International Journal of Scientific & Engineering Research Volume 3, Issue 8, August-2012 1
ISSN 2229-5518
Swathi Y Mr.Sundeep Kumar Mr.Manoj Challa Dr.Jitendranath Mungara
I INTRODUCTION
An efficient multi-users uses OFDM based broadband wireless systems. There in, adaptation decisions are made solely based on the long-term average channel conditions instead of fast channel fading. Specifically channel parameters are replaced by their mean values, resulting in a deterministic rather than stochastic optimization problem. By doing so, quality-of-service (QoS) can only be guaranteed in a long-term average sense, since the short- term fluctuation of the channel is not considered in the problem formulation. With the increasing popularity of wireless multimedia applications, however, there will be more and more inelastic traffic that require a guarantee on the minimum short-term data rate. As such, slow adaptation schemes based on average channel conditions cannot provide a satisfactory QoS.
In this paper, we propose a TDMA based multi channel MAC protocol to improve the channel efficiency and network performance in wireless ad hoc networks. Realizing the relationship between the transmission power and retransmissions on a link determining the optimal transmission power, we build a cross-layer design-based nonlinear optimization model which aims at minimizing the network-wide energy consumption. We solve this problem by transforming it into two sub problems with less complexity. Results reveal the advantage of the cross-layer optimization model in energy conservation, and the effectiveness of the time scheduling algorithm in reducing the TDMA frame length, and thus, the end-to-end latency
Finally, it should be noted that in this paper, a slot is reused only if the interference introduced is negligible.
Consider slot reuse with non-negligible same slot and
interfering with each other. In this case, the trade-off between energy
consumption and frame length (or delay) needs to be
investigated. The rest of the paper is organized as follows. Section II discusses the existing system, Section III deals with our proposed system, Section IV deals with implementation Section V deals with results and finally Section VI and VII deals with conclusion and future enhancement of this paper
II. RELATED WORK
Zhong Zhou proposed an OFDM based MAC Protocol for wireless systems.OFDM scheduling is extremely complex compared to TDMA requiring more higher computational power and memory.Near far problems in OFDM substantially reduces performance.In this type of system if an user is sending some info through one channel and if it takes more memory then until the completion of this the second channel can’t send anything.If the channels are idle means it won’t go to sleep mode thereby wasting energy. When multiple channels are available, the
fixed channels of various nodes are distributed across the
available channels. Thus, since the number of nodes using a specific channel decreases, over-heads of MAC contention
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International Journal of Scientific & Engineering Research Volume 3, Issue 8, August-2012 2
ISSN 2229-5518
on each channel reduces. However,since existing incurs the packet collisions due to the multi-channel hidden node
problem and the packet drops due to queue overflow, the overall network throughput does be not largely increased.
III. PROPOSED SYSTEM
We propose a cross-layer optimization scheme called traffic-adaptive scheme for Multimedia operating over a time division multiple access (TDMA) channel.Based on the traffic condition and buffer status, this scheme employs a Markov Decision Process (MDP) and MAC Protocol to determine the optimal value of the maximum number of simultaneous data frames that can be transmitted in each time slot of a TDMA Channel frame so as to minimize the overall FLR of the system. To facilitate implementation, we also propose an approximation scheme named the rate adaptive scheme to reduce the computation cost. Simulation and analytical results show that both the traffic- adaptive scheme and rate-adaptive scheme can significantly reduce FLR, increase the system throughput, and optimize the packet access delay of the system. Furthermore, the rate-adaptive scheme can achieve a
performance close to the traffic-adaptive scheme when the
int rc = base.dftsub.getRowCount();
for (int i = 0; i < rc; i++) {
String sc = base.dftsub.getValueAt(i, 3).toString();
if (sc.equals("")) {
int scport = Integer.parseInt(base.dftsub.getValueAt(i, 2)
.toString()
base.dftsub.setValueAt("Busy", i, 3);
Socket socket = new Socket("localhost", scport); ObjectOutputStream oos = new ObjectOutputStream(socket.getOutputStream()); oos.writeObject("REQ");
oos.writeObject(cnme);
oos.writeObject(file);
oos.writeObject(port);
B. MMPP Traffic
The MMPP model has been shown to be effective in representing many types of multimedia traffic, including voice, MPEG video, and general data. We apply the MMPP model for all the traffic flows in the system (note that the Poisson model is a special case of the MMPP model).
traffic load in the system is high.
