Which Wireless Technology for Industrial Wireless Sensor Networks? The Development of OCARI...

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 56, NO. 10, OCTOBER 2009 1

Which Wireless Technology forIndustrial Wireless Sensor Networks?

The Development ofOCARI Technology

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Khaldoun Al Agha, Senior Member, IEEE, Marc-Henry Bertin, Tuan Dang, Member, IEEE,Alexandre Guitton, Member, IEEE, Pascale Minet, Thierry Val, and Jean-Baptiste Viollet

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Abstract—In this paper, we present an industrial development7of a wireless sensor network technology called OCARI: Optimiza-8tion of Communication for Ad hoc Reliable Industrial networks.9It targets applications in harsh environments such as power plants10and warships. OCARI is a wireless-communication technology11that supports mesh topology and power-aware ad hoc routing12protocol aimed at maximizing the network lifetime. It is based13on IEEE 802.15.4 physical layer with deterministic Media AccessAQ1 14Control layer for time-constrained communication. During theAQ2 15nontime-constrained communication period, its ad hoc routing16strategy uses an energy-aware optimized-link state-routing proac-17tive protocol. An OCARI application layer (APL) is based on Zig-AQ3 18Bee application support sublayer and APL primitives and profiles19to provide maximum compatibility with ZigBee applications. To20fully assess this technology, extensive tests are done in industrial21facilities at Electricité De France R&D as well as at Direction22des Constructions Navales Services. Our objective is then to pro-23mote this specification as an open standard of industrial wireless24technology.25

Index Terms—Ad hoc network, bit-error rate (BER), deter-26ministic Media Access Control (MAC), IEEE 802.15.4, interfer-27ence model, ISA100.11a, power-aware routing strategies, power28plants, signal-to-interference-plus-noise ratio (SINR), warships,29wirelessHART, wireless sensors network (WSN), WSN middle-30ware, ZigBee.31

Manuscript received July 20, 2008; revised June 30, 2009. This work wassupported in part by the French National Research Agency (Agence Nationalede la Recherche) under Grant ANR-06-TCOM-025.

K. Al Agha is with LRI, Bat 490, Université Paris-Sud11, 91405 Orsay,France (e-mail: [email protected]).AQ4

M.-H. Bertin is with Telit Communications S.p.A.—EMEA, Trieste, Italy(e-mail: [email protected]).AQ5

T. Dang is with Electricité De France (EDF) Research and Development,78401 Chatou, France (e-mail: [email protected]).AQ6

A. Guitton is with Clermont University/LIMOS CNRS, Complexe Scien-tifique des Cézeaux, 63173 Aubière, France (e-mail: [email protected]).AQ7

P. Minet is with French National Institute for Research in Computer Sci-ence and Control (INRIA) Rocquencourt, 78153 Le Chesnay, France (e-mail:[email protected]).AQ8

T. Val is with the Laboratory of Technology and System Engineeringof Toulouse (LATTIS), IUT de Blagnac, 31703 Blagnac, France (e-mail:[email protected]).AQ9

J.-B. Viollet is with Direction des Constructions Navales Services(DCNS), Département Ingénierie, 56311 Lorient, France (e-mail:[email protected]).

Color versions of one or more of the figures in this paper are available onlineat http://ieeexplore.ieee.org.

Digital Object Identifier 10.1109/TIE.2009.2027253

I. INTRODUCTION 32

W IRELESS communication represents a major industrial 33

stake in the coming years. It offers numerous usages 34

and helps industry save operating costs as well as improving 35

operational efficiency. In the recent years, WiFi (IEEE 802.11- 36

WLANs) and Bluetooth technologies (IEEE 802.15-WPANs) 37

have known tremendous development and have penetrated 38

small office and home office as well as large enterprise office. 39

These general-public wireless technologies may find their lim- 40

ited usage in industrial installations because of harsh environ- 41

ments, electromagnetic compatibility and interference issues, 42

safety and information technology (IT) security constraints, and 43

battery autonomy. Some of these issues have been addressed 44

by addenda to existing standards. For example, IEEE 802.11i 45

addresses the IT security, and IEEE 802.11e deals with WiFi 46

multimedia (WMM) quality of service (QoS) and WMM Power 47

Save. However, these specifications target consumer market 48

and do not take into account industrial needs in constrained 49

environment. 50

Applications of wireless sensors network (WSN) technology 51

in industrial environments such as power plants and warships 52

typically require the following characteristics. 53

At the physical (PHY) and Media Access Control (MAC) 54

layers: 55

1) Robust radio transmission (low bit error rate (BER) 56

[1]) regarding radio interferences (measured as signal-to- 57

interference-plus-noise ratio (SINR) [2], [3]); 58

2) Low power consumption along with power-management 59

capability to maximize battery autonomy; 60

3) Compatibility with electromagnetic constraints (e.g., low 61

equivalent isotropically radiated power ≤ 10 mW); 62

4) Deterministic MACs. 63

At the network layer: 64

1) Network topology flexibility: star, tree, mesh topologies; 65

2) Network scalability: ability to deal with large network 66

topology and high density of network nodes; 67

3) Transparency for application layer (APL): self- 68

organizing and autoconfigurable network parameter (net- 69

work address, network path, router node selection, . . .); 70

4) Support of energy-aware routing protocol; 71

5) Support of mobility; 72

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2 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 56, NO. 10, OCTOBER 2009

