NS-2 의 센서 네트워크 시뮬레이션 응용

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NS-2 의 센서 네트워크 시뮬레이션 응용

김 대 영 , 박 노 성

July 28, 2004

Real-time & Embedded Systems LaboratoryMobile Multimedia Research Center

[email protected]://resl.icu.ac.kr/~kimd

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Contents

Introduction to Sensor Networks

Power Aware Data-centric (PAD) Routing Protocol

Minimum Energy Path and Minimum Energy Property Graph MEPG and TMEPG algorithm Distributed Data-centric Bellman-Ford algorithm

Simulation of PAD on NS-2 Implementation of new routing protocol, PAD Wireless network and simulation environment setting Simulation analysis

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What is Sensor Network? Network of sensor nodes with computation & sensing & wireless

communication capabilities

What we can do with Sensor Networks? Sensing(Actuation) : Motion -> Image -> Classification Collaboration : estimate moving direction & speed of an event Mobile sensors : tracking

Internet /

Other network

Internet /

Other network

BaseStation Sensor field

Sensor node

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Sensor Network Applications

Military Digital (Smart) Home Healthcare Logistics, Supply Chain Management ITS Process Automation Environment Intelligent Robot Automotive (Vehicle) Factory Automation Etc.

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Research Topics in Sensor Networks – ICU ANTS (An evolvable Network of Tiny Sensors)

Operating Systems

Network Protocols

Middleware

Application Framework/Profile

Secu

rity

Pow

er E

fficie

ncy

Sensor Network Applications

(Digital Home, Military, U-SCM)

Hardware Platforms

Localiz

atio

n/S

yn

ch

ron

izatio

n

ANTS@ICU 2004

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Network layer

Functions: Routing (Ad-Hoc) internetworking with external network: other sensor

network, control system, Internet. Base nodes used as gateway to other network

Design principles: Power efficiency Data-centric Data aggregation Ideal sensor network has attribute-based addressing &

location awareness

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Network layer – Energy Efficient

Energy-efficient routes based on: Available power (PA) Energy required ( )

Energy-efficient routes approaches: Maximum PA route: route with maximum total PA is preferred. (Route 4

PA=5 ) Minimum energy (ME) route: route consumes minimum energy (Route 1

=3 ) Minimum hop route: with minimum hop (Route 3) Maximum minimum PA node route: route whichhas largest minimum PA (Route 3, minimum PA=3)

Route 1: Sink-A-B-T PA=4 =3 Route 2: Sink-A-B-C-T PA=6 =6

(Route 1 with extra node-> not power efficient) Route 3: Sink-D-T PA=3 =4 Route 4: Sink-E-F-T PA=5 =6

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Data Centric / Data Aggregation Data-centric routing

interest dissemination to assign sensor tasks to nodes – two approaches Base nodes broadcast interest Sensor nodes broadcast advertisement of available data and wait for request

from interested nodes Requires attribute-based naming

Users are more interested in querying attributes of phenomenon than individual node

“Areas where temperature is over 300C” Than “the temperature read by a certain node

Data aggregation (Data fusion) Technique used to solve implosion and overlap problem in data-centric

routing Base node asks sensor nodes to report their surrounding conditions Data from multiple sensor nodes are aggregated -> combining data

from many nodes into set of meaningful information Specifics data (e.g location of reporting nodes) should not be left out Node E aggregates data from sensor nodes A,B

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Sensors – Network ProtocolsHierarchical routing

Data-centricprotocols

Flooding/Gossiping

DirectedDiffusion

SPIN

SPIN-PP

SPIN-EC

SPIN-BC

SPIN-RI

Rumor routing

Gradient-basedrouting

LEACH TEEN

PEGASIS

HEED

CADRCOUGARACQUIRE

Hierarchical PEGASIS

APTEEN

Location-basedrouting

MECN GAF

SMECN

GEAR

PAD

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Directed Diffusion

Representative Data Centric protocol Sink broadcasts interest (task description) The interest has timestamp and gradient field As the interest is propagated, the gradients from the source back to

the sink are set up When the source detect the event meeting the interest, send data

back to the sink through the gradient Local data aggregation When the sink receives data, refresh and reinforce the interest

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LEACH (Low Energy Adaptive Clustering Hierarchy ) - MIT

Representative Data aggregation protocol

Assumption Base node can directly communicate with all nodes, that is single hop distance

Clustering hierarchy Setup phase

Each node choose a number between 0 and 1 If this random number is less than the threshold, the node becomes the head Heads advertise to all nodes Once the nodes receive the advertisement, they select their head based on

signal strength Steady state

A node send data to the head and head aggregate the data After certain period of time, back to setup phase

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Geographic and Energy Aware Routing (GEAR)

An energy efficient routing algorithm that propagates a query to the appropriate geographical region, without flooding

Procedure Forwarding the packets towards the target region:

When a closer neighbor to the destination exists: GEAR picks a next-hop that are closer to the destination

When all neighbors are further away: GEAR picks a next-hop node that minimizes some cost value of this neighbor.

