19 a Comparative Analysis of Time Stamped

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All India National Seminar on Computing, Communication and Sensor Network, CCSN-2010

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A Comparative Analysis of Time Stamped Based

Packet Scheduling Algorithms

Biswapratap Singh Sahoo1, Haraprasad Mohanta

2, Rajesh Subhankar

3, Sanjeeb Biswal

4

1

Utkal University, M.Tech Student, [email protected] Hindu University, M.Sc Student, [email protected]

3Spintronic Technology & Advance Research, B.Tech Student, [email protected]

4Spintronic Technology & Advance Research, B.Tech Student, [email protected]

ABSTRACT

Every server uses a scheduling discipline to decide the

order in which the requests are to be served. A

scheduling discipline should satisfy the following

requirements; 1) Is easy to be imp1emented; 2)Provides

fairly distributed bandwidth to competing requests;

3)Guarantees performance bounds for a wide range of

traffic types; 4)Allows easy admission control decision.To date, a lot of scheduling disciplines have been

proposed in the research literature, among which, the

Strict Priority (SP). Weighted Fair Queuing PFQJ and

Weight Round Robin (WRR) are perhaps the three most

widely adopted disciplines. However, the Generalized

Processor Sharing (GPS) discipline for pocket scheduling

best caters to the above properties. GPS uses an idealized

fluid model that can't be precisely implemented in the

real scenario. Worst Case Fair Weighted Fair Queuing

pF2Q is the closest packet approximation algorithm of

the GPS discipline. WFZQ+ is an enhanced version of

WFZQ and has a less time complexity.This paper first reviews the theory of the four timestamp

based algorithms (WFQ, WF2Q+, SFQ, and SCFQ) and

prepare a detailed analysis on basis of the simulations

performed.

Keywords: GPS, WF2Q+, pF2Q

I INTRODUCTION

As the Internet has developed into a ubiquitous global

communication medium, it is used to carry a constantly

evolving mix of applications that is becoming richer with

innovation and improvements in technology. Todays,

network applications can be broadly classified into twofundamental classes i.e. Best-effort Applications and

Guaranteed-service Applications. The two types of

applications differ in terms of their sensitivity to delay

and availability of bandwidth, as well as in terms of the

level of service quality they expect from the network.

Most of the applications that were originally developed

for the Internet (including email, file transfer, and web

browsing) have elastic requirements from the network. In

other words, such applications are able to adapt to the

bandwidth, delay, or loss. Elastic applications do not

require any explicit guarantees and work correctly with a

best-effort service under which the network only makes apromise to attempt to deliver their packets.

On the other hand, real-time and interactive applications

(including streaming audio and video, multimedia

conferencing, etc) do require performance bounds from

the network in terms of bandwidth, delay, or delay jitter.

For instance a VoIP application requires both a minimum

bandwidth (generally, between 20-80 Kbps) and a round-

trip delay of about 150 ms to ensure a good user

experience. These applications require a guarantee of

service quality from the network, and the network must

reserve resources on their behalf. Furthermore, the

performance that guaranteed-service applications receive

is directly affected by the scheduling discipline employed

by the nodes along their path, as these disciplines are

responsible for scheduling packets on the outgoing links.

In packet-switched networks, packets from various users

or flows have to share the Network resources, including

buffer space at the routers and link bandwidth. Whenever

resources are shared, contention arises among flows

seeking service. Consequently, shared resources employ a

scheduling discipline to resolve contention by

determining the order in which users receive service. In

particular, the scheduling algorithm is a central

component of the quality of service (QoS) architecture ofpacket switched networks.

II PROBLEM DEFINITION

Our goal is to compare the four timestamp based

algorithms (WFQ, WF2Q+, SFQ, SCFQ) for the

following performance parameters:

Algorithmic Complexity Fairness of the scheduler Average end to end Delay Delay Jitter Loss of packets Throughput of the data streamAnd prepare a detailed analysis on basis of the

simulations performed.

III REVIEW OF PREVIOUS WORK

Generalized Processor Sharing

GPS is an ideal scheduler, a theoretical construct that

serves both as a starting point for designing practical

scheduling disciplines and as a reference point for

evaluating the fairness and delay properties of thesedisciplines. GPS visits each backlogged flow queue in

turn and serves an infinitesimal fraction of the head-of-

line packet at each queue. If flows are assigned different


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weights, then the service they receive from GPS is

proportional to their weight.

If a queue is empty, GPS skips it to serve the next non-

empty queue. Therefore, whenever some queues are

empty, backlogged flows will receive additional service

in proportion to their weights. Consequently, GPS

achieves an exact max-min weighted fair bandwidth

allocation. It also provides isolation (protection) among

flows, since a misbehaving flow is restricted to its fair

share and does not affect other flows.

