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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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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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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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8 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 56, NO. 10, OCTOBER 2009
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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AL AGHA et al.: WHICH TECHNOLOGY FOR WIRELESS SENSOR NETWORK? DEVELOPMENT OF OCARI 9
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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10 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 56, NO. 10, OCTOBER 2009
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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12 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 56, NO. 10, OCTOBER 2009
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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[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
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