besides determining and maintaining the
best routes between mesh nodes in a network, the routing
module within the Mesh Transmission Layer is also
responsible for providing the transport module with crucial
information on the quality of the wireless links.
The quality of the wireless links, which is used for route
maintenance and shared with the transport module, is
determined by computing the packet delivery probability at
each link. Such probability is derived by calculating the
expected transmission count (ETX) [3] at each link:
1
=
fr
ETX
dd
, (1)
where d
f
and d
r
denote the forward and reverse packet
delivery ratios, respectively. The forward delivery ratio
describes the probability that a packet is successfully forwarded
over a link from sender to receiver, whereas the reverse
delivery ratio describes the probability that this packet is
correctly acknowledged. Such delivery ratios are determined
using probe packets of a fixed size that are broadcasted by each
node in fixed time intervals. Each node remembers the number
of probe packets it correctly receives at each link within the last
x seconds, and calculates the ratio between the received and the
total number of probe packets sent accordingly. The ETX of a
route comprises the sum of the ETX values of all links on the
route.
Along with the ETX metric, the routing module also relies
on information from the transport module on end-to-end
connections for quick updates of the routing table. Specifically,
as the transport module is responsible for maintaining end-to-
end transport connections between end hosts, it notifies the
routing module about the accessibility of current connected
peers. Hence, in case a peer is not responding, the routing
module is notified, and the corresponding peer is temporarily
labeled as inaccessible for data exchange. In case TC messages
validate that the peer is not part of the network, it is deleted
from the routing table. Such an inaccessibility label is helpful
to inform the user/application about the exact status of other
peers.
C. Transport Module
The transport module within the Mesh Transmission layer
is responsible for a reliable data transport between end-to-end
hosts in the mesh network. The new module overcomes the
well-known deficiencies of classic TCP in IEEE 802.11
multihop wireless networks, which arise from TCP’s
congestion control algorithm. First, TCP’s window-based
congestion control leads to packet bursts when received
acknowledgments trigger the transmission of several data
packets, e.g., when receiving a cumulative ACK. Due to the
spatial reuse constraint of the wireless channel in IEEE 802.11
multihop wireless networks [6], neighboring nodes cannot
transmit simultaneously. Thus, packet bursts result in increased
contention on the wireless channel. This link layer contention
may lead to packet drops due to the hidden and exposed
terminal problems [6]. Second, TCP’s congestion control
algorithm relies on packet losses as indication of congestion
and, thus, provokes losses in order to identify spare bandwidth.
In IEEE 802.11 multihop wireless networks, this behavior
results in increased congestion, causing significant
performance degradation for TCP [10].
To overcome the deficiencies stated above, we propose a
purely rate-based congestion control algorithm rather than
employing window-based mechanisms. The adaptive
transmission rate accounts for the spatial reuse constraint of
IEEE 802.11 and proactively identifies incipient congestion,
i.e. before congestion-related losses actually occur. The novel
transport module is packet-based and uses sequence numbers to
maintain in-order packet delivery. Since it operates purely rate-
based, neither a congestion window nor related window-
adjustment algorithms such as slow start and congestion
avoidance are required. Explicit Gap Notifications are
employed in the new transport algorithm to achieve reliability
and save bandwidth.
1) Explicit Gap Notifications
A key feature of the new transport module is that it uses
Explicit Gap Notifications (EGNs) rather than conventional
acknowledgments to achieve reliability. EGNs are packets
transmitted from receiver to sender in order to explicitly
indicate gaps within the data packet flow rather than sending a
positive acknowledgment for each correctly received packet. A
single EGN packet is cumulative since it can report more than
one undelivered data packet. This saves a fair amount of costly
bandwidth and improves end-to-end goodput.
Using the EGN mechanism, the sender maintains a sending
buffer of a fixed size, 200 kbytes by default, in which it saves
the packets already transmitted. The reason for such a buffer is
to be able to retransmit dropped packets upon receiving one or
more EGNs. In case the sending buffer gets full while no EGN
has been received within the lifetime of the current buffer, the
sender requests an explicit EGN by purposely holding back a
data packet. Once the requested EGN has been received, the
sender transmits the held packet and empties the entire buffer.
The purpose of such explicit request is to make sure that the
receiver is still alive and replying, and that all previous data
packets have been successfully received.

