Latency
Equalization as a New Network Service Primitive(2012)
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Abstract
Multiparty interactive network
applications such as teleconferencing, network gaming, and online trading are
gaining popularity. In addition to end-to-end latency bounds, these
applications require that the delay
difference among multiple clients of the service is minimized for a good
interactive experience. We propose a Latency EQualization
(LEQ) service, which equalizes the perceived latency for all clients
participating in an interactive network application. To effectively implement
the proposed LEQ service, network support is essential. The LEQ architecture
uses a few routers in the network as hubs to redirect packets of interactive applications
along paths with similar end-to-end delay. We first formulate the hub selection
problem, prove its NP-hardness, and provide a greedy algorithm to solve it.
Through extensive simulations, we show that our LEQ architecture significantly
reduces delay difference under different optimization criteria that allow or do
not allow compromising the per-user end-to-end delay. Our LEQ service is
incrementally deployable in today’s networks, requiring just software
modifications to edge routers.
Introduction
The
increased availability of broadband access has spawned a new generation of
netizens. Today, consumers use the network as an interactive medium for
multimedia communications and entertainment. This growing consumer space has
led to several new network applications in the business and entertainment
sectors. End-to-end delay requirements can be achieved by traffic engineering
and other QoS techniques. However, these approaches are insufficient to address
the needs of multiparty interactive network applications that require bounded
delay difference across multiple clients to improve interactivity. Previous
work on improving online interactive application experiences considered
application-based solutions either at the client or server side to achieve equalized
delay. Client side solutions are hard to implement because they require that
all clients exchange latency information to all other clients. They are also
vulnerable to cheating .Server-side techniques rely on the server to estimate
network delay, which is not sufficiently accurate in some scenarios. Moreover,
this delay estimation places computational and memory overhead on the
application servers, which limits the number of clients the server can support.
Previous studies have investigated different interactive applications, and they
show the need for network support to reduce delay difference since the prime
source of the delay difference is from the network. The importance of reducing
latency imbalances is further emphasized when scaling to wide geographical
areas as witnessed by a press release from AT&T.
We design and implement network-based Latency EQualization (LEQ), which is a
service that Internet service providers (ISPs) can provide for various
interactive network applications. Compared to application-based latency
equalization solutions, ISPs have more detailed knowledge of current network
traffic and congestion, and greater access to network resources and routing
control. Therefore, ISPs can better support latency equalization routing for a large
number of players with varying delays to the application servers. This support
can significantly improve game experience, leading to longer play time and thus
larger revenue streams.
Problem Description
Client side solutions are hard
to implement because they require that all clients exchange latency information
to all other clients. They are also vulnerable to cheating. Server-side
techniques rely on the server to estimate network delay, which is not
sufficiently accurate in some scenarios. We design and implement network-based Latency EQualization (LEQ), which is a
service that Internet service providers (ISPs) can provide for various
interactive network applications. Compared to application-based latency
equalization solutions, ISPs have more detailed knowledge of current network
traffic and congestion, and greater access to network resources and routing
control. Therefore, ISPs can better support latency equalization routing
for a large number of players with varying delays to the application servers.
This support can significantly improve game experience, leading to longer play
time and thus larger revenue streams. Due to the problems of client-side
solutions, several delay compensation schemes are implemented at the server
side. However, while introducing CPU and memory overhead on the server, they
still do not completely meet the requirements of fairness and interactivity.
For example, with the bucket
synchronization mechanism , the received packets are buffered in a bucket,
and the server calculations are delayed until the end of each bucket cycle. The
performance of this method is highly sensitive to the bucket (time window) size
used, and there is a tradeoff between interactivity versus the memory and
computation overhead on the server. In the time
warp synchronization scheme, snapshots of the game state are taken before the
execution of each event. When there are late events, the game state is rolled
back to one of the previous snapshots, and the game is reexecuted with the new
events. This scheme does not scale well for fast-paced, high-action games
because taking snapshots on every event requires both fast computation and
large amounts of fast memory, which is expensive. In , a game-independent
application was placed at the server to equalize delay differences by
constantly measuring network delays and adjusting players’ total delays by
adding artificial lag. However, experiments in [12 suggest that using
server-based round-trip-time measurements to design latency compensation across
players fails in the presence of asymmetric latencies.
Existing System
Improving
online interactive application experiences considered application-based
solutions either at the client or server side to achieve equalized delay.
Client side solutions are hard to implement because they require that all
clients exchange latency information to all other clients. They are also
vulnerable to cheating. Server-side techniques rely on the server to estimate
network delay, which is not sufficiently accurate in some scenarios. This delay
estimation places computational and memory overhead on the application servers,
which limits the number of clients the server can support . Previous studies
have investigated different interactive applications, and they show the need
for network support to reduce delay difference since the prime source of the
delay difference is from the network. The importance of reducing latency
imbalances is further emphasized when scaling to wide geographical areas as
witnessed by a press release from AT&T .
