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\def\makelabel##1{\upshape ##1}}% } {\end{list}\end{raggedright}} \newenvironment{specHead}[2]% {\vspace{20pt}\hrule\vspace{10pt}% \phantomsection\label{#1}\markright{#2}% \pdfbookmark[2]{#2}{#1}% \hspace{-0.75in}{\bfseries\fontsize{16pt}{18pt}\selectfont#2}% }{} \def\TheFullDate{2012-01-15 (revised: 15 January 2012)} \def\TheID{\makeatother } \def\TheDate{2012-01-15} \title{Ordered Cross Layer Approach for Multicast Routing in Mobile Ad hoc Networks: Qos by Clogging Control} \author{}\makeatletter \makeatletter \newcommand*{\cleartoleftpage}{% \clearpage \if@twoside \ifodd\c@page \hbox{}\newpage \if@twocolumn \hbox{}\newpage \fi \fi \fi } \makeatother \makeatletter \thispagestyle{empty} \markright{\@title}\markboth{\@title}{\@author} \renewcommand\small{\@setfontsize\small{9pt}{11pt}\abovedisplayskip 8.5\p@ plus3\p@ minus4\p@ \belowdisplayskip \abovedisplayskip \abovedisplayshortskip \z@ plus2\p@ \belowdisplayshortskip 4\p@ plus2\p@ minus2\p@ \def\@listi{\leftmargin\leftmargini 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\textcolor{GJMediumGrey}{\rule{\textwidth}{2pt}} \vskip16pt \textcolor{GJBlue}{\large\bfseries\abstractname\space} }{% \vskip8pt \textcolor{GJMediumGrey}{\rule{\textwidth}{2pt}} \vskip16pt } \usepackage[absolute,overlay]{textpos} \makeatother \usepackage{lineno} \linenumbers \begin{document} \author[1]{Nagaraju Mittapally } \affil[1]{ Netaji institute of engineering and technology, Hyderabad, AP, India.} \renewcommand\Authands{ and } \date{\small \em Received: 16 December 2011 Accepted: 4 January 2012 Published: 15 January 2012} \maketitle \begin{abstract} Here in this paper a MAC layer level clogging detection system has been projected. The planned model aims to explores a system to compute the degree of clogging at victim node with maximal accuracy. This clogging detection apparatus is integrated with a Two-Step Cross Layer Clogging Control Routing Topology. The proposed model involves controlling of clogging in two steps with effective energy capable blocking detection and optimal cost of routing. Packet drop in routing is mostly due to link crash and clogging. Most of the existing clogging control solutions do not have the ability to distinguish between packet loss due to link collapse and packet loss due to clogging. As a result these solutions aim towards action against packet drop due to link malfunction which is an unnecessary effort and ends with of energy resources. The other limit in most of the available way out is the utilization of energy and resources to detect clogging state, degree of clogging and alert the source node about blocking in routing path. This paper explores a cross layered model of clogging recognition an control mechanism that include energy efficient clogging detection, Multicast Group Level Clogging Evaluation and Handling Algorithm [MGLCEH] and Multicast Group Level Load Balancing Algorithm [MGLLBA], which is a hierarchical cross layered base clogging recognition and avoidance model in short can refer as Qos Optimization by cross layered clogging handling (MGLCEH). This paper is supported by the investigational and simulation results show that better store utilization, energy efficiency in clogging detection and clogging control is possible by the proposed topology. \end{abstract} \keywords{Ad-hoc networks, manets, clogging, cross-layer design, optimization, random access, wireless network.} \begin{textblock*}{18cm}(1cm,1cm) % {block width} (coords) \textcolor{GJBlue}{\LARGE Global Journals \LaTeX\ JournalKaleidoscope\texttrademark} \end{textblock*} \begin{textblock*}{18cm}(1.4cm,1.5cm) % {block width} (coords) \textcolor{GJBlue}{\footnotesize \\ Artificial Intelligence formulated this projection for compatibility purposes from the original article published at Global Journals. However, this technology is currently in beta. \emph{Therefore, kindly ignore odd layouts, missed formulae, text, tables, or figures.}} \end{textblock*} \let\tabcellsep& \section[{Introduction}]{Introduction}\par he regular TCP clogging control mostly adapted for internet is not an apposite for MANETs because MANETs are known to affect topology and topology stacks of control mechanisms .also the MANETs are environmentally irreconcilable with standard TCP.