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This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the ICC 2007 proceedings.

DARA: Delay-Aware Routing Algorithm in a Hybrid
Wireless-Optical Broadband Access Network (WOBAN)
Suman Sarkar1 , Hong-Hsu Yen2 , Sudhir Dixit3 , and Biswanath Mukherjee1
1
Department of Computer Science, University of California, Davis, CA 95616, USA
2
Department of Information Management, Shih Hsin University, Taiwan
3
Nokia Research Center, Burlington, MA 01083, USA
Email: {sarkar, mukherje}@cs.ucdavis.edu, hhyen@cc.shu.edu.tw, sudhir.dixit@nokia.com

Abstract— Hybrid wireless-optical broadband access net- i.e., an end user can try to deliver its packet(s) to any one
work (WOBAN) is a promising architecture for future of the gateways (from which the packet will find its way to
network operations. Recently, the wireless part of WOBAN the rest of the Internet). But in the downstream direction (from
has been gaining increasing attention and early versions a gateway/ONU to a wireless user), this network is a unicast
are being deployed as a municipal access solution to network, i.e., a gateway will send a packet to only its specific
eliminate the wired backhaul to every wireless router. This destination (or user).
architecture saves on network deployment costs because
fiber (or wiring) does not need to extend to the end user,
and it extends the reach of emerging optical access so-
lutions, e.g., Passive Optical Network (PON)-based access
solutions. However, a major research opportunity exists in
developing an efficient routing algorithm for the wireless
front end of WOBAN.
We propose and investigate the characteristics of “Delay-
Aware Routing Algorithm (DARA)” that minimizes the
average packet delay in the wireless front end of a
WOBAN. We model wireless routers as queues and predict
wireless link states periodically. Our simulation experi-
ments show that DARA achieves better load balancing and
less congestion compared to tradional approaches such as
minimum-hop routing algorithm (MHRA) and shortest-
path routing algorithm (SPRA). In addition to minimizing
the delay, DARA also improves the average hop count
compared to the predictive throughput routing algorithm
(PTRA), a popular protocol used in several deployments Fig. 1. SFNet: wireless mesh in San Francisco WOBAN.
for the wireless front end of a WOBAN.
Note that the wireless links in the front end mesh of a
WOBAN may have asymmetric and differential capacities.
I. I NTRODUCTION This is because of how a router connects to other routers in
A hybrid wireless-optical broadband access network (re- the neighborhood; e.g., if a router is associated with two other
ferred to as “WOBAN” here) consists of a multi-hop wireless routers, and the wireless channel is time-division multiplexed,
mesh network at the front end, and it is supported by an then on average, each link (associated with that router) will
optical access network, e.g., a passive optical network (PON) get half of the capacity to other routers. Also the effective link
at the back end. At the back end of a WOBAN, Optical Line capacity from router A to router B may be different than that
Terminals (OLT) reside in a Central Office (CO) and feed to from router B to router A, because routers A and B may have
multiple Optical Network Units (ONU). Thus, from ONU to different numbers of neighbors.
the OLT/CO, we have a traditional fiber network; and, from In this study, we focus on the packet delay (latency) in the
ONUs, end users are wirelessly associated. At the front end front end (wireless mesh) of the WOBAN, i.e., the packet
of a WOBAN, end users with wireless devices at individual delay from the router to the gateway (attached to ONU) and
homes or business premises are scattered over a geographic vice versa. The packet delay could be significant as the packet
area. Each of them will associate with a nearby wireless may travel through several routers in the mesh before finally
router. The collection of routers forms a multi-hop wireless reaching the gateway (in the upstream direction) or to the
mesh network; and a few of them, called “gateways”, are user (in the downstream direction). The larger the mesh of the
strategically placed over the geographical region of coverage. WOBAN, the higher is the expected delay. Thus, we propose
Gateways are attached to ONUs. A ONU can drive multiple “Delay-Aware Routing Algorithm (DARA)” as a proactive
gateways [1], [2]. routing scheme where we model each wireless router as an
An end user sends a data packet to one of its neighborhood M/M/1 queue and predict the wireless link states (using link-
routers. This router then injects the packet into the wireless state prediction or LSP) periodically [6], [7], [8]. Based on the
mesh of the WOBAN. The packet travels through the mesh, LSP information, we assign link weights to the wireless links.
possibly over multiple hops, to one of the gateways/ONUs Links with higher predicted delays are given higher weights.
and is finally sent through the optical part of the WOBAN Then we compute the path with the minimum predicted delay
to the OLT/CO. In the upstream direction (from a wireless from a router to any gateway and vice versa. While traveling
user to a gateway/ONU), WOBAN is an anycast network, upstream/downstream, a router/gateway will send its packet