IV. IMPLEMENTATION
Check
Here we are discussing the modules related to implementing this paper.These are organized as follows
A. Multi code TDMA System
We consider a MAC multichannel system employing time division multiple access (TDMA) and Multimedia in each TDMA time slot. We focus on the uplink common traffic channel in one radio cell.Without loss of generality, the uplink common traffic channel is divided into TDMA frames of duration TF and each TDMA frame consists of a
C. Scheduling
fixed number (F) of time slots,each with a duration of
Ts.Also we assume that perfect signaling channels exist for the mobile stations to convey their states (e.g., data rates and queue lengths) at the end of each TDMA frame to the base station, and for the base station to inform the mobile stations about the channel status and the transmission schedule for the next TDMA frame before it starts.
This is summarized as follows
private void setSubcarrier(String cnme,String file, int port) {
// TODO Auto-generated method stub
try {
The scheduling algorithm decides how to schedule data frames from each traffic flow in a TDMA frame so that the system can provide fairness to different traffic flows.
D. Queue Analysis
Before presenting the optimization of u, we
need to first analyze the average number of data frame losses in a TDMA frame given the upper bound u of the number of simultaneous data frame transmissions in a slot, the buffer state vector N!, the traffic state vector D!, the slot allocation, and the scheduling decision vector
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International Journal of Scientific & Engineering Research Volume 3, Issue 8, August-2012 3
ISSN 2229-5518
E. Slot Allocation
Given u, the maximum number of the simultaneous data frame transmissions allowed in one time slot and M!, the scheduling decision vector, the system also need to inform the mobile stations in which time slot their scheduled data frames should be transmitted. If exactly u data frames are transmitted in every time slot, the BER of all data frames can be easily determined. However, if there are not so many data
Figure3:ChannelAllocation
frames transmitted in one TDMA frame, the BER of a data frame varies with the number of data frames transmitted in the same time slot. In other words, the BER depends on the slot allocation scheme.
F. Traffic Adaptive Optimization
In this paper, we focus on the cross-layer optimization of u, the upper bound of the number of simultaneous data frame transmissions in each time slot of a TDMA frame. The objective is to minimize the FLR (i.e., taking into consideration both FER and FDR) of the system so that the channel throughput is maximized (Note that the throughput is the aggregate packet arrival rate factored by (1-FLR)). To make such an optimization, the system needs to know the scheduling function and the slot allocation.The slot allocation used in this paper is described in Section 3.3. We will also show a specific scheduling function which minimizes the FLR of every TDMA frame. The algorithm is summarized as follows
private void checkStatus(String str) {
try {
if (str.equals("REP")) {
byte[] file=(byte[])ois.readObject();
String filename= (String)ois.readObject();
String scn=(String)ois.readObject(); user.dft.addRow(new Object[]{scn,filename}); lrecFile=newFile("RecFiles/"+scn+"_"+filename); FileOutputStreamfos=new FileOutputStream(lrecFile); fos.write(file);
fos.close();
JOptionPane.showMessageDialog(null, "LastReceivedFile
is:"+lrecFile.getAbsolutePath());
} else if (str.equals("Data")) {
}
} catch (Exception e) {
e.printStackTrace();
}
G. Queue Analysis
Before presenting the optimization of u, we need to first analyze the average number of data frame losses in a TDMA frame given the upper bound u of the number of simultaneous data frame transmissions in a slot, the buffer state vector N!, the traffic state vector D!, the slot allocation, and the scheduling decision vector.
H. Multimedia database Optimization
This optimization method is based on the following principle. The more data frame transmissions are allowed in every time slot in a TDMA frame, the higher chance the data frames are transmitted with errors and the less chance the buffers overflow. Especially, a larger upper bound of the number of simultaneous transmissions in one time slot for a TDMA frame may decrease the large FDR experienced when the traffic flows are in a “burst” (i.e., a large number of data frames arriving in a short period). Since the FLR accounts for both frame errors and frame drops, the minimal FLR can be attained by choosing an appropriate upper bound of the number of data frame transmissions allowed in every time slot.The algorithm is summarized as follows
public void mediaPlayer(final String path, final JPanel panel) {
new Thread() { public void run() { try {
Playerp=Manager.createRealizedPlayer(new
File(path).toURL());
Componentctrlpanel= p.getControlPanelComponent(); Componentplayer= p.getVisualComponent(); player.setBounds(10, 20, 300, 170);
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International Journal of Scientific & Engineering Research Volume 3, Issue 8, August-2012 4
ISSN 2229-5518
ctrlpanel.setBounds(10, 191, 300, 20);
panel.add(player);
panel.add(ctrlpanel); panel.repaint(); p.start();
System.out.println(" Player Started");
}
V. SIMULATION RESULTS
We compared the throughput and energy savings
Of existing and proposed systems by using ns-2
simulator.Results shows that proposed system provides increase in throughput and less energy savings than existing system
When multiple channels are available, the fixed
channels of various nodes are distributed across the
available channels. Thus, since the number of nodes using a specific channel decreases, over-heads of MAC contention on each channel reduces. However,since existing incurs the packet collisions due to the multi-channel hidden node problem and the packet drops due to queue overflow, the overall network throughput does be not largely increased compared to the proposed MAC protocol.