\par The packet salvage setbacks and losses in MANETs are primarily due to their node mobility combined with intrinsically unexpected medium which is a direct consequence of the common wireless multi hop channel cannot be construe as clogging losses .\par The primary individuality of a wireless multi hop channel is that within interfering range of one node only a single data is transmitted. In MANETs' networks in an complete area are congested due to shared standard where as internet clogging is single router. A note valuable point is that in a MANET the nodes are not overcrowded.\par The main reason for the incompatible of a regular TCP and a MANET is the fact that package losses in MANET may not always be due to network clogging and the transmission times (including the round trip times) vary highly making the package losses quite difficult to observe .\par It is difficult to find the source of clogging in a multi hop network because a single user has the capability to produce a clogging resulting in comparatively lower bandwidth of mobile ad-hoc networks .The wireless networks are more susceptible to clogging problems when compared with the traditional wire line network. Therefore a balanced clogging control system is to be employed compulsorily for the stability and superior performance of a wireless network.\par The non homogeneous nature of the application topologys in the multihop wireless networks, a single and unified solution for the clogging related problems cannot be obtained .Instead a suitable clogging control depending upon the properties and functions of the related network can be designed .As a result, these proposal majorly form a subset of solutions for the identified problems rather than a complete, instantly used topology. They pose as a parent for applicationtailored topology stacks. Exceptionally, few of the topology properties serve wide range of applications.\par The recent years have witness a much more focus on the clogging control methods directed on the modeling, analysis, algorithm development of closed loop control schemes (e.g. TCP) making them sympathetic for adaption to the mobile hoc networks .under the provision of constraints of routing path and bandwidth algorithms possessing the ability to unify and stabilize operation have been evolved .Another major constraint to be painstaking in a wireless hoc network is due to the MAC[Media access Control) layer. Majority of( D D D D )\par wireless MACs possess a time constriction permitting a single user to access a physical channel at a given time. The sections in the paper are organized to provide the following details as regards. The section2 explores the most cited works in the area of text .section3 gives a detail discussion of the projected topology and section 4 relies on the simulation and their results to be consummate by conclusion and references. \section[{a) Related Work}]{a) Related Work}\par QoS centric clogging control solution can be found in \hyperref[b0]{[1]}. was Yung Yi et al \hyperref[b14]{[13]} proposed few metrics for clogging aware routing ] Xiaoqin Chen et al \hyperref[b1]{[2]} introduced metrics to evaluate data-rate, MAC transparency and buffer delay, which helps to identify and deal the blocking contention area in network. Hongqiang Zhai, et al., \hyperref[b2]{[3]} projected a solution by arguing that clogging and severe medium debate is interrelated. Tom Goff et al., \hyperref[b4]{[5]} discussed a set of algorithms that initiates different path usage when the quality of a path in use turns out to be suspect. A crosslayer hop-by-hop clogging control scheme projected by Xuyang et al., \hyperref[b5]{[6]} to improve TCP performance in multihop wireless networks. Dzmitry et al \hyperref[b6]{[7]} presents the impact blocking on transport layer that decreases the performance. Duc et al. \hyperref[b16]{[15]} proposed that current designs for routing are not adjustable to clogging.