Proposed System
The
design and implement network-based Latency EQualization (LEQ), which is a
service that Internet service providers (ISPs) can provide for various
interactive network applications. Compared to application-based latency
equalization solutions, ISPs have more detailed knowledge of current network
traffic and congestion, and greater access to network resources and routing
control. Therefore, ISPs can better support latency equalization routing for a
large number of players with varying delays to the application servers. This
support can significantly improve game experience, leading to longer play time
and thus larger revenue streams. Our network-based LEQ service provides
equalized-latency paths between the clients and servers by redirecting interactive
application traffic from different clients along paths that minimize their
delay difference. We achieve equalized-latency paths by using a few routers in
the network as hubs, and interactive application packets from different clients
are redirected through these hubs to the servers. Hubs can also be used to
steer packets away from congested links.
Our LEQ
architecture provides a flexible routing framework that enables the network
provider to implement different delay and delay difference optimization
policies in order to meet the requirements of different types of interactive
applications.
To
achieve LEQ routing, we formulate the hub selection problem, which decides
which routers in the network can be used as hubs and the assignment of hubs to
different client edge routers to minimize delay difference. We prove that this
hub selection problem is NP-hard and inapproximable. Our LEQ routing
significantly reduces delay difference in different network settings
Advantages:
LEQ is
achieved by optimized hub selection and assignment. Each client edge router is
assigned to more than one hub, so it has the flexibility to select among its
assigned hubs to avoid congestion. Our LEQ routing significantly reduces delay
difference in different network settings
Module List
Ø
Login
Ø
Client Node
Ø
Hub Selection process
Ø
Server Node
Ø
Latency EQualization (LEQ)
Ø
LEQ Hub Routing
Module Description
Login
In this
module the user can get in to the system by enter the username and password.
The user can register them self in the particular node. Therefore we can easily
identify a Client node, where it is resident.
Client Node
Client
traffic from an interactive application enters the provider network through
edge routers R1 and R2. The server for the interactive application is connected
to the network through edge router R10. Using the LEQ routing architecture, R6
and R7 are chosen as hubs for R1 , R7 and R8 are chosen as hubs for
R6.Usingredirection through hubs, R1 has two paths to the server edge router
R10:R1-R6-R10 and R1-R7-R10, both of which have a delay of 10ms. R2 has two
paths R2-R7-R10 and R2-R8-R10, whole delay is also 10ms.Each client edge router
is assigned to more than one hub, so it has the flexibility to select among its
assigned hubs to avoid congestion.
Server Node
R1 ,R2 …
are routers in the network. Server side edge router R10.Server node from an
interactive application enters the provider network through edge routersR10.The
number of the links represent the latency of each link R6,R7 and R8 are the hubs
for R1,R2 and R10.Client edge routers redirect the application packets
corresponding to the LEQ service through the hubs to the destined servers. By
redirecting through the hubs, application packets from different client edge
routers with different delays to the servers are guaranteed to reach the
servers within a bounded delay difference. The average delay difference for
packets from different sites to the server through these two hubs.
Hub selection process
To solve
the hub selection problem, we design a simple greedy heuristic algorithm
to pick
the hubs. Our algorithm first sorts in increasing order all the delays from
each client edge router through each possible hub to its associated servers.
This sorted list is denoted by the array.
One could
use source routing to address the problem of latency equalization. Source
routing can be used by the sender to choose the path taken by the packet.
However, this requires that all clients are aware of the network topology and
coordinate with each other to ensure that the delay differences are minimized.
LEQ
We design and implement network-based Latency EQualization (LEQ), which is a
service that Internet service providers (ISPs) can provide for various
interactive network applications. Compared to application-based latency
equalization solutions, ISPs have more detailed knowledge of current network
traffic and congestion, and greater access to network resources and routing
control. Therefore, ISPs can better support latency equalization routing for a
large number of players with varying delays to the application servers. This
support can significantly improve game experience, leading to longer play time
and thus larger revenue streams.
Network-based
LEQ service provides equalized-latency paths between the clients and servers by
redirecting interactive application traffic from different clients along paths
that minimize their delay difference.
LEQ Hub Routing
The network-based LEQ
architecture is implemented using a hub routing approach: Using a small number
of hubs in the network to redirect application packets, we equalize the delays
for interactive applications. To explain the basic LEQ architecture, we
consider a single administrative domain scenario and focus on equalizing
application traffic delays between the different client edge routers and the
server edge routers without considering access delay. Based on the
application’s LEQ requirements, the application traffic from each client edge
router is assigned to a set of hubs. Client edge routers redirect the application
packets corresponding to the LEQ service through the hubs to the destined
servers. By redirecting through the hubs, application packets from different
client edge routers with different delays to the servers are guaranteed to
reach the servers within a bounded delay difference.
Software Requirements
Front
End/GUI Tool
: Microsoft
Visual studio 2008
Operating
System
: Windows family
Language
: C#.NET
Backend
: SQL Server 2005
Hardware Specification
Processor
: Pentium
dual core
RAM
: 1 GB
Hard Disk
Drive
: 80 GB
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