2) Rate-based Congestion Control
a) Considering Link Contention
The classic TCP congestion control algorithm saturates the
link by increasing the load issued into the network until a
packet loss is detected, where such packet loss identifies
congestion. Upon congestion, the transmission rate is throttled
to empty overfilled queues on the routers and is then increased
again until a new packet loss is detected and so forth.
Considering the characteristics of IEEE 802.11 multihop
networks, it becomes obvious that a transport protocol which
actually provokes packet drops to get network feedback has to
suffer from poor performance. Thus, our congestion control
algorithm identifies high contention on the network path of the
transport connection and proactively throttles the transmission
rate before losses occur.
In order to identify contention on the path between sender
and receiver, we consider the packet loss probability at each
link on the path. Such loss probability is directly correlated to
the level of contention at the wireless links and is thus a
reliable measure. First we consider the loss probability of a
wireless link, p
link
, as a function of the forward and reverse loss
probabilities p
f
and p
r
, respectively:
(1 )= +−
link f f r
p p pp
(2)
In other words, a packet is considered lost in case either the
packet itself is dropped on the forward path (i.e. p
f
), or the
packet is successfully transmitted but the corresponding link
layer acknowledgment is dropped on the reverse path (i..e.
(1- p
f
) p
r
). To prevent a redundant computation overhead, we
derive p
link
from ETX:
(1 )
(1 ) (1 (1 ))(1 )
1
1
1
= +−
= +−−
=
=
link f f r
f fr
fr
p p pp
d dd
dd
ETX
(3)
In order to account to the loss probability of a given path
between a sender A and a receiver B, we consider the loss
probability at the bottleneck-link of the path, i.e. the link with
the highest loss probability. We do so to adjust the transmission
rate at the sender according to the most congested link on the
path in order to avoid packet drops and degraded goodput. We
define the maximum loss probability
,
max
<>AB
P
on a path of i links
as:
,
max
1
max(1 )
<>
=
AB
i
i
P
ETX
, (4)
where ETX
i
denotes the ETX value at link i. In Subsection
C.2.C we show how
,
max
<>AB
P
is considered for the computation of
the final packet transmission rate.
b) Considering the Spatial Reuse Constraint
Besides the measure of contention on the network path, the
derivation of an appropriate transmission rate should also
account for the spatial reuse constraint of IEEE 802.11
multihop wireless networks [6]. That is, due to the hidden
terminal effect, in a chain topology where the transmission
range of each node is about 250m and the interference and
carrier sensing ranges are 550m, a TCP sender at node i can
only transmit a packet successfully as soon as node (i+3) has
finished its transmission in order to avoid collisions. We refer
to the time elapsed between transmitting a TCP packet by node
i and receiving the packet at node (i+4) as the 4-hop
propagation delay (FHD). Such hidden terminal effects depend
mainly on the characteristics of the network interface as well as
the adopted routing protocol. First, the network interface
determines the ratio between the transmission range and the
interference range. Due to the settings of the network interface
considered in this paper, hidden terminals along the path can be
avoided if a transmitting node delays the transmission of a data
packet until the previously sent packet is forwarded 4 times.
Thus, we consider FHD for the calculation of the transmission
rate.
If we assume a network with perfect scheduling at link
layer, the maximum spatial reuse with minimum collisions
would be achieved with a transmission rate R
max
=1/FHD.
Following [6], an upper bound for the capacity of a path with h
hops in an IEEE 802.11 multihop wireless network is given by
h/4 packets. Let T
one-way
denote the time a packet traverses from
the sender to the receiver. This quantity can be computed as
/4
one way
T FHD h
=
. Subsequently, the number of packets in
flight on the way from sender to receiver with a sender’s
transmission rate of R
max
, is given by:
max
1
# packets in flight
4
one way
RT h
=⋅=
(5)
Thus, the number of packets in flight transmitted with the
maximum transmission rate R
max
reflects the maximum
capacity of the network path. Note that for network paths with
h < 4, R
max
is computed using the h-hop propagation delay
instead of the 4-hop propagation delay. Without loss of
generality and for ease of exposition, we consider network
paths with h
4 in the subsequent discussion.
In order to use R
max
as an upper bound for the transmission
rate, we need to measure the 4-hop propagation delay FHD of
the data packets. To prevent extra control traffic overhead, we
estimate FHD based on end-to-end round-trip-times (RTT)
measurements at the sender. The RTT is composed of the sum
of the delay experienced by the data packet on the way from
the sender to the receiver and the delay experienced by the
Explicit Gap Notification (EGN) packet sent from the receiver
to the sender. Each of these delays comprise the time to
forward the packet over h hops, where each forwarding
requires a queuing delay t
q
and transmission delays t
data
, and
t
EGN
, respectively. The link layer retransmissions and backoff
are implicitly considered in the queuing delay t
q
. Using the
measured RTT, we get:
( ) ( )
=+++
q data q EGN
RTT ht t ht t
(6)
Solving for t
q
while using t
data
= s
data
/b and t
EGN
= s
EGN
/b for
a bandwidth b and data/EGN packet sizes s
data
and s
EGN
, we
derive the average queuing delay as:
(7)
Subsequently, we can estimate the 4-hop propagation delay
of the transport data packet:

