Layered Software Challenge of Wireless Technology in the Oil & Gas Industry

Stig Petersen SINTEF ICT

stig.petersen@sintef.no

Simon Carlsen and Amund Skavhaug StatoilHydro ASA

{scar, amusk}@statoilhydro.com

Abstract

Recent advances in wireless technology have enabled the development of low-cost wireless solutions capable of robust and reliable communication within application areas such as wireless networking, wireless sensor networks, and asset tracking. For the Oil & Gas industry, utilizing this technology will lead to reduced operating costs and enable new applications.

There are several challenges related to the introduction of wireless technology in the Oil & Gas industry. Primarily, wireless devices have to execute software implementations of complex network algorithms with real-time requirements on embedded platforms with limited resources and low-power requirements. Further, how to enable the monitoring and control applications of the wireless solutions to be managed and operated by technical personnel who do not necessarily have extensive knowledge of the underlying wireless technology. And finally, wireless systems should seamlessly integrate with already existing IT infrastructure and user applications.

In this paper, issues related to these challenges are investigated.

1. Introduction Recent advances in wireless technology have

enabled the development of low-cost wireless solutions capable of robust and reliable communication. International standards such as the IEEE 802.11a/b/g [1][2][3][4] for wireless local area networks and the IEEE 802.15.4 [5] for low-rate wireless personal area networks, as well as numerous RFID (radio-frequency identification) specifications, have enabled applications such as wireless networking, wireless

sensing, monitoring and control, and wireless asset and personnel tracking.

Wireless technology has the potential to be beneficial to the Oil & Gas industry in many regards [6]. Eliminating the need for cables can contribute to reduced installation and operating costs, it enables installations in remote and hostile areas, and it allows for cost-efficient temporary and mobile installations. In addition, wireless technology will enable a new range of applications, particularly in the area of health, safety and environment (HSE).

Technical requirements for the deployment of wireless technology in the Oil & Gas industry have been identified in [7]. This work states that wireless solutions have to be based on open, international standards, and operate in the unlicensed portions of the frequency spectrum. When two or more systems operate in the same frequency band, it is imperative that they are able to friendly coexist. As wireless technologies are more susceptible to environmental changes than their wired counterparts, it is crucial to be able to quantify the expected and operational reliability and availability of a wireless link and/or network. To protect against privacy and access security breaches, wireless solutions need to implement data encryption, transmitter authentication and data consistency validation. For battery operated devices, such as wireless sensors, the Oil & Gas industry is pushing for battery lifetimes in excess of five years (at a one-minute update rate).

In this paper, the application areas for wireless technology in Oil & Gas industry are identified and described, along with the relevant wireless systems and standards utilized in each area. The main contribution of this paper is the investigation of the layered software challenge related to the introduction of wireless technology in the Oil & Gas industry. In this context, the term layered software challenge is used to emphasize that there are many different software

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challenges found in various abstraction layers. These challenges span embedded software running on wireless devices, the user interfaces for the configuration, monitoring and control of the wireless systems, and the integration of wireless systems with existing IT infrastructure and user applications.

2. Applications areas

Three main application areas for wireless

technology in the Oil & Gas industry have been identified, namely wireless network access, wireless sensing, monitoring and control, and asset and personnel tracking.

2.1. Wireless network access

Wireless access to the corporate LAN, or even the

Internet, from within process areas has been a main focus in the Oil & Gas industry for the last couple of years.

Although there are several technologies for wireless computer networking, the major standard for short-range communication is the IEEE 802.11 family of standards for wireless local area networks (WLANs). [1][2][3][4]. WLAN operates in the unlicensed frequency bands of 2.4 and 5 GHz. Table 1 shows an overview of the most common WLAN specifications.