Disseminating the packet within the region

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Power Aware Data-centric routing protocol

PAD@ANTS

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Basic Knowledge :Relay Region and Relay Node

The minimum signal strength is proportional to , (2≤ ≤5) power of distance.

If this inequality is true, the indirect transmission consumes less energy.

• Relay Region : the area where the inequality is always true

• Relay Node : the node located in the Relay Region such as r in the above figure

• k-Relay Node : k denote the number of intermediate nodes in the path, e.g. r is 1-Relay Node.

(t, r) + > (t, i) + (i, r) + 2 , where ( : receiving cost)

t → r t → i → r

= 2 = 4

The shape of boundary depends on .

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Basic Knowledge :Enclosure Region and Enclosure Graph

The nodes inside Relay Region is out of concern because it is not energy efficient.

• Enclosure Region : surrounded region by Relay Regions

• Minimum Energy Property Graph (MEPG) : the graph has all minimum energy paths (MEPs) but total number of edges are smaller than the original graph. (Cut the edges not related to MEPs in the original graph)

• Enclosure Graph : the graph whose edges are connected only to the nodes of Enclosure Region. Enclosure Graph contains MEPG.

Routing on MEPG is more efficient than on the original graph.

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Related Works :MECN, SMECN and etc.

The first maker of Minimum Energy Property Graph (MEPG) concept.

• Find Enclosure Graph and do routing.

• The node r is inside the Relay Region of h, so that r must be excluded from Enclosure Graph. However, MECN cannot do that because of it’s incorrect algorithm.

•In addition, MECN removes edges only to 1-Relay Node. For the optimality, edged to k-Relay Node, (k≥1) must be cut down. The complexity of MECN is O(n3).• SMECN removes k-Relay Node, but still complicated. Not such different, just a simple update.

• Li and Wan said that Enclosure Region is similar to the Voronoi region. They suggested the simple O(nlogn) algorithm using the Voronoi region. Their algorithm makes just the approximation of MEPG.

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Related Works :Drawbacks

Not optimal MECN removes only subset of 1-Relay Nodes. Result of Li and Wan’s algorithm is the approximation.

Too complicated O(n3) algorithm Computation for Enclosure Region

Not reasonable assumption Receiving cost is 0 and alpha is 2. (Li and Wan’s assumption)

Path-loss In noisy situation, the minimum signal strength is not just proportional to power of dis

tance. Only Minimum Energy Property Graph is possible.

Summary MECN : Not optimal, too complicated, and only path-loss SMECN : Optimal result, too complicated, and only path-loss Li and Wan : approximated result, not reasonable assumption, and only path-loss but si

mple algorithm

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Introduction to PAD

Minimum energy consumption Finding MEPs

Data-centric Minimum Energy Path Tree (MEPT)

Set of two schemes New MEPG algorithm

Reducing edges Afford to support other weight values such as delay and packet loss

Distributed Data-centric Bellman-Ford (DDBF) algorithm Finding MEPs Dynamic selecting of next node for equivalent remaining energy. Low transmission delay

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New MEPG algorithm

The MEPG algorithm of PAD adopts totally different approach from the existing works.

It is optimal and lightweight O(VlogV+E) algorithm. Real estimation except path-loss can be used and any assumptions are not needed.

Main idea Unit Minimum Energy Path (UMEP) : the direct edge consume

s less energy than any other paths. MEP consists of UMEPs.

A⇒D→E →F < A ⇒D →X →Y → E →F

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An example of MEPG algorithm

1. A collects the information of the local graph.Vertex = {A, B, C, D, E}

2. A runs the Dijkstra’s algorithm on the local graph.The MEPs from A to B, C, D, and E are found.Found MEPs : A→B, A→B→E, A→C, A→C→D

3. A extracts the MEPs whose length 1.Found UMEPs : A→B, A→C

B

CE

A

D

B

CE

A

D

B

CE

A

D

B

CE

A

D

Local Graph MEPs UMEPs

The edges from C to D, and from B to E has been removed.C and B are responsible for finding the removed edges.

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An example of MEPG algorithm

Original Graph BN is finding UMEPs.10 > 4 + 2

6 > 3 + 2

10 > 2 + 4 7 > 2 + 36 > 2 + 2

Done.1/3 edges are

removed.