42

=+= +


data data EGN
q
s ss
RTT
FHD t
b hb
(8)
This estimation requires that the sender knows about the
number of hops on the network path to the receiver and the
bandwidth of the wireless network interface. Since this
information is available from the routing module and the link
layer, no extra overhead is required.
c) Computing the Transmission Rate
Since the computation of the adaptive transmission rate
should account for both the current contention on the network
path and the spatial reuse constraint, we incorporate the
maximum path loss probability
,
max
<>AB
P
and FHD in the
transmission rate formula. Recall that a rate of R
max
=1/FHD
specifies an upper bound for the achievable goodput under
optimal conditions, i.e. with theoretically perfect scheduling
and no contention. In order to adaptively throttle the
transmission rate R according to the current degree of
contention, we use
,
max
<>AB
P
as an additional decay factor:
,
max
1
(1 )
<>
=
⋅+
AB
R
FHD P
(9)
In favor of a stable transmission rate, we average the
measured 4-hop propagation delay samples using the
exponentially weighted moving average (EWMA) with
averaging weight
α
:
(1 )= +
old
FHD FHD FHD
αα
(10)
As validated by our simulations, a suitable value for
α
has
proven to be 0.7.
IV. P
ERFORMANCE EVALUATION
To evaluate the performance of our Mesh Transmission
Layer (MTL), we conduct a performance study using ns-2 [5],
in which we compare the performance of MTL with the classic
TCP/IP stack. As a transport protocol for the TCP/IP stack we
deploy the widely used TCP NewReno, whereas for routing the
standard OLSR protocol with ETX support is adopted. In all
experiments, except for experiments showing transient
behavior, we conduct steady-state simulations starting with an
initially idle system. In each run, we utilize FTP connections
until 55,000 packets are successfully transmitted, and split the
output of the experiment in 11 batches, each 5,000 packets in
size. The first batch is discarded as initial transient. The
considered performance measures are derived from the
remaining 10 batches with 95% confidence intervals by the
batch means method.
In ns-2, all link-layer layer parameters of IEEE 802.11 are
configured to provide a transmission range of 250m and a
carrier sensing range as well as an interference range of 550m.
The RTS/CTS handshake is disabled and we consider a channel
bandwidth of 54 Mbit/s according to IEEE 802.11g while
setting the size of transport data packets (both for TCP and
MTL) to 1,460 bytes.
A. Chain Topology
The first topology we consider is an equally spaced chain
comprising h+1 nodes (h hops) with a single FTP flow and a
200m inter-node distance. TCP packets traverse along the chain
from the leftmost node (i.e., the source) to the rightmost node
(i.e., the destination). Nodes in the chain are positioned such
that only direct neighbors can communicate with each other
over one hop. Figures 2 and 3 show the goodput as well as the
number of packets dropped at link layer versus number of hops
for MTL and TCP/IP, respectively. Figure 2 shows that MTL
achieves up to 48% more goodput than TCP/IP (e.g. at 2 hops).
Figure 2. Chain topology: Goodput vs. number of
hops
Figure 3. Chain topology: Number of packet
drops at link layer vs. number of hops
Figure 4. Parallel chains topology: Goodput and
fairness
Figure 5. Parallel chains topology: Goodput vs.
simulation time for MTL
Figure 6. Parallel chains topology: Goodput vs.
simulation time for TCP/IP
Figure 7. Grid topology: Cumulative distribution
function (CDF) of the goodput between each pair
in the network (Average MTL: 8,755 kbit/s;
Average TCP/IP: 6,386 kbit/s)