U.S. Government work not protected by U.S. Copyright


along the computed path only if the predicted delay is below not suitable for delay-sensitive services as the corresponding
a predetermined threshold, referred to as the delay requirement packets can take longer routes (as long as the route satisfies
for the mesh; otherwise we will not admit the packet into the the throughput criteria).
mesh. We also study how choosing a path from a set of paths There exist several research efforts that address routing
(whose delays are below the delay requirement) can alleviate which fits with the front end of a WOBAN. In [10], the
congestion and achieve better load balancing. authors propose a link-activation framework (even-odd link
We consider a part of the city of San Francisco, Califor- assignments) for scheduling packets in a wireless network.
nia, from approximately (N 37◦ 46 43.39 , W 122◦ 26 19.22 They show that the packet delay for wireline schedulers,
(Golden Gate Avenue and Divisadero Street intersection)) to viz., Weighted Fair Queuing (WFQ) and Coordinated Earliest
(N 37◦ 46 51.78 , W 122◦ 25 13.27 (Golden Gate Avenue and Deadline First (CEDF), when implemented over the wireless
Van Ness Avenue intersection)) and from (N 37◦ 47 32.57 , multi-hop network, are guaranteed to be approximately twice
W 122◦ 26 28.90 (Divisadero Street and Pacific Avenue in- the delay of the corresponding wireline topology. In [11], the
tersection)) to (N 37◦ 47 41.39 , W 122◦ 25 23.71 (Van Ness authors provide admission control schemes for a multihop
Avenue and Pacific Avenue intersection)) (see Fig. 1) for our wireless network for packets with QoS requirements. In [12],
performance study. This is approximately a one square-mile the authors develop a routing protocol that makes use of
area in downtown San Francisco with an estimated population Bottleneck Link Capacity (BLC) as the link metric for wireless
of around 15, 000 residents [3], [4], [5]1 . The wireless part of networks. Other interesting research efforts appear in [13],
our San Francisco WOBAN (henceforth called “SFNet”, see [14], [15], [16], and [17].
Fig. 1) is a mesh that consists of a number of point-to-point Next, we propose our routing algorithm, called DARA (that
or point-to-multipoint WiFi routers2 . minimizes the average packet delay and achieves better load
The rest of this study is organized as follows. In Section II, balancing), for the wireless front end of a WOBAN.
we briefly review the current routing schemes in municipal
wireless networks and related research efforts. In Section III,
we propose our delay-aware routing algorithm (DARA) and III. D ELAY-AWARE ROUTING A LGORITHM (DARA)
analyze the LSP mechanism. Section IV contains performance DARA is a proactive routing algorithm. DARA considers
studies of DARA compared to other routing schemes used the end-to-end delay for packets (here end-to-end means from
in the front-end wireless mesh of WOBAN, and Section V the packet’s source router to a gateway or vice versa in the
summarizes this study. front end of a WOBAN). So, routing in the mesh deals with
packets from a router to a gateway (and vice versa). A wireless
II. C URRENT A PPROACHES AND R ESEARCH routing path consists of two parts: (1) the associativity of a
O PPORTUNITIES user to a nearby wireless router in its footprint, and (2) the
The minimum-hop routing algorithm (MHRA) and the path from this (ingress) router to a suitable gateway (through
shortest-path routing algorithm (SPRA) are used in the wire- the wireless mesh).
less part of a WOBAN (where the link metric in MHRA is A user needs to decide which router it should associate
unity and that in SPRA is inversely proportional to the link with before sending its packets. If there is only one router in