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Distributed Data-centric Bellman-Ford algorithm

A kind of Distance Vector (DV) whose metric is power consumption (PC) and hop count (HC).

PC is the main metric, HC just records the hop count of the MEP.

The result is the routing tree for the data-centric.

Triggering based, Non-continuous broadcasting of the routing information

After the update period, the base node initiates new routing information.

Routing Table of node u

• It has two metric, PC for minimum energy routing and HC for low-delay routing.

• PC is the main metric, such that found HC doesn’t guarantee not the minimum hop path but the path shorter than or at least the same length as MEP.

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Other functionality

Prolongation of the lifetime Dynamic selection of the next node → ARM (Acyclic

Rerouting Method) Nodes’ battery is consumed as evenly as possibly.

Urgent delivery MEP is longer than minimum hop path.

Mobility Maintain the routing table without

Slow-convergence Loop of routing path

Self-healing Broken nodes are excluded from the routing.

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Simulation Environment

NS-2

MICA2 as a sensor node model 433MHz, sensitivity -109dBm, peak output 10dBm 5.3mA~26.7mA in tx mode, 7.4mA in rx mode More than 30pkts/s, pkt size 42bytes Omni-directional, 1dB gain, and 10cm over the ground so 10m tx rang

e Min-hop DV routing protocol

50x50 field, 1 base and 199 sensor nodes deployed randomly

CBR traffic whose period is randomly generated between 1 sec and 10 sec

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Simulation Result

Initial Graph

MEPG MEPG, where = 0

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Simulation Result

0 100 200 300 400 500 6000

10

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50

60

70

80

90

Time (sec)

Th

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be

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f n

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co

ns

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all

en

erg

y

Min-hop RoutingDDBF on initial graphPAD

0 100 200 300 400 500 6000

0.5

1

1.5

2

2.5x 104

Time (sec)

Th

e n

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be

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ac

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tsth

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as

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od

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av

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0 10 20 30 40 50 600

5

10

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20

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The number of broadcasted routing information

Th

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Simulation of PADon

NS-2

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NS-2 Simulator

Discrete event simulator Wired, wireless, and combined network of wired and wireless Comparison and analysis of protocols and traffics Traffic (CBR, FTP, TELNET, WEB…), Transport (TCP, UDP), Routing

(DV, LS, DSDV, AODV…), MAC (802.3, 802.11, SMAC…), QoS, Queuing, Link, Delay, Scheduler…

Status 200K lines of C++ and OTcl source code Most UNIX like systems and MS Windows family

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Sensor Network related part ofNS-2 Simulator

Mobile node Not only for sensor network Derived from Node class Not connected by Link Ability to move within a given topology Energy model

SMAC MAC protocol for sensor network Not stable Some bugs (abnormal working in the situation of dense and large number of

nodes, recent double precision bugs) Not finished work Not connected to energy model

Directed Diffusion Famous sensor network routing protocol in the early period.

Many other sensor network protocol had simulated on NS-2 but they are not contributed to NS-2 release.

We think that peoples interested in the simulation of sensor network in NS-2 may want to implement their own protocol.

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Combination of OTcl and C++

OTcl is the frontend and C++ is hidden to users. They have similar class hierarchy and closely related to each other.

<OTcl class> <C++ class>

– Simulation script

– Configure the node and topology

– Manipulating bytes and packets

– Complicated algorithm

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C++/OTcl Linkage

Root of ns-2 object hierarchy

bind(): link variable values between C++ and OTcl TclObject

command(): link OTcl methods to C++ implementations

TclClass Create and initialize TclObject’s

Tcl C++ methods to access Tcl interpreter

TclCommand Standalone global commands

EmbeddedTcl ns script initialization

<from IEC 2000 Workshop>

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Mobile Node Architecture

Node

ARP

Propagation and antenna models MobileNode

LL

MAC

PHY

LL

CHANNEL

LL

MAC

PHY

Classifier: Forwarding

Agent: Protocol EntityNode Entry

LL: Link layer object

IFQ: Interface queue

MAC: Mac object

PHY: Net interface

protocolAgent

(sink/source)

routingagent

addrclassifier

portclassifier

255

IFQIFQ

defaulttarget_

Radio propagation/antenna models

Prop/ant<from ISI ns tutorial 2002>

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Signal reception

Node 1

Node 2

Node 3

Node 4

2. R ≥ CSThresh3. R ≥ RXThresh4. R/P ≥ CPThresh (in collision)

Unless, two packets are discarded5. Delivered to MAC

1. Signal will be delivered to all nodes

2. R ≥ CSThresh3. R < RXThreshCan not regenerate the bit stream from the signal

2. R < CSThreshCan not be recognized

R: signal strength of received packetP: signal strength of previous packet

C

H

A

N

N

E

L

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Packet flow

Node

ARP

Propagation and antenna models MobileNode

LL

MAC

PHY

LL

CHANNEL

protocolAgent

(sink/source)

routingagent

addrclassifier

portclassifier

255

IFQ

defaulttarget_

ignore

Generated pkt

Received pkt

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Implementing new routing protocol