Citations
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Journal ArticleDOI
TL;DR: The numerical results show that the proposed clean-slate architecture outperforms the traditional layered architecture with respect to the throughput efficiency for both error control schemes.
Abstract: In this paper, VANET applications have been classified according to their purpose. Furthermore, a clean-slate architecture specifically designed for VANETs has been introduced. The proposed non-layered context-aware ubiquitous architecture adapts dynamically to changes, is oriented to services (VANET applications) and has a flexible structure. The vehicle and environmental context-aware information as well as the VANET communication characteristics are designed for the proper operation of the applications. In addition, the performance of Automatic Repeat Request and Forward Error Correction (FEC) block codes with respect to the throughput efficiency has also been analyzed for a VANET following the proposed clean-slate architecture. The numerical results show that the proposed clean-slate architecture outperforms the traditional layered architecture with respect to the throughput efficiency for both error control schemes. FEC block codes are able to maintain high throughput efficiency over longer distances because the hop length extension technique is applied.

9 citations


Cites background from "A Clean-Slate Architecture for Reli..."

  • ...In [6], the clean-slate architecture for wireless mesh networks is explained....

    [...]


Journal ArticleDOI
TL;DR: The numerical results show that the proposed role-based architecture outperforms the traditional layered architecture with respect to the throughput efficiency for all error control schemes.
Abstract: Highlights? We develop a flexible role-based architecture for Body Sensor Networks (BSNs) ? We analyze the performance of Automatic Repeat Request (ARQ), Forward Error Correction (FEC) block codes and FEC convolutional codes with respect to the throughput efficiency for a Body Sensor Network (BSN) following the proposed role-based architecture ? The proposed role-based architecture outperforms the traditional layered architecture with respect to the throughput efficiency for all error control schemes ? FEC block codes are able to maintain a high throughput efficiency over longer distances In this paper, a flexible role-based architecture for Body Sensor Networks (BSNs) is introduced The proposed non-layered context-aware architecture is application-oriented and able to incorporate future applications Particular applications have certain requirements Functional units (roles) instead of protocol layers are designed to perform the required tasks for applications to work properly The role data of an application is inserted in the role headers of the container and is available for other applications with the same basic, specific or particular roles Furthermore, the performance of Automatic Repeat Request (ARQ), Forward Error Correction (FEC) block codes and FEC convolutional codes with respect to the throughput efficiency has also been analyzed for a BSN following the proposed role-based architecture The numerical results show that the proposed role-based architecture outperforms the traditional layered architecture with respect to the throughput efficiency for all error control schemes FEC block codes are able to maintain a high throughput efficiency over longer distances because the hop length extension technique is applied

6 citations


Book ChapterDOI
01 Jan 2012

5 citations


Proceedings ArticleDOI
03 Nov 2013
TL;DR: A scheduling algorithm with an integrated backpressure mechanism for multiradio cognitive WMNs that not only achieves nearly perfect fairness, but can also prevent bandwidth wastage.
Abstract: Wireless mesh networks (WMN) are efficient and low cost solutions for the deployment of broadband access in various environments. To support real-time applications such as multimedia and emergency services throughout the network, WMNs must provide appropriate quality of service (QoS). While the capacity and the bandwidth availability of single radio WMNs may severely limit QoS for such traffic, multiradio cognitive WMNs (CWMN) can overcome these restrictions and provide better QoS mechanisms. This paper describes a scheduling algorithm with an integrated backpressure mechanism for CWMN. This algorithm ensures that the available bandwidth is properly shared considering the type of traffic to forward, the distance of the clients from the portal and the fluctuating conditions of the links. The performance of our new scheduling algorithm is evaluated in a simulated environment. We show that, while increasing throughput, our algorithm not only achieves nearly perfect fairness, but can also prevent bandwidth wastage.