6) Support of authentication of network node and anti-73

intrusion (to the network) mechanisms.74

At the APL:75

1) Support of application profiles (e.g.: sensors, actuators,76

time-constrained);77

2) Support of different application communication modes:78

request/reply, publish/subscribe (event-based notifica-79

tion), and periodic/programmable notification;80

3) Support of IEC61804/electronic device description lan-81

guage (EDDL) for diagnosis and maintenance purposes;82

4) Support of authentication mechanisms.83

In response to these industrial needs and challenges, there are84

some working groups such as the wireless industrial networking85

alliance (WINA), the ZigBee Alliance, WirelessHART [4] from86

HART communication foundation (HCF), and ISA100 that87

have tried to define and establish industrial wireless-technology88

standards for different application domains. Currently, only89

ZigBee has commercially available products as this Alliance90

was formed very soon in the end of 2004. These specifica-91

tions are all based on IEEE 802.15.4, which provides a good92

foundation for building ad hoc mesh network. However, IEEE93

802.15.4 does not specify a standard way or algorithm to fully94

optimize power consumption in the MAC layer along with95

a corresponding routing schema. It is up to the application96

designer to elaborate its own strategy. Deterministic MAC layer97

[5] is also absent from this standard.98

In this paper, we describe the Optimization of Communica-99

tion for Ad hoc Reliable Industrial networks (OCARI) project100

in which we try to develop a wireless sensor communication101

module running an industrial ad hoc mesh networking protocol.102

It is based on IEEE 802.15.4 PHY layer and satisfies the103

following criteria in harsh environment:104

1) Deterministic MAC layer for time-constrained communi-105

cation;106

2) Optimized energy-consumption routing strategy for max-107

imum network lifetime within the nontime-constrained108

communication period;109

3) Support of human walking-speed mobility for some par-110

ticular network nodes (sinks).111

The project is funded by the French National Research112

Agency (Agence Nationale de la Recherche). It started at the113

end of 2006 and gathers partners (see [6] for more details)114

from industries (EDF/project leader, DCNS, and Telit), as115

well as university laboratories and research institutes (LIMOS,116

LATTIS, LRI, and INRIA). EDF and DCNS provide require-117

ments and use cases in power industry and warship applications.118

Telit, a high-technology company in wireless communication,119

industrializes the prototype. LIMOS and LATTIS university120

laboratories develop and implement OCARI medium-access121

methods. INRIA and LRI research institutes work on optimized122

energy-consumption routing strategy based on optimized-link123

state-routing (OLSR) proactive protocol [7], [8].124

This paper is organized as follows. Section II presents a125

review of existing wireless-communication standards which126

may be used in industrial environments. Section III shows127

the technical aspects of OCARI and details the technological128

choices. Finally, future works are detailed in Section IV.129

II. REVIEW OF EXISTING INDUSTRIAL 130

WIRELESS-COMMUNICATION 131

STANDARDS 132

Wireless mesh networking has emerged in the recent years 133

as a promising design paradigm for next-generation wireless- 134

communication networks with interesting characteristics such 135

as self-organizing and autoconfigurable topology, and ad hoc 136

routing concept. These properties promise substantial benefits 137

in terms of operating and maintenance costs of the communica- 138

tion infrastructure in industrial installations. They also ease the 139

development of “killer applications” such as condition monitor- 140

ing or condition-based maintenance (CBM) that requires flex- 141

ible and cost-effective sensor networks. Wireless technologies 142

help engineers achieve these objectives. However, most of the 143

existing general-public wireless-communication technologies 144

do not take into account the industrial requirements. There 145

exists proprietary radio-communication technologies for indus- 146

trial use (e.g., Wavenis), but the benefits of interoperability (and 147

thus, cost) are lost from multivendors solutions. Developing and 148

promoting industrial wireless-communication standards help 149

industrial end users preserve the expected benefits of wireless 150

technologies. We propose to review the state of the art of current 151

industrial wireless networking standards. 152

A. IEEE 802.15.4-2003-Based ZigBee Specifications 153

ZigBee is a low-rate wireless personal-area network (PAN) 154

standard for embedded communication system with very low 155

power consumption. It proposes a lightweight1 protocol stack 156

for applications which require low data rates (up to 250 kb/s) 157

and low latency. ZigBee is designed to interconnect au- 158

tonomous sensors and actuators to control units. Battery life- 159

times last from a few months to many years as a result of 160

system power-saving modes, battery-optimized network param- 161

eters, and application configurations. ZigBee is based on IEEE 162

802.15.4-2003 PHY (868 MHz/915 MHz or 2.4 GHz) and AQ11163

MAC layers over which it specifies its network layer (NWK) 164

and APL (Fig. 1). 165

The responsibilities of the ZigBee NWK include mecha- 166

nisms used to join and leave a network, to apply security to 167

frames, and to route frames to their intended destinations. In ad- 168

dition, the NWK is in charge of the discovery and maintenance 169

of routes between devices. This is achieved by discovering one- 170

hop neighbors and storing relevant neighbor information. In a 171

star topology, the network is controlled by one single device 172

called the ZigBee coordinator. In mesh and tree topologies, the 173

ZigBee coordinator is responsible for starting a new network, 174

when appropriate, and assigning addresses to newly associated 175

devices, but the network may be extended through the use 176

of ZigBee routers. In tree networks, routers transfer data and 177

control messages through the network using a hierarchical 178

routing strategy. Tree networks may employ beacon-oriented2 179

communication as described in the IEEE 802.15.4-2003 180

1Full implementation of the protocol stack takes less than 32 KB of memoryand up to 64 KB for the network coordinator which requires extra RAM for thenode devices database and for transaction and pairing tables.

2Since the new release of ZigBee specification in 2008, this feature isabandoned for saving space in the MAC layer.

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AL AGHA et al.: WHICH TECHNOLOGY FOR WIRELESS SENSOR NETWORK? DEVELOPMENT OF OCARI 3

Fig. 1. ZigBee stack architecture [10].