Routing protocol → Routing Agent which is the child of Agent class

Responsibility Maintaining the routing table Dealing with the routing information delivered to port 255 Marking the next node in pkt from the source and send to LL Forwarding the received pkt

TTL over → drop Loop occurred → drop Re-marking the next node and send to LL

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Directory structure

Ns-2.27├ mac│ └ wireless-phy.cc├ pad│ ├ rtable.cc/h │ └ pad.cc/h├ tools│ └ loss-monitor.cc/h └ tcl └ lib └ ns-lib.tcl

For per packet style tx power control

For PAD routing agent

Couting received pkts, average hop count, etc

For OTcl part of PAD routing agent

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PAD Implementation : C++/OTcl Linkage

static class PADClass : public TclClass {public: PADClass() : TclClass("Agent/PAD") {} TclObject *create(int argc, const char *const *argv) { return (new PAD_Agent()); }} class_pad;

PAD_Agent::PAD_Agent(){ helper_ = new PAD_Helper (this); bind_time("initrig_", &initrig_t); bind_time("update_period_", &update_period_); : bind("report_unit_", &report_unit_); bind("betta_", &betta_); bind("gamma_", &gamma_); bind("limit_", &limit_);}

A kind of declaration of the OTcl calss that C++ class mirrors

Return new C++ class whenever OTcl class created.

OTcl can access C++ variables.








<pad/pad.cc>

<pad/pad.cc>

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PAD Implementation : C++/OTcl Linkage

Tcl& tcl = Tcl::instance();if (thisnode->energy_model()->energy() == 0.0 && mylevel_ != 0) { level_[1]--; level_[0]++; mylevel_ = 0; printf("dead %d %d\n", (int) Scheduler::instance().clock(), myaddr_);}if (myaddr_ == 0) { printf("%d %d ", (int) Scheduler::instance().clock(), level_[0]); tcl.eval("$sink log");}Scheduler::instance().schedule(helper_, energy_, 1);

int PAD_Agent::command(int argc, const char *const *argv) { if (argc == 2) { if (!strcmp(argv[1], "start-pad")) { startUp(); return TCL_OK; } } else if (argc == 3) { if (!strcmp(argv[1], "addr")) { myaddr_ = Address::instance().str2addr(argv[2]); return TCL_OK; } : } return Agent::command (argc, argv);}








Create the instance of Tcl interpreter

Command the Tcl interpreter

Compare the command from Tcl

If nothing matched, it may be for the Agent class.

<pad/pad.cc>

<pad/pad.cc>

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PAD Implementation : recv()

void PAD_Agent::recv(Packet *p, Handler *h) { hdr_ip *iph = HDR_IP(p); hdr_cmn *cmh = HDR_CMN(p); int src = Address::instance().get_nodeaddr(iph->saddr()); int dst = cmh->next_hop(); Node* srcnode = Node::get_node_by_address(myaddr_); double r, e, f = srcnode->energy_model()->initialenergy(); int l, i;

if (src == myaddr_ && cmh->num_forwards() == 0) { if (adj_table_.next_index() == -1) { drop(p, DROP_RTR_TTL); return; } cmh->size() += IP_HDR_LEN; iph->ttl_ = IP_DEF_TTL; } else if (src == myaddr_) { drop(p, DROP_RTR_ROUTE_LOOP); return; } else { if (--iph->ttl_ == 0) { drop(p, DROP_RTR_TTL); return; } }

if (src != myaddr_ && iph->dport() == ROUTER_PORT) { //trg_rcv_++; processUpdate(p); } else { if (src == myaddr_ && cmh->num_forwards() == 0) gen_pkt_++; else if (src != myaddr_ && cmh->num_forwards() > 0) rcv_pkt_++; else flt_pkt_++; forward(p); }

Recv() Entry point of the agent Pkt is delivered to recv() of each ag

ent. Sending up and down to another lay

er is just the call of recv() whose parameter is the pointer of pkt.