\par The existing models aim at identify clogging losses in routing path .The packet loss generate a link failure. Making efforts to manage the packet losses that cause link failure are in effective. Another exclusive approach is regularizing the outflow at all nodes participating in routing. In majority of cases of control the clogging at hop level \hyperref[b14]{[13]} \hyperref[b7]{[8]}. Henceforth outflow regularization at each node of the network involves operation of expensive wealth. Here in this paper we argue that it is a important to identify the reason for packet loss. Hence we can avoid the clogging control process via outflow regularization under the status of link failure. And also we continue the spat that hop level blocking control alone is not plenty when the hop levels are unable to normalize themselves. The outflow load to control the blocking by utilizing the same resources can be done as in spring level outflow regularization models. Here we propose a cross layer based clogging control routing topology that contains Clogging detection and clogging control models. \section[{II.}]{II.} \section[{Groups Structure Based Multi Cast}]{Groups Structure Based Multi Cast}\par Routing: An ordered cross layer approach for qos provisioning by clogging control a) Measuring degree of clogging at Relay hop level node Unlike conventional networks, nodes in the ad hoc network exhibit a high degree of heterogeneity in terms of both hardware and software configurations. The heterogeneity of the relay hop nodes can reflect as varied radio range, maximum retransmission counts, and barrier capacity. Hence the degree of communication load, packet drop frequency, and degree of buffer consumption at relay hop level node is minimum combination to find the degree of clogging. The usage of these three purposeful values supports to decouple the clogging measure process from other MAC layer behavior.\par The degree of channel load, packet drop rate and degree of buffer operation together provide a scope to envisage the blocking due to inappropriate ratio between collision and retransmission count. When retransmissions compared to collision rate are significantly low then outflow delay of relay hop node will increase proportionally, which leads to clogging and reflected as clogging due to buffer overflow. \section[{b) Measuring degree of clogging at path level traffic}]{b) Measuring degree of clogging at path level traffic}\par The degree of clogging at each relay hop together helps to identify the degree of clogging at path level traffic from source to goal node. Each relay hop level node receives the degree of clogging from its neighbor node in hierarchy. Since the destination node, which is last node of the routing path is not outlet the emptiness status. Hence the destination node initiates to assess the degree of clogging at path level traffic. The interrupted updates of clogging status at each relay hop level node to its heir in routing path is significantly energy consuming activity. Hence to conserve the energy, the clogging update strategy considers two restricted behavior, which follows: III. \section[{Cross layered model for Clogging Control}]{Cross layered model for Clogging Control}\par The packet dipping often occurs in Manets. The reasons for this packet plummeting are as below We opt to the approach described by Mohammad M. Qabajeh et al \hyperref[b16]{[15]}. With the knowledge of the presented nodes the region is divided into equal partitions. Hexagon is mostly chased for the zonal shape because it covers a highest surface and also provides the improvement of communicating with more neighbors as they have near circular shape of the transmitter. The availability of small, economical low power GPS receiver makes it possible to apply positionbased in MANETs. The communication range of node is denote as R and the side of hexagon as L.As the nodes should be able to correspond with each other the R and L are related as L=R/2. Each Group has a Group characteristics ( zid ), Group Header ( zh ) and Group Leader Backup ( ' zh ).\par The zh node maintains in sequence about all the nodes in a Group with their positions and IDs. Also, maintain information about the zh of the neighboring Cells as shown in the figure {\ref 1}. The CLB node keeps a copy of the data stored at the zh so that it is not lost when the zh node is off or touching the Group. By knowing the coordinates of a node location, nodes can execute our self-mapping algorithm of their present locations onto the current Group and calculate it's zid easily. Figure {\ref 1}.shows the general overview of the network architecture. \section[{c) Selecting Group Heads}]{c) Selecting Group Heads}\par A Group-Head selection occur under the pressure of the Following metrics:( D D D D )\par a. Node positions: A node with a position p that is close to the centre is more likely to act as a Group head. b. Optimum energy available: a node with higher energy e more probably acts as a Group head. c. Computational ability: the node with high computational ability c is more possible to act as a Group Head.