specification. Concerning ZigBee routing strategy, it is a mixed181

mechanism composed of a simplified version of ad hoc on-182

Demand Distance Vector (AODV) [9], [12] and tree routing183

intended to extend the coverage of the network beyond the184

coverage of each network node.185

The ZigBee APL consists of the application support186

sublayer (APS), the ZigBee device object (ZDO) containing187

the ZDO management plane, and the manufacturer-defined188

application objects. The responsibilities of the APS include189

maintaining tables for binding, which is the ability to match190

two devices together based on their services and their needs,191

and forwarding application messages between bound devices.192

The responsibilities of the ZDO include defining the role of the193

device within the network (ZigBee Coordinator, Router, or End194

device), discovering devices on the network and determining195

which application services they provide, initiating and/or196

responding to binding requests, and establishing a secure197

relationship between network devices. More details about198

NWK and APL may be found in [10].199

IEEE 802.15.4 specifies two medium-access methods: unco-200

ordinated mode and coordinated mode (beacon-enabled mode)201

in which a coordinator (called the PAN-coordinator) regularly202

sends beacons to synchronize the network nodes. In coordinated203

mode, the PAN coordinator does not need to listen all the time204

to the communication channel. However, ZigBee has chosen205

the use of the uncoordinated mode that requires the ZigBee206

coordinator to listen permanently to the channel and, thus,207

wastes the coordinator battery. Energy is saved in ZigBee by208

allowing a very low power consumption for the end devices in209

“doze” mode (lower than 10 μA), and letting them switch to 210

normal operating mode in less than 300 μs. 211

In spite of these characteristics of ZigBee, this standard AQ12212

does not satisfy the very constrained battery autonomy of the 213

wireless sensor networks in application such as environmental 214

monitoring in large industrial facility. Indeed, as ZigBee does 215

not retain coordinated mode, only ZigBee End Devices (IEEE 216

802.15.4 Reduce Function Devices) can be put to a doze mode. 217

ZigBee Routers and Coordinators need to be always awakened 218

(active mode) in order to listen to the communication channel. 219

Crossbow and Telecom Italia have submitted an extension, 220

called low-power active router protocol for adoption in ZigBee 221

Pro 2009. It concerns the NWK and proposes some improve- 222

ments such as periodic listening to reduce radio duty cycle 223

and wake-up message that the receiver periodically sniffs for 224

a wake-up signal and then waits for data, otherwise, it sleeps 225

at the end of the wake-up period [13]. Another limitation of 226

ZigBee is that it does not directly support device mobility. 227

1) AODV only discovers the route on demand and the only 228

used QoS is the instantaneous radio link, thus, route repair 229

is done on error. The complete route-discovery process 230

can take a significant time (up to 10 s). This is not useable 231

in unstable topology in which network nodes regular- 232

ly move. 233

2) In ZigBee 2006 specification, when the link to the parent 234

node fails, a reassociation is required, and a new network 235

address is attributed to the concerned child node depend- 236

ing on its position in the network tree. This does not 237

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work for sleeping End Devices which might not receive238

the broadcast message signaling the new network-address239

renumbering. This limitation has been removed by the240

ZigBee Pro specification since its release in January 2008241

[11]: The network nodes keep their existing addresses,242

but new routes have to be rediscovered.243

In spite of these properties, ZigBee does not offer support for244

sink mobility [14] in which data-collector points travel through245

the nodes of a wireless sensor network.246

B. IEEE 802.15.4-2006-Based ISA100.11a Specification247

ISA100.11a is part of ISA100, a family of standards of248

wireless systems for industrial automation, which results from249

converging efforts of defining industrial wireless standards250

from different organizations and alliances such as WINA,251

NCCR-MICS, NSF-Program on Sensors and Sensor Networks252

and HCF. ISA100.11a Working Group3 aims at defining all253

specifications including security and management for wireless254

devices serving various application classes [15]. The focus255

here is to address performance needs for periodic monitoring256

and process control where latencies on the order of 100 ms257

can be tolerated with optional behavior for shorter latency.258

ISA100.11a specification is still under development. This re-259

view is based on published presentations and on current works260

from the ISA100.11a WG.261

ISA100.11a key features aim at responding to the following262

requirements:263

1) The ability to serve process-industry applications without264

excluding factory automation;265

2) In-plant and near-plant use;266

3) Technology to address different traffic class;267

4) A single APL providing both native and tunneling proto-268

col capability for broad usability;269

5) The addressing of 2.4 GHz IEEE 802.15.4-2006 PHY270

layer devices;271

6) A comprehensive coexistence strategy with channel hop-272

ping to support coexistence (with IEEE 802.11) and273

increase reliability;274

7) Simple, flexible, and scalable security addressing ma-275

jor industrial threats leveraging IEEE 802.15.4-2006276

security;277

8) Field-device meshing and star capability.278

ISA100.11a stack architecture has more layers than the Zig-279

Bee one. It lets the device-management application process280

(DMAP) directly access (using service access point) to the281

Data-Link Layer, the Network Layer, the Transport Layer,282

and the Application Sublayer in order to manage the de-283

vice and its communication services. The DMAP is a spe-284

cial type of user application process that provides a basis285

for building system-management-configuration application and286

communication-monitoring application. Either a distributed or287

centralized system manager is supported in ISA100.11a.288

ISA100.11a addresses failed communications using289

frequency- and slotted-hopping architecture by adding a MAC290

3Composed of industrial end users and technology providers.

Extension Shim [16] to IEEE 802.15.4 MAC, whereas a slow 291

frequency-hopping schema (frequency agility) is adopted in 292

ZigBee-2007 MAC, which is designed primarily for operation 293

in a fixed-channel network. 294

Two main classes of devices are defined in ISA100.11a: 295

Field Devices and Backbone Devices. A Field-Device class can 296

have devices with (i.e., IEEE 802.15.4 Full Function Device) 297

and without routing capability (i.e., IEEE 802.15.4 Reduced 298

Function Device). For example, a handheld device is considered 299

as a nonrouting field device. The typical mode of operation of 300

an SP100.11a handheld device is to attach to a full-function 301

device and to communicate data or monitor network traffic. 302

Roaming of handheld device is not supported by ISA100.11a. 303

Backbone devices are full-function devices which are contin- 304

uously powered, whereas field devices have limited battery 305

power (without routing capability) or moderate power (with 306

routing capability). 307

Network time and time-synchronization information for de- 308

vices on the network are provided by the system manager, a 309

particular backbone device, which acts as clock source. 310

Routing in ISA100.11a is based on graphs using a directed 311

list of links that connect devices. The links associated with each 312

graph are configured by the system-management function on a 313

centralized or decentralized basis. A single network instance 314

may have multiple graphs, some of which may overlap. Each 315

device may have multiple graphs going through it, even to the 316

same neighbors. Each device data-link layer service has one 317

route associated with it. 318

It is difficult to make some critical analysis of this evolving 319

specification. However, one may consider the technical diffi- 320

culties to implement the full stack architecture on low cost 321

hardware. In terms of software architecture, ISA100.11a WG 322

has produced a relatively complete functional specification 323

for system management that is almost absent from ZigBee 324

standard. Coexistence with WiFi is also taken into account 325

in ISA100.11a, and that is really appreciated in industrial 326

environment. Currently, there is no optimized routing strategy 327

for maximizing the lifetime of field network. 328

C. IEEE 802.15.4-2006-Based WirelessHART Specification 329

WirelessHART is specified in HART protocol specification 330

revision 7. The HART protocol is a digital-communication 331

technology that is designed for process measurement and con- 332

trol devices. 333

WirelessHART is an optional HART PHY, data link and net- 334

work layers. More details about WirelessHART can be found in 335

[17]. Compared with ZigBee and ISA100.11a, WirelessHART 336

has adopted time-division multiple access as an access method AQ13337

to the communication medium in order to offer an equivalent 338

of token passing procedure in wired HART. This gives some 339

deterministic behavior and guaranteed bandwidth. 340

WirelessHART does not specify, however, any energy-aware 341

ad hoc routing strategy in its network layer. 342

Before describing our OCARI project, let us summarize the 343

important features of ZigBee, WirelessHART, and ISA100.11a 344

specifications, as shown in Table I. AQ14345

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TABLE IZigBee, WirelessHART, AND ISA100.11a