Generated at upper layer

Loop occurred

TTL over

Routing information

Dealing with routing information

Forward the pkt

<pad/pad.cc>

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PAD Implementation : processUpdate()

void PAD_Agent::processUpdate(Packet *p) {hdr_ip *iph = HDR_IP(p); int src = Address::instance().get_nodeaddr(iph->saddr());Node* srcnode = Node::get_node_by_address(myaddr_); double myenergy = srcnode->energy_model()->energy();unsigned char *d = p->accessdata(); unsigned char *walk = d + 1; unsigned char type = *d; int i, j, found = 0;

if (type == PAD_LOCATION) { double x, y, z, dist; unsigned char tmp; for (i = 0; i < sizeof(double); i++) { memcpy((unsigned char *) ((int)&x + i), walk++, 1); } for (i = 0; i < sizeof(double); i++) { memcpy((unsigned char *) ((int)&y + i), walk++, 1); } for (i = 0; i < sizeof(double); i++) { memcpy((unsigned char *) ((int)&z + i), walk++, 1); } dist = sqrt((x_-x)*(x_-x) + (y_-y)*(y_-y)); // printf("%d receives location info from %d, %g, %g, %g (%g) ", myaddr_, src, x, y, z, dist); adj_table_.add_adj_loc(src, x, y, z, dist, prev_report_);} else if (myaddr_ != 0 && type == PAD_TRIGGER) { int nei_n; double p_consume; int hop, era, tmp; walk = is_neighbor(walk, &found); if (!found) { Packet::free(p); return; } trg_rcv_++; for (i = 0; i < sizeof(double); i++) memcpy((unsigned char *) ((int)&p_consume + i), walk++, 1); for (i = 0; i < sizeof(int); i++) memcpy((unsigned char *) ((int)&hop + i), walk++, 1); for (i = 0; i < sizeof(int); i++) memcpy((unsigned char *) ((int)&era + i), walk++, 1); if (era_ != era) { adj_table_.new_era(); era_ = era; } tmp = adj_table_.tbl_index(src); if (adj_table_.update_nei(tmp, p_consume, hop, era, lowpow_)) { if (myenergy > (srcnode->energy_model()->initialenergy()*0.20)) { adj_table_.get_next_metric(&p_consume, &hop); trg_snd_++; initTrigger(p_consume, hop, era, trig_jitter_); } }

:

Location information from adjacent nodes

Extracting location information from the pkt

Routing information receivedIs it neighbor? (Is it connected on MEPG?)

Extracting metrics from the received pkt

If received pkt is better than previous one, broadcast it.

<pad/pad.cc>

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PAD Implementation : MEPG algorithm

void AdjTable::calc_nei_table(int use, int limit) { double PQ[TBL_SIZE], dist[TBL_SIZE]; int PL[TBL_SIZE], p[TBL_SIZE], l[TBL_SIZE]; int v, i, j, u; double c;

// Dijkstra's Algorithm PQ[0] = dist[0] = 0; PL[0] = 0; p[0] = 0; l[0] = 0; for (v = 1; v <= adj_num_; v++) { PQ[v] = dist[v] = POW_INFINITY; PL[v] = v; p[v] = -1; l[v] = HOP_INFINITY; } i = adj_num_; while (i >= 0) { for (j = 0; j < i; j++) { if (PQ[j] < PQ[i]) { swap(&PQ[j], &PQ[i]); swap(&PL[j], &PL[i]); } } u = PL[i]; for (v = 0; v <= adj_num_; v++) { if (adj_table_[u][v] == POW_INFINITY) continue; c = dist[u] + adj_table_[u][v]; if (c < dist[v] && l[u]+1 <= limit) { dist[v] = c; p[v] = u; l[v] = l[u] + 1; } } for (v = 0; v <= adj_num_; v++) { for (j = 0; j <= adj_num_; j++) { if (v == PL[j]) PQ[j] = dist[v]; } } i--; }

// Choosing UMEPs for (i = 1; i <= adj_num_; i++) {// printf("%d->%d->c %g\n", i, p[i], dist[i]); // printf("%d->%d->c %g\n", i, p[0][i], adj_table_[0][i]); if (use == 1) { if (p[i] == 0) {// printf("find UMEP %d\n", i); add_nei_ent(i-1); } } else add_nei_ent(i-1); }}

, ( [ ] )

' , ( [ ] ')

