A Foundation for Stochastic Bandwidth Estimation
of Networks with Random Service
ABSTRACT:
We develop a stochastic foundation for bandwidth estimation of networks with random service, where bandwidth availability is expressed in terms of bounding functions with a defined violation probability. Exploiting properties of a stochastic max-plus algebra and system theory, the task of bandwidth estimation is formulated as inferring an unknown bounding function from measurements of probing traffic. We derive an estimation methodology that is based on iterative constant rate probes. Our solution provides evidence for the utility of packet trains for bandwidth estimation in the presence of variable cross traffic. Taking advantage of statistical methods, we show how our estimation method can be realized in practice, with adaptive train lengths of probe packets, probing rates, and replicated measurements required to achieve both high accuracy and confidence levels. We evaluate our method in a controlled test bed network, where we show the impact of cross traffic variability on the time-scales of service availability, and provide a comparison with existing bandwidth estimation tools.
Existing System:
Ø The ad hoc networking community assumes that the underlying wireless technology is the IEEE 802.11 standard due to the broad availability of interface cards and simulation models.
Ø This standard has not been targeted especially for multihop ad hoc operation, and it is therefore not perfectly suited to this type.
Ø An accurate evaluation of the capabilities of the routes is necessary. Most of the current QoS proposals leave this problem aside, relying on the assumption that the link layer protocols are able to perform such an evaluation.
Proposed System:
Ø In this system they are using 802.11 MAC layer to evaluate the correct bandwidth.
Ø This method combines channel monitoring to estimate each node’s medium occupancy.
Ø Probabilistic combination of the values is to account for synchronization between nodes, estimation of the collision probability between each couple of nodes, and variable overhead’s impact estimation.
Ø This mechanism only requires one-hop information communication and may be applied without generating a too high additional overhead.
Ø We show the accuracy of the available bandwidth measurement through NS-2 simulations.
Ø These results show that single-hop flows and multihop flows are admitted more accurately, resulting in a better stability and overall performance.
System Requirements
Hardware:
PROCESSOR : PENTIUM IV 2.6 GHz
RAM : 512 MB DD RAM
MONITOR : 15” COLOR
HARD DISK : 20 GB
FLOPPY DRIVE : 1.44 MB
CDDRIVE : LG 52X
KEYBOARD : STANDARD 102 KEYS
MOUSE : 3 BUTTONS
Software:
Front End : Java, Swing
Back End : MS Access
Tools Used : JFrameBuilder
Operating System : WindowsXP
Modules
Ø Packet creation
Ø Apply the RREQ And get RREP
Ø Admission Control Mechanism
Ø Utilized Bandwidth
Module Description
Packet Creation
In this module we split the Data in to N number of Fixed size packet with Maximum length of 48 Characters.
Apply the RREQ and get RREP
The aim of the RREQ is to find a route between the sender and the receiver that meets the constraints specified by the application level in terms of Bandwidth. Therefore, two flows with the same source and destination can follow different routes depending on the network state.
When a source node has data to send, it broadcasts a route request (RREQ) to its neighbors. The RREQ packet contains the address of the sender, and the requirements at the application level, the destination address, and a sequence number. The Intermediate Node or Destination Node sends RREP if it is free, otherwise, it silently discards the message.
Admission Control Mechanism
The Admission Control Mechanism is done in the receiver side. The Admission Control Mechanism has the all status of the node so if the nodes want to send RREP or discard the message, the particular node check the status by using the Admission Control Mechanism.
Bandwidth Utilized
After the source nodes send the total message to the Destination Node finally we calculate the end to end delivery of the Bandwidth and Time delay.
REFERENCE:
Ralf Lubben Markus Filder, Jorg Liebeherr, “A Foundation for Stochastic Bandwidth Estimation of Networks with Random Service”, IEEE Infocom 2011.