\par d. Low mobility: the mobility m of a node is inversly proportional to its selection as a Group head.\par Each node of the Group broadcasts its Multicast Group Level Clogging Evaluation and Handling Algorithm abbreviated as MGLCEH is presented in this section. MGLCEH is an optimal algorithm that helps in locating the packet dropping under clogging. This evaluation occurs under Mac layer and then alerts network layer.\par At an event of inflow receiving by node i : Updating Inflow balancing ability:( ) 1 1 ' ' : ( )\textbf{2 2 : (( ) ( ))}\par ' :\par : This event occurs if Mac-layer alert indicates the clogging circumstance. Once the routing topology \hyperref[b3]{[4]} gets an alert from the Mac layer a propos the blocking at a node i , it alerts the fellow citizen node which is the source node s for conflict node i . Hence s evaluates it's Here ? can be calculated with following equation .True indicates the elimination or minimization of clogging at the Group due to the outflow regularization at Group p Z , if false then Group head of the p Z performs the action of alerting all other Group heads using a broadcasting \hyperref[b12]{[12]} instrument about the clogging at adjacent Group in downstream of the heridetary. Hence all Cells in the upstream side of the p Z apply BGLLBA and the Cells in downstream side of the p Z fill in their zdil . Then all Cells broadcast zdil to resource Group. Hence the source Group revaluates the dil .Basing on the dil , source node regularize its outflow load.if do t T IRS IRS cr T t t T t IRS IRS IRS cr T T T T endif if do t T IRS IRS cr T t IRS IRS cr T endif ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? < ? ? ? = + ? ? ? ? ? ? ? ? ? ? ? = + ? ? ? ? ? ? \section[{Notations used in Algorithm:}]{Notations used in Algorithm:}\par i: Node that had been effected by emptiness s: source node of the i. \hyperref[b12]{[12]} End-of-foreachS Z Measures dil as | | 1 | | Z zdil i i dil Z ? = =\par Hence source node S of Group ZS, which is source node of the routing path regularize it's outflow load to direction-finding path Hence source node S of t's outflow l oad to direction-finding path.\par Fig. 3 : Multicast Group Level Load Balancing Algorithm IV. \section[{SIMULATIONS AND RESULTS DISCUSSION}]{SIMULATIONS AND RESULTS DISCUSSION}\par In this section we discuss the outcome acquired from simulation conducted using a simulation model developed by using MXML in this section. We evaluated concert using madhoc with the following considerations: The process of capacity of clogging control and clogging detection cost is as follows:\par Based on the resource ease of use, bandwidth and energy, for individual operation a threshold value between 0 and 1 assigned. In the mechanism of clogging detection and control the total cost is calculated by summing the cost threshold of every involved event. In V. \section[{CONCLUSION}]{CONCLUSION}\par This manuscript discussed about proposed "Energy Efficient Cross layered blocking Detection and Control Routing Topology" in short referred as MGLCEH (Clogging Detection and have power over with Control seaplane Functionality). MGLCEH derived a cross layered clogging detection mechanism with energy effectiveness as primary criteria that included as clogging detection. \begin{figure}[htbp] \noindent\textbf{2}\includegraphics[]{image-2.png} \caption{\label{fig_0}2 .}\end{figure} \begin{figure}[htbp] \noindent\textbf{2}\includegraphics[]{image-3.png} \caption{\label{fig_1}Fig. 2 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{}\includegraphics[]{image-4.png} \caption{\label{fig_2}}\end{figure} \begin{figure}[htbp] \noindent\textbf{}\includegraphics[]{image-5.png} \caption{\label{fig_3}?Z}\end{figure} \begin{figure}[htbp] \noindent\textbf{1} \par \begin{longtable}{P{0.14671558350803632\textwidth}P{0.0029699510831586303\textwidth}P{0.000593990216631726\textwidth}P{0.001187980433263452\textwidth}P{0.07900069881201957\textwidth}P{0.4888539482879105\textwidth}P{0.12473794549266247\textwidth}P{0.005939902166317261\textwidth}} \tabcellsep \tabcellsep \tabcellsep \tabcellsep IRS\tabcellsep cr\tabcellsep Current inflow balancing ability ratio\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep n BT\tabcellsep Buffering time at node n\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep i zdil\tabcellsep Group level degree of inflow load, here i is a Group\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep id.