'' ' , ( [ '] '')

c u v p v u

c u u v p u u

c u u u v p u u

<pad/rtable.cc>

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PAD Implementation : forward()

void PAD_Agent::forward(Packet *p) { hdr_ip *iph = HDR_IP(p); hdr_cmn *hdrc = HDR_CMN(p); unsigned char *walk; double p_tmp = adj_table_.get_p(adj_table_.next_index()); double p_con_tmp = adj_table_.get_pconsume(adj_table_.next_index()); int i; walk = p->accessdata();

if (walk == NULL) { p->allocdata(sizeof(double)*2 + 1); hdrc->size_ += sizeof(double)*5 + 1 + IP_HDR_LEN; walk = p->accessdata(); } if (txctrl_t > 0.0) *(walk++) = PAD_DATA; else *(walk++) = PAD_NO_CONTROL; for (i = 0; i < sizeof(double); i++) memcpy(walk++, (unsigned char *) ((int)&p_tmp + i), 1); for (i = 0; i < sizeof(double); i++) memcpy(walk++, (unsigned char *) ((int)&p_con_tmp + i), 1); hdrc->direction() = hdr_cmn::DOWN; hdrc->addr_type_ = NS_AF_INET; hdrc->xmit_failure_ = mac_callback; hdrc->xmit_failure_data_ = this; hdrc->next_hop_ = adj_table_.next_node_n(); assert(!HDR_CMN(p)->xmit_failure || HDR_CMN(p)->xmit_failure_ == mac_callback); snd_pkt_++; target_->recv(p, (Handler *)0);}

Per pkt power control

Send down to the link layer

The function called when tx failed

Remarking the next node

<pad/pad.cc>

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PAD Implementation : OTcl code

Simulator instproc create-wireless-node args { $self instvar routingAgent_ wiredRouting_ propInstance_ llType_ \

macType_ ifqType_ ifqlen_ phyType_ chan antType_ energyModel_ \initialEnergy_ txPower_ rxPower_ idlePower_ \topoInstance_ level1_ level2_ inerrProc_ outerrProc_ FECProc_

Simulator set IMEPFlag_ OFF

# create node instance set node [eval $self create-node-instance $args] # basestation address setting if { [info exist wiredRouting_] && $wiredRouting_ == "ON" } { $node base-station [AddrParams addr2id [$node node-addr]] } switch -exact $routingAgent_ { PAD { set ragent [$self create-pad-agent $node] } DSDV { set ragent [$self create-dsdv-agent $node] }

Simulator instproc create-pad-agent { node } { # Create a pad routing agent for this node set ragent [new Agent/PAD] # Setup address (supports hier-addr) for pad agent # and mobilenode set addr [$node node-addr] $ragent addr $addr $ragent node $node if [Simulator set mobile_ip_] { $ragent port-dmux [$node demux] } $node addr $addr $node set ragent_ $ragent $self at 0.0 "$ragent start-pad"

return $ragent}

Create the Mobile Node

Create the routing agent

<tcl/lib/Ns-lib.tcl>

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PAD Simulation Script #1

# ======================================================================# Define options# ======================================================================set val(chan) Channel/WirelessChannel ;# channel typeset val(prop) Propagation/TwoRayGround ;# radio-propagation modelset val(netif) Phy/WirelessPhy ;# network interface typeset val(mac) Mac/802_11 ;# MAC typeset val(ifq) Queue/DropTail/PriQueue ;# interface queue typeset val(ll) LL ;# link layer typeset val(ant) Antenna/OmniAntenna ;# antenna modelset val(energymodel) EnergyModel ;#set val(initialenergy) 2.0 ;#set val(baseenergy) 600 ;#set val(p_rx) 22.2e-3 ;#set val(p_tx) 80.1e-3 ;#set val(x) 50 ;# X dimension of the topography set val(y) 50 ;# Y dimension of the topographyset val(ifqlen) 50 ;# max packet in ifqset val(nn) 200 ;# number of mobilenodesset val(rp) PAD ;# routing protocolset val(stop) 600.0 ;# simulation timeset val(cbr_stop) 597.0 ;# simulation time

Antenna/OmniAntenna set Z_ 0.1

#Phy/WirelessPhy set CPThresh_ 10#Phy/WirelessPhy set CSThresh_ 1e-10 ;#1.559e-11Phy/WirelessPhy set RXThresh_ 1e-10Phy/WirelessPhy set Rb_ 1.38e3Phy/WirelessPhy set Pt_ 10.0e-3Phy/WirelessPhy set freq_ 433.0e+6

Height of antenna : 10cm → tx range 10m, 1.5m → tx range 150m

Berkeley’s MICA2 spec

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Agent/PAD set node_num_ $val(nn)Agent/PAD set calcnei_ 5.5Agent/PAD set initrig_ 6.0Agent/PAD set update_period_ 100.0Agent/PAD set txctrl_ 19.9Agent/PAD set report_599.9Agent/PAD set use_mepg_ 1Agent/PAD set use_energy_ 1Agent/PAD set loc_jitter_ 5.0Agent/PAD set trig_jitter_ 2.5Agent/PAD set energy_jitter_ 0.01Agent/PAD set lowpow_ 1