Simulation results for this paper shows to improve throughput and energy savings as the channel that is unused goes to sleep mode there by reducing energy savings.
Fig 4 shows the TDMA system has increase in throughput with the increase in no of channels.Fig 5 shows the average energy consumption per node.The proposed system allows a node to go to sleep mode in a data slot whenever it is not scheduled to tansmit or receive a packet.In existing system all nodes stay awake.Hence the energy consumption will be less in proposed system
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existing
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proposed
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Packet arrival rate(packets/sec)
VI.CONCLUSION & FUTURE ENHANCEMENT
In this paper, we have proposed a traffic-adaptive TDMA optimization scheme for Multimedia operating over a TDMA framework.Our scheme seeks to determine the maximum number of simultaneous data frame transmissions that can be supported in a time slot of a TDMA frame. To facilitate implementation, we also propose an approximation scheme called the rate-adaptive scheme.Both schemes aim to jointly optimize the physical layer’s BER and the MAC layer’s FDR to minimize the overall FLR.System results show that these two schemes can improve the FLR and throughput
The current work does not impose a limit on the frame
length; hence, there are no assignment failures during the execution of the proposed scheduling algorithm. In practice, the frame length is fixed. Future work is needed to extend the proposed framework to the scenarios of slot reuse with non-negligible interference and fixed frame length.
REFERENCES
[1] Jungmin So and Nitin H. Vaidya, "Multi-channel MAC
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No Of Channels
existing proposed
for ad hoc networks: handling multi-channel hidden
terminals using a single transceiver," in ACM Mobihoc, pp. 222-233, 2006.
[2] T. Luo, M. Motani and V. Srinivasan, "CAM-MAC: A cooperative asynchronous multi-channel MAC protocol for ad hoc networks," in Proc. of 3rd International Conference on Broadband Communications, Networks and Systems
(BROADNETS 2006), pp. 1-10, Oct. 2008
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International Journal of Scientific & Engineering Research Volume 3, Issue 8, August-2012 5
ISSN 2229-5518
[3]. S. Kumar, V. S. Raghavan and J. Deng, "Medium access control protocol for ad hoc wireless networks: a survey,"
Ad-Hoc Networks, vol. 4, no. 3, pp. 326-358, Mar. 2008.
[4] W.-H. Liao, K.-P. Shih and W.-C. Chung, "Multi-channel medium access control protocol with channel distribution for mobile ad hoc networks," IET Communications, vol. 3, no. 12, pp. 1821-1831, Dec. 2009
[5] Zhong Zhou, Son Le and Jun-Hong Cui Computer Science & Engineering, University of Connecticut, Storrs, CT, 06269, USA “An OFDM Based MAC Protocol for Underwater Acoustic Networks”
[6] Chi-Yu Li, An-Kai Jeng and Rong-Hong Jan, "A MAC protocol for multi-channel multi-interface wireless mesh network using hybrid channel assignment scheme," Journal of Information Science and Engineering, Vol. 23, pp. 1041-
1055, 2010
[7] http://www.isi.edu/nsnam/ns.
Authors
Mrs.Swathi Y is presently doing Master of Technology in computer networks and engineering in CMR Institute of Technology, Bangalore Karnataka.She obtained her Bachelor of Engineering degree in computer science
and engineering from NBKR College of Engineering, Vakadu, Andhra Pradesh, India in the year 2003.
K Sundeep Kumar received the M.Tech (IT) from Punjabi University in 2003, ME (CSE) from Anna University in 2009 and pursuing Ph. D (CSE) from JNTUA. He is with the department
of Computer Science & Engineering and as an Associate
Professor, CMR Institute of Technology, Bangalore. He presented more than 10 papers in International and national Conferences. His research interests include OOMD, Software Engineering and Data Warehousing. He is a life member in ISTE.
Mr. Manoj Challa is pursuing Ph.D. in S.V.University, Tirupati, India. He completed his M.E (CSE) from Hindustan College of Engineering, Padur, Tamil Nadu, and India in year 2003. He is presently working as Associate Professor at CMR Institute of Technology, Bangalore, and Karnataka, India.He presented nearly 10 papers in national and international conferences.His research areas include Artificial intelligence and computer networks
Dr.M.Jitendranath is double doctorate in Electronics and Computer Science Engineering and working as Prof & Dean of Research in Computer Science Engineering department in CMRIT, Bangalore. He has published 35 papers in the area of Mobile ad hoc Networks international journals.
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Internatio nal Jo urnal
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ISSN 2229-5518
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Volume 3, Issue 8, August-2012
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