3 citations


Cites background from "A Clean-Slate Architecture for Reli..."

  • ...4 TCP/IP Modifications In [8], a cross-layer design that combines both routing and transport functionalities in a single layer was proposed to improve the delivery of data packets and to provide fairness in IEEE 802....

    [...]


12 Dec 2012
Abstract: Les reseaux mailles sans fil (WMN) sont une solution peu couteuse et efficace afin de deployer rapidement des services d’acces a large bande dans des environnements depourvus d’infrastructure. Toutefois, pour devenir un succes commercial, les WMN doivent supporter des applications en temps reel, telles que celles pour le multimedia et les services d’urgence. Or, ces applications generent du trafic critique qui requiert la mise en place de mecanismes de qualite de service (QoS). Alors que la capacite et la disponibilite de la bande passante des WMN monoradios limitent severement la QoS pour ce type de trafic, les WMN cognitifs (CWMN) multiradios peuvent compenser ces limitations et offrir de meilleurs mecanismes de QoS. Ce projet de recherche propose d’ameliorer la performance des WMN afin qu’ils puissent supporter la QoS requise pour satisfaire aux exigences strictes du trafic genere par des applications en temps reel.

1 citations


Cites background from "A Clean-Slate Architecture for Reli..."

  • ...Dans [82], une conception trans-couche qui combine les fonctionnalités de routage et de transport en une seule couche a été proposée pour améliorer la livraison des paquets de données et pour assurer l’équité dans les WMN IEEE 802....

    [...]


References
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01 Oct 2003
TL;DR: The Optimized Link State Routing protocol is an optimization of the classical link state algorithm tailored to the requirements of a mobile wireless LAN and provides optimal routes (in terms of number of hops).
Abstract: This document describes the Optimized Link State Routing (OLSR) protocol for mobile ad hoc networks. The protocol is an optimization of the classical link state algorithm tailored to the requirements of a mobile wireless LAN. The key concept used in the protocol is that of multipoint relays (MPRs). MPRs are selected nodes which forward broadcast messages during the flooding process. This technique substantially reduces the message overhead as compared to a classical flooding mechanism, where every node retransmits each message when it receives the first copy of the message. In OLSR, link state information is generated only by nodes elected as MPRs. Thus, a second optimization is achieved by minimizing the number of control messages flooded in the network. As a third optimization, an MPR node may chose to report only links between itself and its MPR selectors. Hence, as contrary to the classic link state algorithm, partial link state information is distributed in the network. This information is then used for route calculation. OLSR provides optimal routes (in terms of number of hops). The protocol is particularly suitable for large and dense networks as the technique of MPRs works well in this context.

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TL;DR: This paper presents a detailed study on recent advances and open research issues in WMNs, followed by discussing the critical factors influencing protocol design and exploring the state-of-the-art protocols for WMNs.
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TL;DR: Measurements taken from a 29-node 802.11b test-bed demonstrate the poor performance of minimum hop-count, illustrate the causes of that poor performance, and confirm that ETX improves performance.
Abstract: This paper presents the expected transmission count metric (ETX), which finds high-throughput paths on multi-hop wireless networks. ETX minimizes the expected total number of packet transmissions (including retransmissions) required to successfully deliver a packet to the ultimate destination. The ETX metric incorporates the effects of link loss ratios, asymmetry in the loss ratios between the two directions of each link, and interference among the successive links of a path. In contrast, the minimum hop-count metric chooses arbitrarily among the different paths of the same minimum length, regardless of the often large differences in throughput among those paths, and ignoring the possibility that a longer path might offer higher throughput.This paper describes the design and implementation of ETX as a metric for the DSDV and DSR routing protocols, as well as modifications to DSDV and DSR which allow them to use ETX. Measurements taken from a 29-node 802.11b test-bed demonstrate the poor performance of minimum hop-count, illustrate the causes of that poor performance, and confirm that ETX improves performance. For long paths the throughput improvement is often a factor of two or more, suggesting that ETX will become more useful as networks grow larger and paths become longer.