capacity). Recent approaches also consider solution providers’ its footprint, the user has to choose that router. If there are
patented routing algorithms. Predictive-Throughput Routing multiple routers, and the nearest router is overloaded, the user
algorithm (PTRA) is one such protocol (where PTRA is sim- can choose the next nearest router, which is not overloaded.
ilar to “Predictive Wireless Routing Protocol (PWRP)” [9]). From a router, a packet is injected into the mesh. The packet
We use the name “PTRA” instead of “PWRP” throughout delay due to the single-hop communication between a user
this study. These protocols run inside the wireless routers and and its associated ingress router is unavoidable and is small
gateways in the mesh. compared to the packet delay in the mesh. This is because a
MHRA and SPRA work on the shortest-path principle packet could potentially travel through multiple routers in the
without generally considering other traffic demands on the mesh to get to one of the gateways.
network. Therefore, MHRA and SPRA could suffer from The packet delay in the mesh (namely the front end of a
several routing limitations (viz., increased delay, poor load WOBAN) consists of four components: (1) Propagation delay,
balancing, and high congestion in a link or along a segment (2) Transmission delay, (3) Slot synchronization delay, and (4)
(consisting of multiple links)). Queuing delay.
Unlike MHRA and SPRA, PTRA is not based on the Propagation delay will not be significant assuming routers
shortest-path routing principle. PTRA is a link-state based are close to one another. Transmission delay depends on the
routing scheme, and it chooses the path (from a set of possible effective link capacity. Higher the link capacity, lower is the
paths between a user-gateway pair) that satisfies the overall transmission delay. Slot synchronization delay comes from
throughput requirements, as explained below. PTRA takes the time-division-multiplexing (TDM)-based operation of a
measurement samples of link rates periodically across wireless wireless channel, where each router will send packets to its
links. Given a user-gateway pair, the algorithm computes neighboring routers at the pre-assigned time slots. Queuing
available paths. Based on the history of samples, PTRA delay depends on the rate of packet arrivals and rate of service
dynamically predicts link condition and then estimates the at a router. Higher the packet arrival rate and slower the
throughput of each path. It chooses the path that gives a higher service rate, higher will be the queuing delay. Queuing delay
estimated throughput [9]. Although PTRA is proposed and is cumulative. If a packet traverses multiple routers before it
implemented for only carrying packets in the wireless part reaches a gateway, then in each of these routers it experiences
of a WOBAN, the major problem in PTRA is that the packet queuing delay, which accumulates as the packet travels through
may end up traveling inside the mesh longer than expected (as the mesh.
PTRA does not take into account packet delay). So, PTRA is WOBAN being a municipal network, users with wireless
devices have limited or no mobility. They are mostly
1 San Francisco has an area of nearly 47 square-miles with a population of residential and business users. We also know the users’
around 745, 000; so the population of SFNet in Fig. 1 is quite representative service level agreements (SLA), the network’s connectivity
of San Francisco’s population density. pattern (how routers are associated among themselves), and
2 In greyscale image (of Fig. 1), black squares (five of them) are atached to the locations of routers and gateways or ONUs (which are
the optical part of WOBAN as gateways; others (twenty of them) are routers. attached to the back end of WOBAN) in advance. Also note