Table 1. IEEE 802.11 specifications Standar

d Frequenc

y Band Practical

Bandwidth (~50%)

Theoretical Maximum

802.11 2.4 GHz 1 Mbps 2 Mbps 802.11a 5 GHz 26 Mbps 54 Mbps 802.11b 2.4 GHz 5.5Mbps 11 Mbps 802.11g 2.4 GHz 26 Mbps 54 Mbps 802.11n

(expected 2008)

2.4 GHz and 5 GHz

240 Mbps 300 Mbps

The use of WLAN networks in both homes and

offices has increased rapidly since the late 1990’s. Today, one hardly finds office facilities, hotels or other public spaces that do not provide Wireless LAN access.

In Oil & Gas process plants, however, the introduction of such networks has followed a much more restrictive line. There are several reasons for this. First of all, production failures in process plants must be avoided because of the possible impact on health, safety and environment (HSE). Secondly, failures and stops often results in large immediate financial losses,

in addition to the long-term consequences of reducing the company’s status as a reliable supplier. Furthermore, electronic communication systems in process plants have traditionally been taken care of by automation and telecom groups, seeing wireless computer networks as an (office) IT issue. Many people have negative experiences with wireless networks in their homes or offices. This has probably led to the widespread view that wireless networks are not capable of providing the necessary stability and reliability expected in industrial communication systems. These factors have contributed to the rather conservative approach to introducing new technologies such as wireless networks in the Oil & Gas industry. As a consequence, few suppliers produce WLAN equipment tailored for operating in industrial environments. For WLAN equipment designed for operating in hazardous locations, e.g. EX-zones, the selection is even more limited.

However, the Oil & Gas industry’s recent focus on wireless network access within process areas has led to a growing understanding for the need of this market by an increasing number of vendors. There is also an ongoing trend where IT disciplines are merging with the traditional automation and telecom disciplines. It is therefore expected that the selection of WLAN equipment designed for operating in hazardous zones will expand in the near future.

The following section presents some relevant application areas benefiting from wireless network access in the Oil & Gas process plant.

2.1.2. Simplifying work processes. Traditionally, work processes in Oil & Gas process plants involve a number of manual operations. As an example, a typical workflow for operation and maintenance tasks is presented in Figure 1. This flowchart illustrates how several activities have to be performed in a given order. If we consider a maintenance operation where notifications and work orders are required, typically the whole process has the following progression from a field operator’s point-of-view (simplified):

1. Initiate operation 2. Create a notification. (This is commonly done

with the corporate Enterprise Resource Planning (ERP) system.)

3. Await confirmation from ERP system 4. Create work order (ERP) 5. Await signed work permit 6. Prepare operation 7. Plan operation 8. Execute maintenance operation 9. Close operation

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10. Verify technical condition restored 11. Update documentation, both in technical

document systems and ERP

Start task

Notification necessary?

Create Notification

Work Order required?

Prepare operation

Simplified Execution

Close taskExecute planned operation

Operation planning required?

Operation planning

YES

YES

YES

NO

NO

NO

Figure 1. Workflow for maintenance operation

Wireless network access in the field can help

simplify this process. Consider a PDA (Personal Digital Assistant) with wireless access to company backbone systems, combined with an RFID or barcode reader for reading tag information from plant equipment.

When the field operator detects a faulty component that is subjective to maintenance, the tag of the component is read or scanned with the PDA. A notification describing the upcoming maintenance operation is created on the PDA. This information is then transmitted via the wireless network into the ERP system.

As soon as the necessary confirmation is received, a work order is created. During the maintenance operation, the field operator can update the technical documentation online from his mobile device. As a finishing activity, a verification of the technical

condition of the component has to be performed. Verifying functionality usually requires that the operator is physically present in the field. When the verification is passed, the operator is able to remotely flag the status of the work order as finished using the PDA.

Also, for day-to-day operational tasks there is a large potential for improving and simplifying work tasks. A relevant example in the Oil & Gas industry is simplifying routine test procedures, e.g. periodic testing of fire & gas detectors.

2.2. Wireless sensing, monitoring and control

For wireless sensing, monitoring and control

applications, a growing number of industrial standards using the IEEE 802.15.4 [5] physical (PHY) and medium access control (MAC) layers are emerging.