GPS is defined in a theoretical fluid flow model in which

multiple queues may be served simultaneously. In a

practical packet system, on the other hand, packet

transmissions may not be pre-empted and only one queue

may be served at any given time. The schedulers we

describe in the following subsections attempt to emulate

GPS but are designed for packetized systems.

Weighted Fair Queuing (WFQ)

WFQ is an approximation of GPS that serves packets in

the order they would complete service had they been

served by GPS. Therefore, the WFQ scheduler needs to

emulate the operation of the GPS server. WFQ combines

fair queuing and preferential weighting. In it, queues are

first sorted in order of their increasing weighted value.

Then, each queue is serviced in order of its weighted

proportion to the available resources. Here, the priority

given to network traffic is inversely proportional to the

signal bandwidth. Thus, narrowband signals are passed

along first, and broadband signals are buffered.

A virtual time function is used to calculate the finish

time of the packets had it been scheduled in GPS. The

WFQ scheduler serves packets in increasing order of

their virtual finish times, a policy referred to as smallest

virtual finish time first (SFF). The degree to which

WFQ approximates GPS is determined by two properties.

Bounded delay property. A packet will finish servicein a WFQ system no later than the time it would finish in

the corresponding GPS system plus the transmission time

of a maximum size packet.

Weak service property. The service (in terms of totalnumber of bits) that a flow receives in a WFQ system

does not fall behind the service it would receive in the

fluid GPS system by more than one maximum packet

size.

While due to the second property above a WFQ system

may not fall behind GPS by more than one maximum

packet size but, it was shown that WFQ may introduce

substantial unfairness relative to GPS in terms of the

worst-case fairness index (WFI). WFI is a metric to

represent the maximum time a packet arriving to an

empty queue will have to wait before receiving its

guaranteed service rate. Specifically, GPS has a WFI ofzero, but the WFI of WFQ increases linearly with the

number of flows.

Worst-Case Fair Weighted Fair Queuing (WF2Q)

The WF2Q algorithm was introduced in as a better

packet approximation of GPS than WFQ. Specifically,

WF2Q employs a smallest eligible virtual finish time

first (SEFF) policy for scheduling packets. A packet is

eligible if its virtual start time is no greater than thecurrent virtual time; hence, the WF2Q scheduler only

considers the packets that have started service in GPS

when selecting the packet to be transmitted next. It has

been shown [9] that WF2Q is work-conserving,

maintains the bounded delay property of WFQ, and has

these two additional properties:

Strong service property: The service (in terms oftotal number of bits) that a flow receives from a WF2Q

system cannot fall behind the service it would receive in

the fluid GPS system by more than one maximum packet

size

Worst-case fairness property: The worst-casefairness index of WF2Q is a constant independent of the

number n of flows served by the scheduler.

The first property implies that the WF2Q scheduler

closely tracks the GPS system in terms of the service

received by each flow, and due to the second property,

WF2Q is an optimal packet scheduler in terms of worst-

case fairness.

However, the worst-case complexity of WF2Q is O(n),

identical to that of WFQ, as both schedulers need to

compute the virtual time function .

WF2Q+

WF2Q+ is a lower-complexity scheduler. It is work-

conserving, has the same bounded delay, strong service,

and worst-case fairness properties of WF2Q, but uses a

different virtual time function that can be computed more

efficiently than the function used by WFQ and WF2Q.

The overall complexity of WF2Q+ is O(log n),

significantly lower than the O(n) complexity of WFQ and

WF2Q.

The scheduler implementation can be further simplified

by maintaining a single pair of start and finish virtual

time values per flow, rather than on a per-packet basis.

Overall, the WF2Q+ scheduler achieves tight delay

bounds and good worst-case fairness with a relatively low

O(log n) algorithmic complexity.

Self-Clocked Fair Queuing (SCFQ)

The O(n) worst-case algorithmic complexity of the WFQ

and WF2Q schedulers is due to the fact that the order of

packet transmissions in these queuing schemes is

determined by tracking the progress of the fluid-flow

GPS reference system.

Self-clocked fair queuing (SCFQ) avoids thecomputationally expensive emulation of a hypothetical


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reference system by adopting a self-contained approach

to fair queuing.

The algorithmic complexity of SCFQ is O(log n) because

of the requirement to select the packet with the smallest

finish time for transmission. Although the rule that

SCFQ uses to compute packet finish times is easy to

implement, the trade-off is a much larger delay bound

than WFQ. In particular, the delay bound provided by

SCFQ increases linearly with the number n of flows

served by the scheduler, in the worst case The worst-case

fair index (WFI) of SCFQ is the same as that of WFQ,

i.e, proportional to the number of flows.

