Hybrid Zoning Algorithm to Optimize Overhead in Smart Mobile Communication
Abstract
:1. Introduction
2. Related Work
3. Problem Formulation
4. OLSR Protocol
4.1. The MPR Computation of OLSR
 Input: $N1\left(x\right)=N1$, $N2\left(x\right)=N2$, $M\left(x\right)=MPR$; $MPR=\{\varnothing \}$
 Start with an MPR set made of all members of $N1$ with willingness equal to WILL_ALWAYS;
 calculate $D\left(y\right)$, where $y\in N1$. $D\left(y\right)$ is defined as the number of nodes $u\in N1\left(y\right)\backslash \{N1,x\}$;
 $MPR\leftarrow m$ if $\exists m\in N1$, m is the only node that covers a node $v\in N2$;
 Remove from $N2$ all reached nodes by m;
 While there are nodes in $N2$ which are not covered by at least one node in $MPR$;
 (a)
 Calculate $R\left(w\right)$ for each $w\in N1$. R(w) is the number of nodes in $N2$ which are not yet covered by a node in $MPR$ and are reachable through w;
 (b)
 $MPR\leftarrow w$ if w has the highest willingness with $R\left(w\right)\ne 0$;
 (c)
 In case of multiple choice, $MPR\leftarrow u$, u has the maximum reachability.
 (d)
 In case of multiple nodes providing the same amount of reachability, $MPR\leftarrow y$, where $D\left(y\right)$ is greater; Remove $N2$, the nodes which are now covered by nodes in $MPR$.
4.2. Default Forwarding Rules of OLSR
5. Zone Geographic Forwarding Rules
5.1. Extension of the Message Header
5.2. First Strategy: Acting on Nodes: ZMPR Computation
 First, x changes the current plan to a new Cartesian coordinate of origin x, by deducing its coordinates $({X}_{x},{Y}_{x})$ from the position of all nodes in $N1\left(x\right)$. The new coordinates of x are $(0,0)$ and the coordinates of a node $u\in N1\left(x\right)$ are ${X}_{u}^{x}={X}_{u}{X}_{x}$ and ${Y}_{u}^{x}={Y}_{u}{Y}_{x}$.
 Then, x determines the zone of every neighbor $u\in N1\left(x\right)$ within the new Cartesian coordinate system. Four cases are possible:
 ${X}_{u}^{x}>0$ and ${Y}_{u}^{x}>0$
 –
 if $0<\frac{{X}_{u}^{x}}{{Y}_{u}^{x}}<1$, u belongs to ${Z}_{1}$
 –
 if $\frac{{X}_{u}^{x}}{{Y}_{u}^{x}}>1$, u belongs to ${Z}_{2}$
 –
 if $\frac{{X}_{u}^{x}}{{Y}_{u}^{x}}=1$, u is on the border of ${Z}_{1}$ and ${Z}_{2}$
 ${X}_{u}^{x}>0$ and ${Y}_{u}^{x}<0$
 –
 if $\frac{{X}_{u}^{x}}{{Y}_{u}^{x}}<1$, u belongs to ${Z}_{3}$
 –
 if $1<\frac{{X}_{u}^{x}}{{Y}_{u}^{x}}<0$, u belongs to ${Z}_{4}$
 –
 if $\frac{{X}_{u}^{x}}{{Y}_{u}^{x}}=1$, u is on the border of ${Z}_{3}$ and ${Z}_{4}$
 ${X}_{u}^{x}<0$ and ${Y}_{u}^{x}<0$
 –
 if $\frac{{X}_{u}^{x}}{{Y}_{u}^{x}}>1$, u belongs to ${Z}_{6}$
 –
 if $0<\frac{{X}_{u}^{x}}{{Y}_{u}^{x}}<1$, u belongs to ${Z}_{5}$
 –
 if $\frac{{X}_{u}^{x}}{{Y}_{u}^{x}}=1$, u is on the border of ${Z}_{5}$ and ${Z}_{6}$
 ${X}_{u}^{x}<0$ and ${Y}_{u}^{x}>0$
 –
 if $\frac{{X}_{u}^{x}}{{Y}_{u}^{x}}<1$, u belongs to ${Z}_{7}$
 –
 if $0>\frac{{X}_{u}^{x}}{{Y}_{u}^{x}}>1$, u belongs to ${Z}_{8}$
 –
 if $\frac{{X}_{u}^{x}}{{Y}_{u}^{x}}=1$, u is on the border of ${Z}_{7}$ and ${Z}_{8}$
 Finally, the node x elects dispersive MPRs by selecting a node in each zone prioritizing odd zones to keep them away from each other. The new MPR computation algorithm is detailed below and summarized in Figure 9:
 Input: $N1\left(x\right)=N1$, $N2\left(x\right)=N2$, $M\left(x\right)=MPR$; $MPR=\{\varnothing \}$; $Z=\left\{{z}_{i=1\to 8}\right\}$;
 Start with an MPR set made of all members of $N1$ with willingness equal to WILL_ALWAYS;
 calculate $D\left(y\right)$, where $y\in N1$. $D\left(y\right)$ is defined as the number of nodes $u\in N1\left(y\right)\backslash \{N1,x\}$;
 $MPR\leftarrow m$ if $\exists m\in N1$, m is the only node that covers a node $v\in N2$;
 Remove from $N2$ all reached nodes by m;
 remove from Z the covered zone where m is located;
 While there are nodes in $N2$ which are not covered by at least one node in $MPR$;
 (a)
 Calculate $R\left(w\right)$ for each $w\in N1$. R(w) is the number of nodes in $N2$ which are not yet covered by a node in $MPR$ and are reachable through w;
 (b)
 $MPR\leftarrow w$ if w has the highest willingness with $R\left(w\right)\ne 0$;
 (c)
 Remove from Z the new covered zone;
 (d)
 In case of multiple choice, $MPR\leftarrow u$, u has the maximum reachability. Remove from Z the new covered zones;
 (e)
 In case of multiple choice, $MPR\leftarrow u$, u is located in uncovered odd zone first, if not u is in an uncovered even zone with $R\left(u\right)\ne 0$. Remove from Z the new covered zone.
 (f)
 In case of multiple choice, $MPR\leftarrow y$, where $D\left(y\right)$ is greater; Remove from $N2$ the nodes which are now covered by nodes in $MPR$.
 (g)
 Remove from Z the new covered zone.
5.3. Second Strategy: Acting on Transmissions: Geographic Forwarding Rules
Algorithm 1 Geographic forwarding rules of modified OLSR. 

6. Results
7. Conclusions
Author Contributions
Funding
Conflicts of Interest
Abbreviations
OLSR  Optimized Link State Routing 
AODV  Ad hoc Ondemand Distance Vector 
RR  Route Request 
GPS  Global Positioning System 
GFR  Geographic Forwarding Rules 
MPR  Multipoint Relay 
ZMPR  Zone Multipoint Relay 
ZGFR  Zone Geographic Forwarding Rules 
MANET  Mobile Ad hoc Network 
QoS  Quality of Service 
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Simulation Environment  Parameters 

Area size  1000 m × 1000 m 
Number of nodes  80, 100, 120, 140, 160 
Radio range  R = 100 m 
Modulation  802.11b peer to peer mode 
DataMode  DsssRate1Mbps 
ControlMode  DsssRate1Mbps 
Mobility model  Random Mobility 
Simulation time  100 s 
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Souidi, M.; Habbani, A.; Berradi, H. Hybrid Zoning Algorithm to Optimize Overhead in Smart Mobile Communication. J. Sens. Actuator Netw. 2019, 8, 53. https://doi.org/10.3390/jsan8040053
Souidi M, Habbani A, Berradi H. Hybrid Zoning Algorithm to Optimize Overhead in Smart Mobile Communication. Journal of Sensor and Actuator Networks. 2019; 8(4):53. https://doi.org/10.3390/jsan8040053
Chicago/Turabian StyleSouidi, Mohammed, Ahmed Habbani, and Halim Berradi. 2019. "Hybrid Zoning Algorithm to Optimize Overhead in Smart Mobile Communication" Journal of Sensor and Actuator Networks 8, no. 4: 53. https://doi.org/10.3390/jsan8040053