that the mesh in the front end of WOBAN is “anycast” in the link conditions (see Section III-B) between the intervals to
upstream and “unicast” in downstream direction. avoid “stale” information. These link-state predictions (LSP)
can also capture the burstiness of data packets in the access
Problem Statement network.
• Given parameters: In LWA (see Algorithm 1), we assign link weights in such
- G(V, E) : directed graph denoting front end mesh of a manner that the links with more delays get more weights
WOBAN, and vice versa.
where V : set of vertices and E : set of wireless
links, Algorithm 1 Delay-Aware Routing Algorithm (DARA)
- R : set routers in mesh, - Link-State Advertisement (LSA):
- O : set of gateways/ONUs, For each link i, advertise periodically current packet
where |V | = |R| + |O|,
- λn : rate of packet arrival at router n, n ∈ [1, |R|], intensity (λi ), effective link capacity (Ci ), and time stamp
- λj : rate of packet arrival at gateway j, j ∈ [1, |O|], (tn ).
- λi : rate of packet arrival at link i, i ∈ [1, |E|], and - Link-State Prediction (LSP):
- Ci : capacity of link i, i ∈ [1, |E|]. For each link i, estimate packet intensity (λest ), to be
i
• Objective: used until next LSA gets advertised (see Section III-B).
- Average-packet-delay-optimized routing in front end - Link Weight Assignment (LWA):
mesh of WOBAN. Assign weight of each link i as:
We will sketch our algorithm next for delay-aware routing. Wi = Qi = µCi + 2µCi + µCi ρi est .
1 1
We will model each router inside the mesh as an M/M/1 −λi
queue. A packet’s average packet transfer delay, Q (also - Path Computation:
known as “system time”), along a link depends on the trans- 1) Compute K minimum-weight paths (K > 1),
mission delay, slot synchronization delay, and queuing delay.
Packets arrive at the routers (directed to gateways upstream) i∈Pk Wi , from the source router to the gateway
and gateways (destined to router downstream) in a Poisson or vice versa, where Pk is the k-th path for k ∈
distribution (and are denoted by λn and λj , respectively) with [1, K]. We call these paths as K-DARA paths.
exponential interarrival time. We know that λi is the average 2) Derive a set of paths, F (called “feasible paths”),
packet intensity on link i and follows a Poisson distribution that satisfy the delay requirement of the packet.
as well (where λi can be found knowing λn and λj ). The 3) Among F , choose one path.
packet lengths are independent and exponentially distributed
1
with average packet lengths as µ and the effective link capacity - Admission Control:
is Ci . (The independence assumption is being employed as an 1) Admit a new packet in the mesh only if
approximation for mathematical tractability.) its delay requirement (Treq ) satisfies the
The capacity is assigned to each link i in a diffential and minimum delay among the feasible paths F ,
asymmetric manner. Consider router A has router B and two M inPk ∈F i∈Pk Wi ≤ Treq .
other routers in its vicinity. Similarly, router B attaches to
router A and three other routers. So, router A’s transmitter will 2) Else reject the packet.
send packets to three neighboring routers in three consecutive
time slots. So, differential capacity for link i from router A to
router B will be on average one-third of the full capacity C
(i.e., CiA→B
= C ). Similarly, differential capacity for link i
3
A. Achieving Load Balancing
from router B to router A will be on average one-fourth of the DARA works on the principle of delay optimization along
full capacity C (i.e., Ci B→A
= C ). Note that the differential
4
paths from a router to a gateway in the front end of WOBAN.
capacity assignment is an average-case assignment, because If every packet in the mesh wants the path with minimum
time slots for each TDM frame may not be static. Also, note weight (alternatively, the path with minimum delay), then
A→B B→A
that link capacities can be asymmetric (i.e., Ci = Ci ), some links in the mesh may get more packets (overload
because routers A and B may have different numbers of situation) compared to the other links. This may adversely
neighbors. affect the throughput of the network as many packets might
Therefore, the transfer delay for each link i is Qi = get rejected due to the link congestions in some parts of
1 1 ρi 1 the network (had they chosen some other path they would
µCi + 2µCi + µCi −λi , where µCi is the transmission delay have still satisfied their delay requirement). This is why we
1
(also known as “service time”) and 2µCi is the slot synchro- compute K minimum-weight paths, instead of only computing
ρi
nization delay, and µCi −λi is the queuing delay, where ρi is the minimum-weight path to leaverage greater flexibility in
λi choosing the paths.
the link utilization, and ρi = µCi . Delays for K-DARA paths are bounded between the min-
Algorithm 1 is our proposed delay-aware routing algorithm imum delay and the maximum delay that satisfies the delay
(DARA). requirement of the packet. Let Tpkt denotes the delay of a
In LSA (see Algorithm 1), each router/gateway will period- packet whose delay requirement is Treq in the mesh, then Tpkt
ically advertise its link conditions. Smaller the LSA period, is shown to be as follows:
less is the possibility of “stale” advertisement (where an
advertisement becomes “stale” when the link state changes
significantly after the last advertised information). However, Tpkt = M inPk ∈F Wi , M axPk ∈F Wi ≤ Treq (1)
LSA in smaller intervals leads to the problem of sacrificing a i∈Pk i∈Pk
significant portion of the network’s bandwith in advertisement,
which could have otherwise been used for data packets. where Pk is the k-th path with k ∈ [1, K].
Therefore, we can increase the LSA intervals suitable for We may achieve better load balancing by choosing paths
WOBAN to preserve the bandwidth for packets and predict described above. DARA will also help us relieve network