The ZigBee specification [8], released in 2004 and updated in 2006, defines both a network and an application layer based on the IEEE 802.15.4 PHY and MAC. In October 2007, the ZigBee Alliance released the ZigBee PRO specification [9] which is aimed at the industrial market. It offers enhanced security features, a stochastic addressing scheme which allows for larger networks, and frequency agility which enables networks to change channels when faced with noise and interference.

WirelessHART, released in September 2007 as a part of the HART 7 specification [10], is the first open wireless communication standard specifically designed for industrial process and control applications. The WirelessHART specification uses the IEEE 802.15.4 PHY with a modified MAC-layer and implements frequency hopping in a multi-hop mesh network topology. Time Division Multiple Access (TDMA) is used for communication between network devices, specifying both which timeslot and frequency to use for each link.

The first standard to emerge from the forthcoming ISA100 family of wireless systems for industrial automation will be the ISA100.11a Release 1 [11], which will provide wireless connectivity for fixed, portable and moving devices for non-critical monitoring and control applications. Much like WirelessHART, the ISA100.11a will use the IEEE 802.15.4 PHY with a modified MAC-layer to provide a frequency hopping, multi-hop mesh network capable of inter-network routing. The ISA100.11a is expected to be ratified by Q3 2008.

For the Oil & Gas industry, it is expected that WSN technologies will enable wireless applications such as condition and performance monitoring, environmental monitoring, process control, emergency

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management, and tasks related to HSE. WSNs can also offer options not financially viable today, enabling installations of a temporary nature and in remote or hostile areas, as well as making it cost efficient to monitor more parameters for production optimization purposes.

2.3. Asset and personnel tracking

Keeping track of assets and personnel is becoming

more and more important in industrial facilities. There are different ways to achieve tracking and positioning within the coverage area of a wireless network. For WLAN’s, two different technologies for positioning has been examined in the TAIL IO project (a collaborative research project run by a consortium consisting of StatoilHydro, ABB, IBM, SKF and Aker Kvaerner).

The time difference of arrival principle (TDoA) is based on measuring time-of-flight between a field tag and a receiver station [12]. This concept requires special location receivers to be deployed into the existing WLAN. Tags transmit short beacons that are received by the location receivers. The location receivers are time-synchronized, and by detecting the difference in arrival times of the transmitted signal at each location receiver, the distance to the tag can be calculated. When the tag is within radio range of at least three location receivers, the principle of triangulation is applied for determining position.

Another approach for enabling positioning in an area which has WLAN coverage is by measuring Received Signal Strength, RSS [12]. Common to both time difference models and signal strength models are that they are based on deterministic equations describing physical laws. In general, these techniques do not account for dynamic environment-specific RF propagation effects such as multi-path, interference, noise and shading.

Adding environmental specific calibration to an RF propagation model is known as RF Fingerprinting [12]. RF Fingerprinting is a form of location patterning, where the goal is to adapt the propagation model to the local environment. The drawback of this approach is the need for individual calibration of each site, which is a time consuming manual task. Also, the calibration has to be repeated whenever major changes in the physical environment have occurred, or on a periodic basis to take into account naturally-occurring fluctuations in the propagation environment.

In the Oil & Gas industry, container tracking and personnel tracking in emergency situations are two good examples of interesting application areas for asset and personnel tracking.

2.4.1. Container tracking. In a typical process

plant, there are a large number of container movements during a normal operation cycle. Keeping track of the physical location of each container is in many situations considered a challenge, and requires extensive logistics. In addition, it is important to know the contents of each container. Keeping track of individual container positions along with container metadata is an application where wireless networks can improve efficiency.

To achieve this, each container has to be equipped with an electronic tag, serving as a unique ID. Before the container leaves its origin, the tag information must be updated. Using a centralized database, the tag ID can be linked with container specific data.