Agent/PAD set limit_ 100Agent/PAD set betta_ 1.0Agent/PAD set gamma_ 1.0Agent/PAD set report_unit_ 0.15

# ======================================================================# Main Program# ======================================================================if {$argc < 1} {

puts "Uage: ns pad.tcl \[replication number\]"exit

}set run 0if {$argc == 1} {

set run [lindex $argv 0]}

# Initialize Global Variablesset ns [new Simulator]set tracefd [open pad.tr w]set namtrace [open pad.nam w]

The number of nodesRun MEPG algorithm atRun DDBF algorithm at

Routing table update period, base node resend trigger message in this periodTeach the physical layer maximum tx power

Print simulation result at

1:Do routing on MEPG, 0:on the original graph1:Use tx power control 0:always emit in maximum strength

Jitter for the initial location information broadcastingJitter for routing information broadcastingJitter for remaining battery capacity broadcasting

1:minimum energy routing, 0:minimum hop routing

limit value for TMEPG algorithm

Coefficients for ARM

Choose stream of RNG for the simulation of different environment

46


# configure base node$ns node-config -adhocRouting $val(rp) \ -llType $val(ll) \ -macType $val(mac) \ -ifqType $val(ifq) \ -ifqLen $val(ifqlen) \ -antType $val(ant) \ -propType $val(prop) \ -phyType $val(netif) \ -rxPower $val(p_rx) \ -txPower $val(p_tx) \ -energyModel $val(energymodel) \ -initialEnergy $val(baseenergy) \ -channelType $val(chan) \ -topoInstance $topo \ -agentTrace ON \ -routerTrace ON \ -macTrace OFF \ -movementTrace OFF

set node_(0) [$ns node] $node_(0) random-motion 0 ;# disable random mo

tion

# configure sensor node$ns node-config -adhocRouting $val(rp) \

-llType $val(ll) \-macType $val(mac) \-ifqType $val(ifq) \-ifqLen $val(ifqlen) \-antType $val(ant) \-propType $val(prop) \-phyType $val(netif) \-rxPower $val(p_rx) \-txPower $val(p_tx) \-energyModel $val(energymodel) \-initialEnergy $val(initialenergy) \-channelType $val(chan) \-topoInstance $topo \-agentTrace ON \-routerTrace ON \-macTrace OFF \-movementTrace OFF

for {set i 1} {$i < $val(nn) } {incr i} {

set node_($i) [$ns node]$node_($i) random-motion 0 ;# disable ran

dom motion}

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set rng_ux [new RNG]for {set j 0} {$j < $run} {incr j} {

$rng_ux next-substream}

set rng_uy [new RNG]for {set j 0} {$j < $run} {incr j} {

$rng_uy next-substream} :set ux [new RandomVariable/Uniform]$ux use-rng $rng_ux$ux set min_ 0$ux set max_ $val(x) :set us [new RandomVariable/Uniform]$us use-rng $rng_us$us set min_ 20$us set max_ 30 ;#$val(stop)/2

set ui [new RandomVariable/Uniform]$ui use-rng $rng_ui$ui set min_ 1$ui set max_ 10

# Provide initial (X,Y, for now Z=0) co-ordinates for mobilenodesfor {set i 0} {$i < $val(nn)} {incr i} {

$node_($i) set X_ [$ux value]$node_($i) set Y_ [$uy value]$node_($i) set Z_ 0.0

}

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# Setup traffic flow between nodesset sink [new Agent/LossMonitor]$ns attach-agent $node_(0) $sink$ns at 599.91 "$sink log“

for {set i 1} {$i < $val(nn)} {incr i} {set udp_($i) [new Agent/UDP]$ns attach-agent $node_($i) $udp_($i)$ns connect $udp_($i) $sinkset cbr_($i) [new Application/Traffic/CBR]$cbr_($i) set packetSize_ 42$cbr_($i) set interval_ [$ui value]$cbr_($i) attach-agent $udp_($i)$ns at [$us value] "$cbr_($i) start"$ns at $val(cbr_stop) "$cbr_($i) stop"

}

entry_point_ Routing Agent

Loss Monitor UDP

CBRCount the number of received pkt

Generate pkt according to RNG

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Extracting data from the result

Post-processing of trace file Some protocol doesn’t fully generate the trace

information.

Insert the code in the Agent Print the result at the end of simulation Port-processing with AWK, SED.