PROTOCOL LAYERS CHARACTERISTICS

III. OCARI SPECIFICATION346

Regarding the aformentioned features of ZigBee, Wire-347

lessHART, and ISA100.11a, we have focused our work on348

improving the ZigBee standard by developing a complementary349

industrial specification called OCARI, rather than creating a350

new one from scratch. It aims at responding to the following351

requirements which are particularly important in power gener-352

ation industry and in warship construction and maintenance:353

1) Support of deterministic MAC layer (at least inside a cell,354

see Fig. 2) for time-constrained communication;355

2) Support of optimized energy-consumption routing strat-356

egy in order to maximize the network lifetime within the357

nontime-constrained communication period;358

3) Support of human walking-speed mobility for some par-359

ticular network nodes (sinks);360

4) Support of HART application layer APL (and EDDL-361

IEC61804).362

The development of OCARI targets the following industrial363

applications:364

1) Real-time centralized supervision of personal dose in365

nuclear power plant;366

2) Condition-based maintenance of mechanical and electri- 367

cal components in power plant as well as in warship; 368

3) Environmental monitoring in and around power plant; 369

4) Structure monitoring of hydroelectric dams. 370

In the following paragraphs, we will describe the main 371

specification points of OCARI. 372

A. OCARI Network Topology 373

Used-case analysis of the described industrial applications 374

shows that in most cases, the network topology can be modeled 375

as shown in Fig. 2. OCARI End Device is a “radio-fixed” 376

network node [i.e., its position varies very little compared with 377

its initial location so that its radio link is always managed by 378

the same cell coordinator (CC)]. It is a Reduce Function Device 379

as defined in IEEE 802.15.4 specification. OCARI Cell and 380

Workshop Coordinators are Full Function Devices as specified 381

in IEEE 802.15.4. They are fixed devices in the infrastructure 382

and are equivalent to ZigBee Coordinator. The functions of the 383

CC consist of the following: 384

1) Coordinating the intracell network nodes using a star 385

topology; 386

2) Routing data packets in push mode from end-device 387

network nodes (i.e., sensors in our industrial applications) 388

to the Workshop Coordinator per Workshop domain. 389

Tree routing [18], [19] is used in a time-constrained 390

period and an energy-aware OLSR [20] is used otherwise 391

between CCs. 392

Workshop domain is a permissive volume (delimited by a 393

threshold of the BER, the SINR, or the received signal strength 394

indication [21]) to electromagnetic wave that is covered by a AQ15395

unique Workshop-Coordinator network node. 396

Workshop Coordinator is a gateway (even in polling 397

mode used by most of supervisory control and data 398

acquisition—SCADA—applications) between the wireless sen- 399

sor networks that resided in a Workshop domain and the indus- 400

trial facility backbone. 401

As shown in Fig. 2, Sink node is a mobile-network node 402

which usually represents a patrolman/maintenance operator, 403

equipped with a personal digital assistant, collecting data from AQ16404

sensors inside a cell. The Sink leaves the cell when it finishes 405

to acquire data (in polling mode). 406

Time server is a particular network node which is used for 407

clock synchronization in the whole Workshop domain. For an 408

accurate clock synchronization, IEEE-1588/IEC 61588-2004 409

protocol [22], [23] (Precision Time Protocol, PTP) is used. 410

B. OCARI PHY and MAC Layers 411

Previous studies [24], [25] and our field tests show that 412

IEEE 802.15.4 PHY is very robust. Based on the robustness 413

of IEEE 802.15.4 PHY 2.4 GHz, we decided to adopt it for the 414

OCARI specification. However, as stated earlier, IEEE 802.15.4 415

MAC layer does not completely satisfy our requirements. Our 416

consortium is developing a derived MAC layer [18], [19] that 417

offers different access methods to the medium. 418

1) Global MaCARI Protocol: The context of industrial ap- 419

plications brings many challenges for the MAC protocol, such 420

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Fig. 2. OCARI network topology.

as deterministic communications or low energy consumption.421

In order to be suitable to the large variety of application422

requirements, we proposed a flexible MAC protocol, MaCARI,AQ17 423

which is introduced in [18].424

As with many MAC protocols for wireless sensor networks,425

MaCARI includes some multihop routing features.426

Justifications of main ideas of MaCARI: A deterministic427

MAC layer has to guarantee an access to the radio channel for428

each device of the WSN every certain period of time (which429

is the global cycle of Fig. 3). An energy-efficient MAC layer430

has to make all the network elements sleep as often as possible431

during the global cycle.432

We designed the MAC protocol for the OCARI project,433

denoted by MaCARI, in order to achieve a tradeoff between434

these two main features: determinism and energy efficiency.435

The routing features of MaCARI can be explained using436

an analogy to the return of salmons to the region where they437

were born in. When it is too difficult for the salmon to swim438

upstream, a fish pass can help the salmon by providing an439

alternate path, which is easier but generally longer. Similarly, in440

Fig. 3. OCARI global cycle.

MaCARI, frames can be forwarded directly (to the destination 441

node or to a chosen relay node) or indirectly, by following a 442

path by default. The indirect forwarding corresponds to the fish 443

pass, where the path by default is a spanning tree of the network 444

topology having the PAN coordinator as its root. 445

We decided to have two periodic disjoint phases, each of 446

them corresponding to a type of forwarding (direct or indirect). 447

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To do so, a synchronization of the network devices is necessary.448