congestion. Let γ denote the average system arrivals and Tsys that, at low loads (till the normalized load of 0.40, MHRA
denote the average system delay in the mesh, then Tsys can and SPRA perform comparably with DARA. This is expected
be defined as below (where E denotes the connectivity in the because both MHRA and SPRA work on the shortest-path
mesh): principle. So, at low loads, these two algorithms have higher
  probability to find the shortest paths with less delay. But as
load increases, DARA’s performance improves significantly
1 λi λi
Tsys =  λi Wi + +  (2) compared to MHRA and SPRA. DARA performs much better
γ 2µCi µCi − λi than PTRA at all loads. At a very high load of 0.95, the
i∈Pk i∈Pk ,i∈E
average system delay for DARA improves nearly 30% from
(3)
its nearest competitor, namely PTRA.
where Pk is the k-th path with k ∈ [1, K].

B. Analysis of Link-State Predictions
Link-State Predictions (LSP) need to be quite accurate
to capture the current network conditions and the packet
burstiness. We use “weighted moving average (WMA)” to
estimate the packet intensity. Let λi (tn ) denote the measured
packet intensity that gets advertised (through LSA) in the mesh
at time tn for link i, and let λest (tn−1 ) denote the estimated
i
(or predicted) packet intensity for the same link at the previous
time instant tn−1 (and used for time interval [tn−1 , tn )). So,
LSP will compute the estimated packet intensity for the next
time instant, tn (and to be used for time interval [tn , tn+1 ))
as follows:

3α 1−α
λest (tn ) =
i ∗ λi (tn ) + λest (tn−1 ) ∗ S 1+α , (4)
i
Fig. 2. Average delay (system time) vs. load in SFNet.
3α + 1
where α is the “decaying index” of WMA and S is the number Figure 3 compares individual path delays among the four
of samples used for predictions. Decaying index has a physical schemes. We choose the furthest origin/gateway pair (1, 25)
significance. It captures if a link is highly loaded or not. If a in the mesh (see Fig. 1 for (1, 25) pair in SFNet), because
link is highly loaded, α = ∞. Then Eqn. (4) estimates the a packet will travel multiple hops and the delay will be
current intensity based on all previous samples. On the other cumulative in each hop. We find that DARA performs much
hand, if a link is lightly (or moderately) loaded, we set α = 1, better than all the other schemes. The performance improves
and following Eqn. 4, we observe that only 10% of λi (0) at high loads. We also observe that, after a load of 0.50, PTRA
remains present in packet intensity computations (or 90% of delay shoots up and overtakes SPRA delay.
the past samples are “forgotten” after only eight time periods).