Start-Time Fair Queuing (SFQ)

Start-time fair queuing is a variant of SCFQ that

maintains both a start time and a finish time for each

packet. Unlike the other packet fair schedulers, SFQ

serves packets in increasing order of their start times, not

their finish times.

SFQ has the same low algorithmic complexity O(log n)

as SCFQ. However, it has been shown that the worst-case

delay of SFQ is significantly lower than with SCFQ. The

worst-case fairness properties of SFQ are similar to those

of WFQ and SCFQ.

The table summarises the above algorithms

Algorithms Characteristics Complexity

GPS Ideal algorithm ---

WFQ An implementable

version of GPS(=PGPS)

O(n)

WF2Q+ Approximated GPS

better than WFQ

O(log n)

SCFQ Reduced the

complexity of WFQ

O(log n)

SFQ Reduced the short

term unfairness of

SCFQ

O(log n)

IV SOLUTIONAPPROACH

To perform the analysis we created the simulation

environment in windows XP professional with cygwin

and Network simulator 2.29.

The parameters we selected to analyze the scheduling

algorithms are:

Throughput of Receiving bits(Packets) Average throughput Bandwidth of the link Average end to end delay Delay jitter in the simulation Fairness of the scheduler

Parameters.

Below we discuss the various parameters in brief.

Bandwidth

It is essentially a data transmission rate; It is the

maximum amount of information (bits/sec) that can be

transmitted along a channel. In computer networkbandwidth is often used as a synonym for data transfer

rate. The amount of data that can carried from one point

to another in a given time period (usually a second).This

kind of bandwidth is usually expressed in bits (of data)

per second (bps). As the link bandwidth changes the

behaviour of the scheduler also changes.

Packet loss

Packet loss occurs when one or more packets of data

travelling across a computer network fail to reach their

destination. Packet loss is distinguished as one of the

three main error types encountered in digitalcommunication.

Cause: Packet loss can be caused by a number offactors, including signal degradation over the network

medium. Oversaturated network links, corrupted packet

rejected in transit, faulty networking, hardware faulty

network drivers or normal routing routines.

Effects: when cause by network problem lost ordropped packets can result in highly noticeable

performance issues or jitter with streaming technologies,

voice over IP etc and will affect all other network

application to a degree.Throughput

In communication networks, such as Ethernet or packet

ratio, throughput or network throughput is average rate

of successful message delivery over a communication

channel. This data may be delivered over a physical or

logical link or pass through a certain network node. The

throughput is usually measured in bits per second

(bits/sec or bps) and some time in data packets per

second or data packet per time slot.

The maximum achievable throughput is affected by the

bandwidth in hertz and signal to noise ratio of the analogphysical medium.

Delay and Delay Jitter

Delay is the time taken from point to point in a network.

Delay can be measured in either one-way or round-trip

delay.

Jitter is the variation in delay over time from point to

point. The delay is specified from the start of the packet

being transmitted at the source to the end of the packet

being received at the destination. A component of the

delay which does not very from packet to packet can be

ignored hence if the packet sizes are the same and packetalways take same time to be processed at the destination


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then the packet arrival at the destination could be used

instead of the time the end of the packet is received.

Jitter is the time variation of a periodic signal often in

relation to a reference clock source. Jitter may be

observed in characteristics such as the frequency of

successive pulses, the signal amplitude or phase ofperiodic signal. Jitter is a significant and usually

undesired factor in the design of almost all

communication links.

Jitter can be quantified in the same term as all time-

varying signals example. Peak to peak displacement.

Also like other time varying signals, jitter can be

expressed in terms of spectral destiny.

In the context of computer network, the term jitter is

often used as a measure of variability over time of the

packet latency across a network. A packet with contest

latency has no variation (or jitter).

Fairness

Allocation of link bandwidth is fair if equal bandwidth is

allocated in every time interval to all the flows.

This concept generalized to weighted fairness in which

the bandwidth must be allocated in proportion to the

weights associated with the flows. Formally if fis the

weight of flowf and Wf(t1,t2) is the aggregate service (in

bits) received by it in the interval [t1,t2], then an

allocation is fair if, for all interval [t1,t2] in which both

flows f and m are backlogged.