This leads us to the design of a global cycle constituted of three449

periods: the synchronization, the scheduled activities, and the450

unscheduled activities periods. These three periods are shown451

on Fig. 3.452

Specifications of three MaCARI periods: MaCARI uses453

the PAN coordinator (usually the workshop coordinator) to454

manage the global cycle. The synchronization is performed455

using a single beacon broadcasted in the network in a hop-by-456

hop manner. In order to avoid beacon collisions [29], each CC457

repeats the beacon at a time decided by the PAN coordinator458

so that no beacons are transmitted simultaneously. This beacon459

carries the order in which the CCs have to transmit their beacon,460

which is computed by the PAN coordinator. This sequence461

of beacon transmissions is triggered by the PAN coordina-462

tor at T0. At T1, all the network devices have a common463

time reference.464

The scheduled activities period, which lasts between T1465

and T2, divides time into disjoint slots. The PAN coordinator466

allocates to each cell a given number of slots (usually one).467

During the slot of a cell, the active entities are the following:468

the CC of the cell, the end devices of this cell, and the father469

coordinator of the CC. During this slot, the CC is in charge470

of the communications. The way the slot is used is described471

in Section III-B2. Toward the end of the slot, the CC can ex-472

change data with its father coordinator using polling/selecting.473

By having attributed disjoint time slots to the cells, MaCARI474

guarantees no intercells interferences and a dedicated channel475

between each father and child.476

The unscheduled-activities period takes place during T2 and477

T3. During this time interval, MaCARI manages the activ-478

ity of nodes according to SchEdule RoutEr Nodes Activity479

(SERENA) requests (see Section III-D3), and tries to sendAQ18 480

frames according to routes given by the energy-efficient OLSR481

(EOLSR) routing protocol (see Section III-D2). During thisAQ19 482

period, time slots are given according to a sequence of colors483

(see the part on the SERENA protocol). All the nodes of the484

current color can transmit simultaneously in an independent485

way. During this period, MaCARI does not decide any spe-486

cific scheduling, which is why we refer to this period as the487

unscheduled-activities period.488

Energy-efficiency summary: During the synchronization pe-489

riod, a device of a given cell can sleep as soon as the CC of490

its cell has transmitted the beacon, until the time when it has491

to be active (which occurs at some point between T1 and T2).492

During the scheduled-activities period, all the end devices of a493

cell sleep, except when their cell is active. When a cell is active,494

the father coordinator of the CC is also awaken to provide495

father–son exchanges. During the unscheduled activities period,496

all end devices sleep, but the activity of the CCs depends on the497

SERENA protocol.498

Determinism summary: Once every global cycle, each end499

device has access to the channel during the time slot of its cell.500

Once every global cycle, the coordinator manages the commu-501

nications with its end devices according to strategies described502

in Section III-B2. Each pair of father–son coordinators has a503

dedicated channel (i.e., a part of the time slot) to route frames504

on the default routing path.505

The length of the global cycle determines the reactivity of the 506

protocol. The duration of [T1;T2] impacts on the deterministic 507

behavior of MaCARI, while the duration of [T2;T3] allows 508

the use of simultaneous activities, and, therefore, increases the 509

throughput of the network. 510

2) Intracellular MaCARI Protocol—An Incremental Proto- 511

col With Several Options: This part focuses on the intracellular 512

MaCARI protocol. Our proposal is an incremental protocol 513

with three different options which increase the previous one in 514

terms of bandwidth and energy saving. The MAC layer inside 515

the cell is used when the CC is authorized to communicate 516

since it has received a beacon of its father. During [T1;T2], the 517

cell owns a guaranteed medium access, i.e., without collision 518

or interference risks against the other nodes of the OCARI 519

network. 520

Slotted CSMA/CA in beacon-enabled mode [28]: The 521

simplest intracellular medium access method is based on 522

the well-known slotted carrier sense multiple access/collision 523

avoidance (CSMA/CA). Every slot allocated between T1 and AQ20524

T2 corresponds to a superframe (as in IEEE 802.15.4 vocabu- 525

lary). Each node of the cell uses the same distributed protocol. 526

As an end device, a node can only exchange with its CC. Data 527

for end devices are transmitted by the CC during a timeslot 528

requested by the end device. Concurrent accesses are avoided 529

by the CSMA/CA method. This best effort MAC is relevant for 530

a lightly loaded cell with regard to the QoS requirements. We 531

have done a simulation and an implementation of this slotted 532

CSMA/CA protocol. Some performance analyses are presented 533

in [18], [33], and [34]. 534

CSMA/CA + GTS [28]: The random characteristic of 535

the CSMA/CA implies a collision risk between two or more 536

devices of the same cell. In fact, quasi-simultaneous clear- 537

channel assessment function calls by concurrent transceivers 538

entails a collision. The consequences of the phenomenon could 539

be insignificant for most applications but could be disastrous 540

when the submitted network load is important. Indeed, the 541

more frames to transmit, the more collisions and the more 542

frames to retransmit. A collapse phenomenon appears which 543

implies a low-bandwidth usage. Delays are also increased. This 544

can be unacceptable for time-constrained applications. This 545

problem can be avoided by using, in each cell, a specific access 546

method using a superframe with two periods: contention-access 547

period (CAP) and contention-free period (CFP). CAP uses only 548

CSMA/CA. This period permits a basic QoS for nonpriority 549

flows without temporal guarantees. This best effort algorithm 550

can be used for sporadic and unexpected flows. CFP uses some 551

dedicated timeslots allocated by the CC to its own end devices. 552

These slots are named guaranteed time slot (GTS). 553

According to the application needs of each sensor, an end 554

device requests to its coordinator a GTS allocation for the 555

next superframe. If the minimal size of the CAP has not 556

been reached, the CC can allocate a new GTS. The CAP is 557

reduced accordingly. If an end device does not use its GTS 558

during a specific duration, this GTS is automatically suppressed 559

(by timeout). The end device must request for a new GTS 560

attribution in the next superframes. The IEEE 802.15.4 standard 561

has proposed this algorithm, but it is rarely implemented on 562

available devices on the market or on evaluation kits. We have 563

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implemented this GTS option in a prototype, and performance564