IV. P ERFORMANCE S TUDY
We compare how delay-aware routing algorithm (DARA)
performs vis-a-vis MHRA, SPRA, and PTRA. We took SFNet
as our test setting. We envision SFNet as a part of on-going
efforts to deploy the San Francisco municipal network. In
SFNet, we distributed 25 wireless routers in one square-mile
area. We designated five of these 25 routers as gateways
to the optical back end of WOBAN and placed them at
the edges of SFNet (see Fig. 1)3 . We generated packets in
a Poisson distribution. The packet lengths are independent
and exponentially distributed. We assumed a wireless router’s
capacity to be 11 Mbps in ideal conditions.
In MHRA, we assign all link weights as unity. In SPRA, we
assign link weights as the inverse of link capacity. MHRA and
SPRA are greedy approaches. In PTRA, we took the measure- Fig. 3. Delay vs. load (for the furthest router/gateway pair (1, 25) in SFNet).
ments of wireless links periodically. Then we computed a set
of paths between a router and a gateway and chose the path Figure 4 shows the average hop counts of all four schemes.
with higher estimated throughput. So, for each path in PTRA, Expectedly, MHRA and SPRA produce the minimum average
we find the link with the minimum free capacity. We call it number of hops, but DARA performs comparably with them
the “weakest link”. The weakest link will be the bottleneck for (particularly at a low load, till 0.40, DARA performs very
pumping packets (and for throughput) in the path. We chose well). DARA performs much better than PTRA for all loads.
the path with the best of the “weakest links” (alternatively, we In Fig. 5, we plot the percentage distribution of path lengths for
chose the maximum of the minimum of free capacities for a each of these schemes. From the associated table, we observe
set of paths.). that DARA performs well, because unlike PTRA, DARA tries
Figure 2 shows that DARA outperforms MHRA, SPRA, and to pack many packets in fewer hops (1 − 3 hops). DARA has
PTRA with respect to average system delay. We can observe a maximum of ten hops in this example, but only 0.025% of
packets will get routed along the 10-hop paths.
3 We carefully choose the number (as well as distribution) of routers and Figure 6 captures how these schemes perform in terms
gateways in SFNet to match the solution provider’s current deployment status, of load balancing and link congestion. We plot the traffic
where typically 25 − 30 routers are needed to serve one square-mile of area. difference, which is the difference between the maximum


enough so that the total bandwidth consumption due to LSA is
low. So, in between the higher LSA periods, LSP will predict
link states. Thus, LSP saves WOBAN bandwidth with accurate
predictions of link states.

Fig. 4. Average hops vs. load in SFNet.

Fig. 7. Actual vs. predicted packet intensities at high loads.

V. S UMMARY
The hybrid wireless-optical broadband access network
(WOBAN) is evolving fast as a cost-effective and high-
capacity alternate solution to the traditional access networks.
The wireless part of a WOBAN is being deployed in many
Fig. 5. Hop distributions vs. load in SFNet. communities. The rapid deployment needs efficient routing,
control, and management of both the wireless front end and
the optical back end of a WOBAN.
and the minimum packet intensities for links in the mesh for In this study, we proposed and investigated the character-
MHRA, SPRA, DARA, and PTRA paths. Smaller the differ- istics of a “Delay-Aware Routing Algorithm (DARA)” that
ence, better will be the load balancing (or less will be the link minimizes the average packet delay in the wireless front end
congestion) and vice versa. In this performance metric also, of a WOBAN. We modeled wireless routers as M/M/1 queues
DARA performs much better than MHRA and SPRA. MHRA and predicted wireless link states periodically. We showed
and SPRA find the shortest paths and thereby poorly balance that DARA achieves better load balancing and less congestion
the load. Consequently, they congest a part of the mesh. Both compared to tradional approaches such as minimum-hop rout-
DARA and PTRA perform well and are comparable to each ing algorithm (MHRA) and shortest-path routing algorithm
other. Till the load of 0.75, DARA performs better than PTRA. (SPRA). In addition to improving delay, DARA also improves
After that, PTRA performs better. the average hop count compared to predictive throughput
routing algorithm (PTRA), a popular routing algorithm used
in the wireless front end of a WOBAN.

R EFERENCES
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WOBAN, it is very important to keep the LSA period high

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