\\ \multicolumn{5}{l}{This helps in minimization of source level outflow balancing cost and balances the power consumption.}\tabcellsep a) Network and Node activities under projected topology The network is to be crack into Cells\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep For each Group i where 1.. | | i Z =\tabcellsep ; (| | Z is\\ \multicolumn{5}{l}{Group A geographical area, which is the part of preferred mobile ad hoc network DPG Distance Power Gradient}\tabcellsep entirety number of Cells ) Select Group-head for each Group i\\ \multicolumn{5}{l}{EIL LFL}\tabcellsep Inflow inferred Loss Link Failure Loss\tabcellsep Find spread load threshold n ? for each Group i\\ \multicolumn{5}{l}{IRS}\tabcellsep Inflow balancing ability\tabcellsep By using\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep Group head of the\tabcellsep th i Group\\ \multicolumn{5}{l}{zh}\tabcellsep ' i\tabcellsep Reserved Group head of the\tabcellsep th i Group\\ \multicolumn{4}{l}{Z}\tabcellsep c\tabcellsep Current Group in the hierarchy\\ \multicolumn{4}{l}{Z}\tabcellsep p\tabcellsep Preceding Group to the current Group\tabcellsep c Z in\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep hierarchy\\ \multicolumn{4}{l}{Z}\tabcellsep f\tabcellsep Fallowing Group to the current Group\tabcellsep c Z in\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep hierachy\\ \multicolumn{4}{l}{Z}\tabcellsep i\tabcellsep th i Group in the routing path\\ \multicolumn{3}{l}{n}\tabcellsep \multicolumn{2}{l}{z}\tabcellsep Group of the node n\\ \multicolumn{2}{l}{?}\tabcellsep \tabcellsep \multicolumn{2}{l}{Z}\tabcellsep Group level Transmission Load Threshold\\ ?\tabcellsep \multicolumn{4}{l}{n}\tabcellsep Node level Transmission Load Threshold\\ ?\tabcellsep \multicolumn{4}{l}{T}\tabcellsep projected threshold that indicates interval among two transmissions at one hop level\\ ?\tabcellsep \multicolumn{4}{l}{t}\tabcellsep Interval observed between last two transmissions\\ ?\tabcellsep \multicolumn{4}{l}{et}\tabcellsep time spent since last transmission at one hop level\\ \multicolumn{5}{l}{IRS ?}\tabcellsep T\tabcellsep Average Inflow balancing ability threshold observed for predefined interval T ?\\ \multicolumn{2}{l}{?}\tabcellsep \multicolumn{2}{l}{'}\tabcellsep Average threshold of the receiving strength\\ \multicolumn{5}{l}{IRS ce}\tabcellsep Expected Inflow balancing ability threshold at current interval\\ \multicolumn{5}{l}{IRS r}\tabcellsep Inflow balancing ability ratio\end{longtable} \par {\small\itshape [Note: p IRS Present Inflow balancing ability e IRS Expected Inflow balancing ability RP Routing Path n dt Delay time at node n N Number of nodes in entire network i Zn Number of nodes in a Group i i zh k ndil n ? of each Group spread load threshold for entire network can be measured. b) Splitting the network into Groups]} \caption{\label{tab_0}Table 1 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{} \par \begin{longtable}{P{0.26340504757964417\textwidth}P{0.06189491104675217\textwidth}P{0.0003516756309474555\textwidth}P{0.0003516756309474555\textwidth}P{0.002110053785684733\textwidth}P{0.0003516756309474555\textwidth}P{0.0003516756309474555\textwidth}P{0.001406702523789822\textwidth}P{0.03305750930906082\textwidth}P{0.0003516756309474555\textwidth}P{0.004923458833264377\textwidth}P{0.0017583781547372776\textwidth}P{0.0003516756309474555\textwidth}P{0.0003516756309474555\textwidth}P{0.0003516756309474555\textwidth}P{0.0003516756309474555\textwidth}P{0.09952420355812991\textwidth}P{0.2788787753413322\textwidth}P{0.0703351261894911\textwidth}P{0.0158254033926355\textwidth}P{0.000703351261894911\textwidth}P{0.010550268928423666\textwidth}P{0.0003516756309474555\textwidth}P{0.0003516756309474555\textwidth}P{0.0017583781547372776\textwidth}} \multicolumn{3}{l}{For each node}\tabcellsep \tabcellsep \multicolumn{6}{l}{n Z ?}\tabcellsep p\tabcellsep begin\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep 1 \{ , ,..., \} 2 u u uk Z n n n\tabcellsep c\tabcellsep : All upstream nodes to s .\\ If\tabcellsep \multicolumn{3}{l}{n ndil zdil >}\tabcellsep \multicolumn{2}{l}{Z}\tabcellsep p\tabcellsep \multicolumn{3}{l}{and}\tabcellsep \multicolumn{2}{l}{n ndil zdil ?