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"A Clean-Slate Architecture for Reli..." refers background in this paper

  • ...To prevent a redundant computation overhead, we derive plink from ETX: (1 ) (1 ) (1 (1 ))(1 ) 1 11 = + − = − + − − − = − = − link f f r f f r f r p p p p d d d d d ETX (3) In order to account to the loss probability of a given path between a sender A and a receiver B, we consider the loss probability at the bottleneck-link of the path, i.e. the link with the highest loss probability....

    [...]

  • ...Along with the ETX metric, the routing module also relies on information from the transport module on end-to-end connections for quick updates of the routing table....

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  • ...In [3], the authors introduced the Expected Transmission Count (ETX) as a new metric for multihop wireless networks....

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  • ...Such probability is derived by calculating the expected transmission count (ETX) [3] at each link: 1= ⋅f r ETX d d , (1) where df and dr denote the forward and reverse packet delivery ratios, respectively....

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  • ...Such a trend, which is referred to as clean-slate network design, has been becoming increasingly popular within the research community ([13], [17], [18])....

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Proceedings ArticleDOI
26 Sep 2004
TL;DR: A new metric for routing in multi-radio, multi-hop wireless networks with stationary nodes called Weighted Cumulative ETT (WCETT) significantly outperforms previously-proposed routing metrics by making judicious use of the second radio.
Abstract: We present a new metric for routing in multi-radio, multi-hop wireless networks. We focus on wireless networks with stationary nodes, such as community wireless networks.The goal of the metric is to choose a high-throughput path between a source and a destination. Our metric assigns weights to individual links based on the Expected Transmission Time (ETT) of a packet over the link. The ETT is a function of the loss rate and the bandwidth of the link. The individual link weights are combined into a path metric called Weighted Cumulative ETT (WCETT) that explicitly accounts for the interference among links that use the same channel. The WCETT metric is incorporated into a routing protocol that we call Multi-Radio Link-Quality Source Routing.We studied the performance of our metric by implementing it in a wireless testbed consisting of 23 nodes, each equipped with two 802.11 wireless cards. We find that in a multi-radio environment, our metric significantly outperforms previously-proposed routing metrics by making judicious use of the second radio.

2,593 citations


"A Clean-Slate Architecture for Reli..." refers background in this paper

  • ...Such a trend, which is referred to as clean-slate network design, has been becoming increasingly popular within the research community ([13], [17], [18])....

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01 Jan 2000
TL;DR: Urethane prepolymer compositions are made from 1- isocyanato-3-isocyanatomethyl-3,5,5-trimethyl cyclohexane and polyols at a total NCO to OH ratio of at least 1.2:1, and the prepolymers are reacted with cycloaliphatic polyamines to give urea-urethanes.

1,902 citations


"A Clean-Slate Architecture for Reli..." refers methods in this paper

  • ...The routing module implements proactive route determination similar to the Optimized Link State Routing Protocol (OLSR) [2]....

    [...]

  • ...As a transport protocol for the TCP/IP stack we deploy the widely used TCP NewReno, whereas for routing the standard OLSR protocol with ETX support is adopted....

    [...]


Frequently Asked Questions (1)
Q1. What are the contributions in "A clean-slate architecture for reliable data delivery in wireless mesh networks" ?

In this paper, the authors introduce a clean-slate architecture for improving the delivery of data packets in IEEE 802. 11 wireless mesh networks. Opposed to the rigid TCP/IP layer architecture which exhibits serious deficiencies in such networks, the authors propose a unitary layer approach that combines both routing and transport functionalities in a single layer. In a comparative performance study, the authors show that MTL achieves up to 48 % more goodput and up to 100 % less packet drops than TCP/IP, while maintaining excellent fairness results.