analyses are in progress.565

Experimentation results from a small configuration have566

shown that GTS option offers a better temporal stability com-567

pared with the CSMA/CA option. For example, the jitter on the568

medium-access delay is almost nonexistent with the GTS. This569

jitter varies between 4 and 11 ms in CSMA/CA (respectively,570

from one to five packets by superframe transmitted by four571

end devices in a star topology). In addition to its deterministic572

character and the low jitter, another advantage concerns the573

energy economy. Indeed, it is possible to make end devices574

sleep except their GTS, which is more difficult to realize using575

CSMA/CA.576

CSMA/CA + GTS(n) (with multiple reservation levels):577

The previous solution is an interesting option, but its major578

drawback is the GTS static allocation for each superframe.579

For example, one GTS by superframe could be useless for a580

simple temperature sensor. It would be interesting to propose581

a service differentiation according to application communica-582

tion end-device needs. This new intracellular MaCARI option583

proposition is based on a special reservation level named n.584

A GTS is dedicated to an end device according to its period-585

icity request: when n = 0: for each superframe (as in IEEE586

802.15.4 standard), when n = 1: every two superframes, and,587

in the general case: every 2n superframes. The main advantage588

is the cohabitation of different guaranteed traffics according589

to different sensors. It is also possible to choose a reverse-590

allocation principle. In a superframe, a sensor could have more591

than one GTS. In this case, the reservation level is n = 0.592

However, the end device must request several GTS in each593

superframe. The bandwidth allocated to such an end device is594

increased.595

The other advantage of this GTS(n) option is the power596

saving offered by this MaCARI layer. A sensor can commute597

to doze mode, particularly when this sensor is not concerned of598

these superframes. If a temperature sensor has a high inertia,599

its end device can wake up only every four or eight super-600

frames for a fast and short temperature transmission. After this601

activity, the end device commutes to battery-saving mode. In602

the classical IEEE 802.15.4 protocol, a wake up is mandatory603

for every superframe to keep the GTS. In our proposition,604

it is possible to save timeslots with an optimized allocation605

only when it is necessary. This option maximizes doze mode606

outside GTS. We are currently implementing this option in the607

prototype.608

CSMA/CA + GTS(n) + PDS: The principal drawback609

of the previous option (also in the IEEE 802.15.4 standard)610

is related to the GTSrequest which is necessarily done by611

the end device in CSMA/CA mode. This request mode is612

not fully deterministic because this GTS request access is613

nonguaranteed. For critical sensor applications which need614

guaranteed access, we propose a new intracellular MaCARI615

option based on previously dedicated slot (PDS). A PDS is616

allocated to every known specific sensor which wants to use617

this high level of QoS. A PDS is in fact an a priori GTS.618

This PDS can be used by an end device to transmit periodic619

data with high QoS. The end device can also use this PDS to620

request more or less GTS. This dynamic GTS allocation permits621

variation according to bandwidth and delay needs. To avoid an 622

overload of the used bandwidth, a large n is associated to this 623

first PDS. An analytical performance analysis [5] shows that 624

the bandwidth used for this PDS is small (0.78% for a PDS 625

with n = 3). At the moment, we also have implemented this 626

option which offers the best energy efficiency. Indeed, there 627

is no more energy lost by the end device to request GTS, 628

since there is no transmission of GTSrequest in the case of 629

the PDS. 630

Conclusion for intracellular MaCARI protocol: Intracel- 631

lular MaCARI proposes a core based on beaconed-slotted 632

CSMA/CA and three other optional functionalities. This core 633

should be satisfactory in most cases when only a low baud 634

rate is necessary. The second option (IEEE 802.15.4 GTS) 635

may propose a first level of determinism. The new option 636

GTS(n), which requires GTS, proposes a higher QoS flexibility 637

owing to a mechanism of service differentiation. Moreover, 638

the energy saving resulting from this option is previously 639

required by the OCARI project which aims to propose a MAC 640

layer with energy-saving functionalities. New option based 641

on PDS enables a higher level of determinism. These vari- 642

ous options are increasingly effective with regard to energy 643

optimization. 644

C) OCARI Energy-Autonomy Model: The majority of 645

OCARI nodes operate on batteries and are energy dependent. 646

The lifetime of a node depends on the lifetime of its battery. 647

Indeed, to be scalable, replacing a battery when its functioning 648

becomes critical is not permitted because of the required hu- 649

man overhead. The solution that OCARI proposes is to create 650

energy-efficient solutions that reduce the battery utilization of a 651

node and transfer traffic to nodes with more remaining energy 652

in their batteries. 653

In sensor and ad hoc networks area, many works were 654

considered a simple energy model for node operations (routing, 655

processing, . . .). The idea is to suppose an initial amount of 656

energy that is mostly equal for all nodes and then applying a 657

subtraction for every operation. Different levels of consumption 658

were calculated according to the specific operation (transmis- 659

sion, reception, waking up, . . .). Then, when the energy level 660

becomes low, the node is kept away and works only for elemen- 661

tary and basic operations to avoid its death and its elimination 662

from the network. This model seems to be linear and is, in 663

fact, far from the reality. The battery manufacturers [30], [31] 664

display the discharge curves of their products which is close 665

to a constant discharge until a critical point where the battery 666

is dead. 667

Our goal in OCARI is to integrate the energy cost of the 668

functions performed by a node in order to estimate its remaining 669

energy level. This level serves, as indicated in the next section, 670

as a metric for the routing protocol. Nodes select routes to desti- 671

nation according to the energy cost estimated by our model. The 672

idea consists in affecting an initial value of energy to a battery 673

or a node and then subtracting from this value an amount that 674

corresponds to the given operation (transmission, reception, 675

wake up, . . .) and also to the date of this operation. The date 676

takes into account how many times the battery is used. The 677

more the battery is used, the lesser its energy replenishes. We 678

define an exponential function where the slope corresponds to 679

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Fig. 4. Battery self-discharge model (Max = 200; const = 104; t1 is chosenrandomly between 0 and 58 ms).

the date and the amplitude to the quantity of energy consumed680

by the specific operation681

Rr(0) = Max

Rr(i) = Rr(i − 1) − C(i)e−constΔi

where682

Rr(i), i ∈ N remaining energy in a node at date i;683

Max maximum energy for a node;684

C(i) consumed energy during the step i;685

Δ duration in seconds of step i;686

Const constant.687

The value of C(i) is calculated according to the ZigBee688

standard where689

Etx = 30.2 × 10−6 mA · H + 8.0556 × 10−6 × t1

for packet transmission690

Erx = 40.986 × 10−6 mA · H + 8.0556 × 10−6 × t1

for packet reception, etc.691

Note that a node is consuming more energy for data reception692

than for data transmission.693

Simulation results (Fig. 4) show the discharge function ac-694

cording to the time when a node transmits or receives data.695

The duration of operation were taken following a uniform696

distribution. Those results show a better behavior of a discharge697

than a linear model and fit better with real measurements that698

we realized in a real environment.699

D) OCARI Network Layer:700

1) Energy-Efficient Strategies: The energy-constrained701

nature of OCARI nodes requires the use of energy-efficient702

strategies to maximize network lifetime. We can distinguish703

four types of energy-efficient strategies [32]:704

1) Topology control algorithms where a node adjusts its705

power transmission instead of transmitting with the max-706

imum power;707

2) Algorithms that reduce volume of information transferred708

by aggregating information, optimizing network flooding,709

avoiding useless transmissions, or tuning the period of710

control messages;711

Fig. 5. Distribution of node energy in the transmit and receive states.