During transportation, the container passes several checkpoints within coverage of wireless networks, enabling tracking of the container on its way towards the destination. Events during transport, such as customs inspection, can be logged online and added into the central database.

When the container arrives at the plant, its presence is detected by the plant-wide wireless network. A field operator equipped with a mobile device, e.g. PDA or laptop computer, can access the metadata of the container by making a request to the central database.

As the container is moved around in the plant area, its physical position can be monitored by utilizing the positioning capabilities of the plant-wide WLAN. Typically, positioning data is linked with a map of the site, visualizing the position of the container in an intuitive way. When content is added or removed, the field operator can update the central database using a wireless mobile device.

In order for the concept of container tracking to be successful, a tight integration between the wireless network, the positioning application, the database server, user applications and mobile devices is required. In this respect, this concept is a layered software challenge.

2.4.2. Personnel tracking in emergency

situations. In an Oil & Gas offshore production plant, strict procedures apply in emergency situations. Every Oil & Gas facility is equipped with a large number of fire & gas detectors. If one or more detectors are triggered, an alarm goes off. Depending on the severity of the situation, the platform manager decides whether or not evacuation procedures should be initiated. In this case, the evacuation order is given through the plant’s public address system. All personnel are trained to muster at specific mustering stations.

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For an offshore facility, mustering stations are located close to the life-boat launch areas. To keep count of personnel arrived at these mustering stations, name lists have to be checked. Traditionally, this procedure has been carried out manually.

By equipping each individual with an RFID tag, and linking the tag ID with a database containing personnel data, counting people at the mustering station can be implemented as an automated process. When an RFID tag is within radio range of the backhaul wireless network at the life-boat area, its tag ID is read and linked with the personnel information in the database. Using this information, the user application generates name lists.

Furthermore, in the case of persons failing to muster at the mustering station, the tracking and positioning capabilities of the wireless network can be utilized. The evacuation system could track the location of the missing person, or at least achieve information about which area the RFID tag was last detected.

This scenario for personnel tracking in emergency situations can be enabled by an RFID system with active tags combined with wireless network coverage throughout the entire facility. In addition, as this is a safety critical application, there will probably be a need for full redundancy of all infrastructure components and the use of especially robust software.

3. Embedded software challenges

The different wireless embedded devices used in the previously identified application areas are listed in Table 2.

Table 2. Embedded devices

Application Area Devices Network access Access points

Mobile devices (PDA,PC) Sensing, monitoring and control

Sensors Gateways

Asset and personnel tracking

Location access points RFID tags

The most challenging environment for embedded

software can arguably be found on wireless sensors, which will be the main focus of the study performed in this section.

3.1. Introduction to wireless sensors

A typical wireless sensor consists of three main

parts; a sensing unit, a processing unit and a

communication unit (see Figure 2). In addition, it has components such as a power supply (battery), memory (RAM) and storage (flash).

Wireless Sensor

Sensing

Processing

Communication

Figure 2. Simplified wireless sensor

The sensing unit measures information about a

physical phenomenon and converts the measurements to a digital representation via an A/D-converter. The processing unit usually analyzes and processes the received digital data, as well as handles the network protocol and controls the local RF transceiver. The communication unit provides the wireless interface, and consists of an RF transceiver and an antenna.

Wireless sensors usually have very limited resources in terms of processing capacity, available memory and storage space due to strict low-power requirements. Yet, they are still required to execute software implementations of complex networking algorithms with real-time requirements. Wireless sensor networks (WSNs) have to be capable of self-healing and self-configuration in order to provide a robust and reliable multi-hop network for rough RF environments. This can be achieved by the use of dynamic routing protocols, where each wireless sensor has to store and constantly update neighbor information, as well as handling network connection requests from other wireless sensors.

3.2. WSN standards

Specifications for international standards for

wireless sensor networks, such as ZigBee PRO, WirelessHART and ISA100.11a, use stacks to provide a layered and abstract description of the network protocol design (see Figure 3).