Mathematically

[Wf(t1,t2)/f] - [Wm (t1,t2)/m] = 0

Simulation Settings and Parameters

As different algorithms have different preferences or

assumptions for the network configuration and traffic

pattern, one of the challenges in designing our

simulation is to select a typical set of network topology

and parameters (link bandwidth, RTT, and gateway

buffer size), as well as load parameters (numbers of TCP

and UDP flow, packet size, traffic patterns) as the basis

for evaluation. Currently we havent found systematicway or guidance information to design the simulation. So

we make the decision by reading all related papers and

extracting and combining the key characteristics from

their simulations.

R R

10Mbps 1ms 10Mbps 1ms

2Mbps 5ms

TCP src/dst

UDP src/dst

Figure - 1 (Simulation topology)

The network topology we used is a classic dumb-bell

configuration as shown in Figure. This is a typical

scenario that different types of traffic share a bottleneck

router. TCP (FTP application in particular) and UDP

flows (CBR application in particular) are chosen as

typical traffic patterns.

In our simulation, we used 12 TCP flows and 8 UDP

flow. The bottleneck link in this scenario is the link

between two routers. We set the link bandwidth at

2Mbps, although we varied this to analyze the effect of

bandwidth in the simulation.(the packets size for both

TCP and UDP are 1000 bytes). The simulation time is set

to be 100 seconds. These settings are selected after some

parameter tuning simulations.

V RESULTS & DISCUSSIONS

As mentioned earlier the behaviors of the scheduling

algorithms are stated below according to respectiveparameters.

Average throughput

Average throughput of all the schedulers remains almost

same when subjected to different link bandwidth. The

simulation settings are same as stated in section 3.2

except the link bandwidth. Throughput increases with

the increase in bandwidth.

Figure-2 (Average throughput of schedulers with

different bandwidth)

When the bandwidth is fixed and no of TCP and UDP

nodes are changed, SFQ stays ahead of other algorithmsas the TCP nodes are increased. All others behave the

same.


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Figure 3 (Average throughput with different TCP-UDP

node combinations)

End-to-end delay

End-to-end delay in different link bandwidth also

remains same for different schedulers.

Figure 4 (End-to-end delay)

SCFQ and SFQ has a slightly higher delay bound

compared to WFQ and WF2Q+. SFQ has a tighter delay

bound than SCFQ. The results are not visible in the

graph but the stats show this with a very small variation.

Packet Loss

WFQ suffers most in terms of packet loss. SFQ performs

best here. With increase in total no of nodes, packet loss

increases as the traffic increases for all the schedulers.

When there is no TCP flow UDP nodes take up all the

bandwidth hence packet loss is zero. Similarly when

theres no UDP flow TCP nodes makes maximum use ofavailable bandwidth and packet loss becomes minimum.

Figure 5 (Throughput of lost packets)Delay jitter

In case of delay jitter for end-to-end delay WF2Q+

performs better when bandwidth is low. With increase in

bandwidth all the schedulers tend to merge together. The

low delay jitter bound shows that WF2Q+ is more suited

to interactive applications (audio, video streaming) than

the others.

Figure 6(Delay jitter)

Fairness

Fairness to the flows is the most important feature of all

the algorithms discussed here. Here too WF2Q+ performs

better than other schedulers when link bandwidth is low.

As the conditions become more favourable SFQ starts

dominating.

Figure 7 (Fairness)

Although SFQ computes the virtual start and finish times

of packets faster it doesnt follow/approximate GPS.

Since WF2Q+ is based on simulating GPS with less

complexity it performs well under low bandwidth,

whereas SFQ dominates when bandwidth is increased.

VI CONCLUSION

In this report we compared several packet scheduling

(queue management) algorithms (WFQ, WF2Q+, SCFQ

and SFQ) based on simulation results. We have presented

our simulation setting, comparison result and algorithm

characteristics. Its still hard to conclude which

algorithm is better in all aspects than another. But the

major trends are:

End-to-end delay for all the algorithms are almost thesame

WF2Q+ shows better results in case of unfavorableconditions like low bandwidth and high traffic, SFQ on

the other hand performs well in optimal conditions.

All the algorithms tend to behave identically asbandwidth increases beyond a certain speed.

WFQ and WF2Q+ has computation overhead perincoming packet their space requirements are different.

The following table summaries our evaluation results:

Algori

thms

Fairne

ss

Delay

Jitter

Avera

ge

throug

hput

Packet

Loss

Algori

thmic

Compl

exity

End to

end

Delay


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WFQ Not

Good

Not

Good

Good Not

Good

Not

Good

Un

Affect

ed

WF2Q

+

Better Best Not

Good

Good Good Un

Affect

ed

SCFQ Good Better Better Better Good Un

Affect

edSFQ Best Good Best Best Good Un

Affect

ed

Figure 8 (Comparison Table)

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19 a Comparative Analysis of Time Stamped