}\tabcellsep Z\tabcellsep p\tabcellsep ?\tabcellsep ?\tabcellsep Z\tabcellsep p\tabcellsep begin\tabcellsep 1 \{ , ,..., \} 2 d d dk Z n n n\tabcellsep c\tabcellsep : All downstream nodes to s .\\ \multicolumn{8}{l}{n BT BT bt n = +}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep 1 \{ , , ,..., \} 2 S u u uk Z Z Z Z : Set of upstream Cells to p Z\tabcellsep in\\ \multicolumn{17}{l}{Note: Value of barrier threshold bt should be decided such}\tabcellsep routing path, here S Z is a Group that contains source node of\\ \multicolumn{2}{l}{that Endif dil zdil n ?}\tabcellsep Z\tabcellsep \multicolumn{2}{l}{c}\tabcellsep \multicolumn{2}{l}{+}\tabcellsep ?\tabcellsep Z\tabcellsep c\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep the routing path 1 2 \{ , ,..., d d Z Z Z\tabcellsep dm\tabcellsep ,..., \} T Z : Set of downstream Cells to p Z\\ \multicolumn{17}{l}{Find End-of-for each n dil and send n dil to p Z zh measures p Z zdil if p Z zdil dil > and ( Z zdil Alert: Outflow regularization at p p Z zh p dil ? ) ? ? Z leads to overcome clogging begin}\tabcellsep in routing path, here T Z is a Group that contain target node of the routing path ? : Group level outflow threshold ? : Network level Outflow threshold Algorithm: Mac layer alerts about the blocking at node of Group c Z to routing topology, hence the following steps perform in\\ \multicolumn{12}{l}{situation at contention Group.}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep sequence\\ \multicolumn{17}{l}{Return; Alerts all Group heads in network regarding clogging contention Group. Endif p Z zh For each Group z in 1 2 \{ , , ,..., \} S u u uk Z Z Z Z begin}\tabcellsep 1 zn Zc ? k = complete following at node s zdil dil Z k ? c Z c ? = zn Z c If c s Z ndil zdil > and s ndil zdil ?\tabcellsep Z\tabcellsep c\tabcellsep ?\tabcellsep ?\tabcellsep Z\tabcellsep c\tabcellsep begin\\ \tabcellsep \multicolumn{16}{l}{For each node n z ? begin If n z ndil zdil > and begin n BT BT bt ndil zdil ? n z ? ? n = +}\tabcellsep z\tabcellsep s BT BT bt s = + Note: Value of buffer threshold bt should be certain such that dil zdil s Z Z c c ? ? + Return. Endif\tabcellsep D D D D ) (\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{9}{l}{Note: Value of barrier threshold bt should be understood such that dil zdil n z z ? ? + Endif}\tabcellsep s sends alert to c Z zh alerts all nodes that belongs to Group c c Z zh about conflict node i . Z 1 2 \{ , ,..., \} c u u uk Z n n n updates their ndil by apply BGLLBA\\ \multicolumn{17}{l}{Find End-of-foreach dil and send n n dil to z zh zh measures z z zdil and broadcast towards source Group. End-of-foreach For each Group z in 1 2 \{ , ,..., ,..., \} d d dm T Z Z Z Z begin For each node n belong to Group z begin determine n ndil and sends to z zh}\tabcellsep c measures their ndil and alerts Z zh Measures zdil as fallows recursively and alerts 1 2 \{ , ,..., \} c d d dk Z n n n c Z zh 1 zn Z c ndil k k zdil z zn c Z c ? = =\tabcellsep Z zh\tabcellsep c\\ \tabcellsep \multicolumn{11}{l}{End-of-foreach z zh measures 1 zn z ? ndil k zdil as z k zdil z zn z = =}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep If Alert: blocking at contention node handle at current Group c c Z zdil dil > and ( ) c Z zdil dil ? ? ? begin Z level. Return. Endif\end{longtable} \par {\small\itshape [Note: z zh z zh Sends z zdil to source Group via propagation]} \caption{\label{tab_2}}\end{figure} \begin{figure}[htbp] \noindent\textbf{2} \par \begin{longtable}{P{0.48166666666666663\textwidth}P{0.36833333333333335\textwidth}} \multicolumn{2}{l}{Performance Analysis}\\ No of Hops\tabcellsep 225\\ Approximate Hop distance\tabcellsep 300 meters\\ Approximate total network\tabcellsep 1000X1000 meters\\ fairly accurate Group Rdious\tabcellsep 100X100 meters\\ Physical channel bandwidth\tabcellsep 2mbps\\ Mac Layer:\tabcellsep 802.11 DCF with option of\\ \tabcellsep handshaking prier to data\\ \tabcellsep transferring\\ Physical layer illustration\tabcellsep 802:11B\\ presentation Index\tabcellsep Outflow regularization cost\\ \tabcellsep and end-to-end throughput\\ be very successful simulation\tabcellsep \\ time\tabcellsep \end{longtable} \par \caption{\label{tab_3}Table 2 :}\end{figure} \footnote{© 2012 Global Journals Inc. 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