Fig. 6. Distribution of node energy in the idle, overhearing, and interferencestates.

3) Energy-efficient routing algorithms select routes that min- 712

imize the energy consumed by the end-to-end transmis- 713

sion of a message and avoid nodes with low residual 714

energy; 715

4) Scheduling node-activity algorithms allow nodes to sleep 716

in order to spare energy, provided that the network and 717

application functionalities are still ensured. 718

In the first version of OCARI, all nodes transmit with 719

the maximum power. Hence, all energy-efficient-strategy cat- 720

egories, except the first one, are used in OCARI. In this section, 721

we detail the two modules comprising the network layer: the 722

energy-efficient routing called EOLSR and the scheduling of 723

router nodes activity called SERENA. 724

2) EOLSR: EOLSR is an energy efficient extension of 725

the OLSR routing protocol. OLSR [33] is a proactive protocol 726

based on link state. It has been tuned to wireless ad hoc 727

networks by the concept of multipoint relays (MPRs). MPRs 728

reduce the amount of links advertised in the network and the 729

number of transmissions needed to advertise an information in 730

the network. OLSR consists of two basic functionalities. 731

1) Neighborhood Discovery: Each router node acquires the 732

knowledge of its one- and two-hop neighbors by exchang- 733

ing periodic Hello messages. It independently selects its 734

MPRs among its one-hop neighbors in order to cover all 735

its two-hop neighbors. 736

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Fig. 7. OCARI stack.

2) Topology Dissemination: A node selected as MPR sends737

a Topology Control message in the network; this message738

is forwarded by the MPRs if and only if it is the first739

receipt. Each router node uses the information included in740

the Topology Control messages to determine the shortest741

route to any destination in the network. We can then742

notice that in OLSR, the intermediate nodes of a route743

are MPR nodes.744

As the selection of MPRs does not take into account the745

residual energy of nodes, and as the shortest route is not746

always the route consuming the least energy, OLSR does not747

maximize network lifetime. EOLSR has been introduced for 748

this purpose. It keeps the principles of OLSR. The classical 749

selection of MPRs is kept to optimize broadcasts in the net- 750

work, whereas new ones, called extended MPRs (EMPRs), AQ21751

taking residual energy of nodes into account, are used to build 752

routes. The route selection is also modified in order to select 753

the route that minimizes the energy dissipated by the end- 754

to-end transmission of a packet, including the energy lost in 755

transmitting, receiving, overhearing, and in interferences. If 756

several routes dissipate the same energy, the shortest one is 757

chosen. 758

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Fig. 8. OCARI application architecture.

EOLSR does not require additional messages, existing mes-759

sages of OLSR are extended to include the residual energy of760

nodes, computed as explained in Section III-C. For more detailsAQ22 761

on EOLSR, the reader can refer to [20].762

3) SERENA: SERENA deals with scheduling of router-763

nodes activity; it is the second module comprising the network764

layer. In order to spare energy, a node must sleep. However,765

it must be awake to receive messages. Hence, a coordination766

of nodes is required. In SERENA, this coordination is done as767

follows: A node is awake only during its slots (i.e., the slots768

during which it can transmit) and the slots granted to its one-hop769

neighbors. Slots are assigned to a node according to its color770

and its traffic.771

As interferences are limited to two hops, a two-hop coloring772

algorithm is used. (In OCARI specification, the interference773

model is based on two times the estimated radio range.) The774

coloring algorithm is decentralized: A node colors itself if and775

only if all the nodes up to two-hop with a higher priority are776

already colored. The node selects the smallest color available777

up to two hop. The priority of a node is the couple (cardinality778

of the up to two-hop neighborhood, node identifier). In the first779

version of OCARI, a simple slot assignment is provided, using780

cross-layering mechanisms. A more sophisticated one can be781

found in [26].782

When nodes move, conflicts of colors can occur: Two nodes 783

that are either one- or two-hop neighbors have the same color. 784

Such conflicts are detected and solved: The node with the 785

highest priority keeps its color, whereas the other selects the 786

smallest color available up to two hop. 787

4) Performance Evaluation: We now quantify the ben- 788

efits brought by EOLSR and SERENA, used separately and 789

then, in combination, in a wireless ad hoc network. As the 790

MaCARI layer is under implementation, the results shown in 791

Figs. 5 and 6 have been obtained with an IEEE 802.11 network 792

at 2 Mb/s; the powers used in the different states are: 1.3 W 793

in the transmit state, 0.9 W in the receive state, 0.74 W in 794

the idle state, and 0.047 W in the sleeping state. There are 795

150 nodes with a network density (i.e., average number of 796

one-hop neighbors) of ten. The initial energy of the nodes is 797

equal to 100 J. User traffic consists of 30 flows, with randomly 798

chosen sources and destinations, and a throughput of 16 Kb/s. 799

Message size is 512 B. Messages of the routing protocol are not 800

taken into account. Each result is the average of five simulation 801

runs. 802

As expected, Figs. 5 and 6 show that with SERENA and 803

EOLSR, less energy is dissipated in the idle and interference 804

states leaving more energy for transmitting and receiving mes- 805

sages. This justifies the choice of the EOLSR and SERENA 806

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algorithms. Both algorithms contribute to a more efficient use of807