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AWK and SED

num_nodes is set 2001 0 0 nan2 0 0 nan

:19 0 0 nan20 0 0 nan21 0 18 4.3888922 0 40 5.123 0 68 5.4558824 0 97 5.443325 0 127 5.393726 0 163 5.39877

:596 61 18845 6.13462dead 596 97597 62 18846 6.13435598 62 18846 6.13435599 62 18846 6.134350 15 12 131 0.0180012 0 0 597.477 0 0 0 0 0 0 1000000000 -1 -11 23 22 77 0.0168975 2 0.0557542 0 234 12 53 1425 1473 5 5 5 62 17 16 46 0.0215665 46 0.0215665 0.230704 175 12 77 2183 2249 11 13 13

153 12 12 132 0.0297361 132 0.0297361 1.75927 421 34 122 0 122 0 13 13 144 18 16 107 0.0627739 107 0.0627739 1.28186 469 16 159 0 158 1 9 9 125 21 18 169 0.0214703 198 0.0163407 0.266743 340 27 102 906 1008 0 6 6 86 28 21 16 0.0222356 16 0.0222356 0 125 7 34 571 605 0 3 3 47 17 16 38 0.0611482 38 0.0611482 0 94 13 58 4 59 3 15 15 15

:

<Result file>

#!/usr/bin/awk -fBEGIN { time[600]; dead[600]; rcv[600]; hop[600];}

{ time[$1] += 1; dead[$1] += $2; rcv[$1] += $3; hop[$1] += $4;}

END { for (i = 21; i < 600; i++) printf i" "time[i]" "dead[i]/time[i]" "…"\n";}

#!/usr/bin/sed -f/^dead/d/^num_nodes/ds/nan/0//[^\.]*\.[^\.]*\.[^\.]*$/d/^[0-9]\{1,\} [0-9]\{1,\}\.[0-9]\{1,\}$/d/^[0-9]\{1,\} 0 0 0$/d/^graph/d/^}/d/.pos./d/.--./d

0 100 200 300 400 500 6000

10

20

30

40

50

60

70

80

90

Time (sec)

Th

e n

um

be

r o

f n

od

es

co

ns

um

ing

all

en

erg

yMin-hop RoutingPADPAD on MEPG

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Copy the patch file into your ns-2.27 directorycp s6.tar ~/ns-allinone-2.27/ns-2.27

Untartar xvf s6.tar

Modify Makefile

Exercise

dsdv/dsdv.o dsdv/rtable.o queue/rtqueue.o \Line 239: pad/pad.o pad/rtable.o\

routing/rttable.o \

tags: force ctags -wtd *.cc *.h webcache/*.cc webcache/*.h dsdv/*.cc dsdv/*.h \

Line 498: pad/*.cc pad/*.h \ dsr/*.cc dsr/*.h webcache/*.cc webcache/*.h lib/*.cc lib/*.h \ ../Tcl/*.cc ../Tcl/*.h

TAGS: force etags *.cc *.h webcache/*.cc webcache/*.h dsdv/*.cc dsdv/*.h \

Line 504: pad/*.cc pad/*.h \ dsr/*.cc dsr/*.h webcache/*.cc webcache/*.h lib/*.cc lib/*.h \ ../Tcl/*.cc ../Tcl/*.h

52

Clean unpatched ns binary and remakemake clean; make

Run the simulation under sim directorycd simvi pad.tcl line 21: set val(stop) 100 line 38: Agent/PAD set report_ 99.9

chmod +x *run 1 5 pad ( ns pad.tcl 1 > pad.log )

Post-processing of the resultextdead pad.log | ./calcdeadmkres pad 5

Exercise

53

References

“NS Manual,” http://www.isi.edu/nsnam/ns/ns-documentation.html

“NS worksop and presentation,” http://www.isi.edu/nsnam/ns/ns-tutorial/index.html

박노성 , 김대영 , 이상수 , 도윤미 , 김지태 , " 센서 네트워크를 위한 저전력 라우팅과 네트워크 수명 연장 기법 ," 제 14 회 통신정보합동학술대회 (The 14th JOINT CONFERENCE ON COMMUNICATIONS & INFORMATION), Apr 2004

54

An example ofCycle and Straying Data

Node u wants to send data but node r doesn’t have enough energy to afford it.

Node u selects node s for its temporary next node. If ARM is applied, u cannot select s, because Hop Count is same.

Node t doesn’t have enough energy, either. Node s chooses node v for its temporary next node.

Node s is the next node of v. Data is sent to node s again.

Cycle occurs at node s, and the data will roams the node u, s, and v to find the node having enough energy.

Documents

NS-2 의 센서 네트워크 시뮬레이션 응용