node energy. Moreover, we have also shown that EOLSR alone,808

SERENA alone, and EOLSR+SERENA increase the network809

lifetime by 40%, 195%, and 275%, respectively. Notice that810

we obtain similar results for the amount of data delivered by811

EOLSR and SERENA used separately or in combination. This812

result highlights the true gain obtained by these protocols: the813

application benefits from this increased network lifetime by814

exchanging more user data.815

In OCARI, the MAC layer provides an immediate acknowl-816

edgment of any unicast message received by its destination.817

That is why SERENA is now evolving toward a three-hop818

coloring algorithm. We expect simulation results with three-hop819

coloring to be similar to those shown in Figs. 5 and 6, allowing820

us to conclude to the better energy efficiency of SERENA and821

EOLSR.822

E) OCARI Stack Architecture: From the work of the differ-823

ent partners, an architecture is defined to organize the develop-824

ments of each layer (Fig. 7).825

This architecture reflects also the choice for prototyping the826

system on two boards, each containing its own microcontroller.827

The first board is for the PHY and the MAC layers, and the828

second board is for the upper layers. It implies defining a829

hardware interface between the MaCARI layer and the upper830

ones allowing the configuration of radio parameters, the transfer831

of data, as well as the interactions between SERENA and832

MaCARI for energy management.833

As the goal is for this stack to be implemented in low-cost834

microcontrollers, it is kept as simple as possible.835

F) OCARI Platform Prototype: In order to evaluate, verify,836

and validate the OCARI specification, we define the following837

platform in which we will implement different communication838

layers. The PHY and MAC layers are implemented inside the839

same communication controller module (One-RF B2400MC-840

Tiny), designed by our partner, Telit.841

OCARI routing strategy and the ZigBee NWK and APS are842

implemented on another module, which is a PC platform for843

ease testing and debugging. On the final architecture, the code844

is put on a different microcontroller.845

G) OCARI Application Architecture: To achieve a seam-846

less integration of wireless sensor networks into real-world847

applications in industrial information systems, we need to848

develop and provide an application architecture that can in-849

teroperate with existing industrial standards. The architecture850

shown in Fig. 8 aims at responding to such requirement851

while supporting the state of the art in industrial information852

technology.853

The role of a WSN-oriented middleware is to provide stan-854

dard and homogenous services to user applications. It also855

contributes to the energy saving of the WSN by implementing856

a centralized and optimized management of network resources857

[27]. Moreover, it serves as a gateway between different userAQ23 858

applications and different Workshop Coordinators, which man-859

age the attached cells.860

The choice of a software-bus standard such as OPC-data861

access and the upcoming version OPC-unified architectureAQ24 862

allows us to provide the compatibility with EDDL for assetAQ25 863

management and for SCADA application.864

IV. FUTURE WORK 865

In the next steps of our project, we will be working on the 866

implementation and the extension of different components of 867

our specification. We believe that OCARI fills some gaps, as 868

stated earlier, in ZigBee while trying to be compatible with 869

ZigBee APS and APL layers. In this way, we can preserve 870

existing efforts and investments on application development 871

already realized using ZigBee technology. 872

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[34] G. Chalhoub, E. Livolant, A. Guitton, A. Van den Bossche, M. Misson,957and T. Val, “Specifications and evaluation of a MAC protocol for a LP-958WPAN,” Ad Hoc Sensor Wireless Netw., vol. 7, no. 1/2, pp. 69–89, 2009.959

[35] M.-H. Bertin, A. Van den Bossche, G. Chalhoub, T. Dang, S. Mahfoudh,960J. Rahmé, and J.-B. Viollet, “OCARI for industrial wireless sensor net-961works,” in Proc. IFIP Wireless Days Conf., Dubai, United Arab Emirates,962Nov. 24–27, 2008, pp. 1–5.963

Khaldoun Al Agha (SM’03) received the B.S. de-964gree in engineering from Supelec, Paris, France, in9651993, and the M.S. and Ph.D. degrees from theAQ28 966University of Versailles, Versailles, France, in 1995967and 1993, respectively. He received the HDR fromAQ29 968University of Paris-Sud11, Paris, in 2002.AQ30 969

In 1998, he was an Assistant Professor with the970University of Versailles. In 1999, he was with the971French National Institute for Research in Computer972Science and Control (INRIA) for one year. He is973currently a Full Professor with the University of974

Paris-Sud11. He created and conducts the networking group at the LRI labo-975ratory. He participates in different projects (BRAIN, SAMU, Arcade, SAFARI,976OCARI, SARAH, RAF, NC2, etc.). His research interests are on resource977allocation, security, and Quality of Service for cellular and ad hoc networks.978

Marc-Henry Bertin, photograph and biography not available at the time of979publication.AQ31 980

Tuan Dang (M’06) received the B.S. degree in981engineering from the “Ecole Centrale de Nantes,”982Nantes, France, and the Ph.D. degree from the “EcoleAQ32 983Nationale Supérieure des Télécommunications de984Paris,” Paris, France.985

He is the Expert Research Engineer with Simu-986lation and Information Technologies for Power gen-987eration systems (STEP) Department, Electricité De988France (EDF) Research and Development, Chatou,989France. His research fields are industrial communica-990tion networks, automation and telecontrol of power-991

generation systems, home and building automation, and energy management.992He has published tens of papers in industrial informatics.993

Dr. Dang is a member of IEEE Industrial Electronics Society-Building994Automation, Control and Management.AQ33 995

Alexandre Guitton (M’09) received the M.Sc. and 996Ph.D. degrees in the field of computer networks from 997the University of Rennes I, Rennes, France, in 2002 998and 2005, respectively. 999

Since 2007, he has been with Clermont University, 1000Aubière, France, where he is currently an Assistant 1001Professor. His research interests include wireless 1002communications, sensor networks, MAC protocols, 1003and energy-efficiency. 1004

Pascale Minet is currently the Vice-Head of the 1005HIPERCOM project with the French National Insti- 1006tute for Research in Computer Science and Control 1007(INRIA) Le Chesnay, France. Her research interests 1008include routing, Quality of Service and multicast 1009in mobile ad hoc networks, energy efficiency, and 1010deployment of wireless sensor networks, as well as 1011real-time scheduling. 1012

Ms. Minet serves as program committee member 1013of several international conferences. 1014

Thierry Val received the Ph.D. degree in com- 1015puter science at Blaise Pascal University, Clermont- 1016Ferrand, France, in 1993 and the HDR from 1017University of Toulouse II, Toulouse, France, in 2002. 1018

He has been with the University of Toulouse 1019where he was a Lecturer when he joined in 1994 and 1020currently teaches networks and hardware systems. 1021He is also the Submanager of the Laboratory of 1022Technology and System Engineering of Toulouse 1023(LATTIS) where he manages a research activity 1024on engineering wireless local networks and related 1025

protocols in collaboration with IRIT-CNRS of Toulouse, LAAS-CNRS of 1026Toulouse, LIRMM-CNRS of Montpellier, and LIMOS-CNRS of Clermont- 1027Ferrand. He is also currently a Professor with the Institute of Tolouse-Blagnac, 1028University of Toulouse. AQ351029

Jean-Baptiste Viollet received the B.S. degree from 1030Polytechnique and from Ponts et Chaussées in 1031early 2007. AQ361032

Since the spring of 2007, he has been with Di- 1033rection des Constructions Navales Services (DCNS) 1034group, Lorient, France, where he is currently an 1035Engineer in charge of the study and tests of the 1036conduct domain and a Conduct Partner in the project 1037FREMM and is in charge of the OCARI R&D project 1038at DCNS. 1039

Which Wireless Technology for Industrial Wireless Sensor Networks? The Development of OCARI...

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