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Figure 3. WSN stack

Each layer in the stack is a collection of related

functions, and a layer is responsible for providing services to the layer above it, while it receives services from the layer below it.

In a WSN stack, the Physical Layer (PHY) controls the RF transceiver, performs frequency and channel selection, handles energy and signal management functions, and provides means for transmitting raw bits (not packets).

The Medium Access Control Layer (MAC) handles access to the physical radio channel, is responsible for radio synchronization, and provides a reliable link between two peer MAC entities.

The Network Layer is responsible for joining and leaving a network, it provides end-to-end packet delivery from source to destination, and it discovers and maintains routing tables.

The Application Layer provides services to user-defined application processes (not necessarily to the end-user), it handles fragmentation and reassembly of data packets, and it defines the role of the device within the network (coordinator, router or end-device).

Even though a stack, through all its layers, defines and describes the functionality and operation of a wireless device for a given standard, it does not provide any guidelines on how to develop and implement the embedded software needed in order to realize the protocols described in the standard specifications. As a result, creating software stacks for international standards has become a major challenge. Not only will the software stack have to implement complex network protocols with real-time requirements in an embedded environment with scarce resources, it also has to fulfill the requirement of guaranteed interoperability between the devices – and the software stacks – from different vendors. This challenge has to be overcome if any of the

aforementioned emerging international standards are to become a viable option for industrial wireless sensor networks.

As an example, the now well established and widespread standard for personal area networks, Bluetooth [13], suffered from lack of interoperability between devices from vendors in its early years. This was caused by differences in implementation of the Bluetooth software stack from different manufacturers.

In addition to the general challenges related to

developing software stacks for international standards, different layers have unique software challenges of their own, which will be addressed in the following sections.

3.3. WSN Physical and MAC layers

For industrial WSNs to be a viable option for

sensing, monitoring and control in the Oil & Gas industry, it is important to keep the power consumption as low as possible in order to ensure that the wireless sensors have a sufficiently long battery lifetime.

The major source of power consumption in a wireless sensor is the communication unit (ref. Figure 2), mainly the RF transceiver when transmitting and receiving data.

To conserve power, it is therefore imperative to be able to shut down the transceiver when it is not in use. The ability to shut down the transceiver can also be beneficial for the power consumption of the processing unit, as in many cases, the microprocessor can enter low-power sleep modes when there is no need for communication.

However, as the power consumption when starting up the transceiver is much higher than in use, for wireless sensors using short data packets, the average power consumption might actually be larger by turning the unit on and off, instead of leaving it on all the time [14]. Operation in low-power modes is in other words only beneficial if the time spent in the mode is greater than a certain threshold. This threshold time depends on the transition times and of the power consumption of the wireless device itself.

Support for this power-saving functionality must also be enabled by the MAC layer. In industrial WSNs a common method to achieve this is to synchronize the network with a time-division multiple access (TDMA) algorithm. All network communication is divided into distinct timeslots of equal length. A timeslot is usually so long as to allow enough time for a device to transmit one packet and wait for the reception an acknowledgement (ACK) from the recipient. A group

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of such timeslots is called a frame, and the frame is repeated periodically throughout the network lifetime. The TDMA concept is illustrated in Figure 4.

Figure 4. TDMA frame format

Each communication link between two devices in

the network is given their own unique timeslot, thus enabling contention-free communication throughout the network, and enabling each device to enter a low-power sleep mode with its transceiver turned off in all the timeslots not reserved for its own links.

A weakness with this form of division of network traffic is its inability to scale in an efficient manner. A large increase in the number of node in the network leads to requirement for a high number of timeslots in the frame, which in turn leads to high latency. To combat this, hybrid TDMA algorithms can be used, where a certain number of timeslots in the frame is not dedicated to a given communication link, but open to free contention between the devices in the network. A pure TDMA solution is employed by WirelessHART, while ISA100.11a utilizes a hybrid TDMA algorithm.

These solutions for enabling efficient power management compose a challenge for the software running on the microprocessor on wireless sensors. First of all, the processor must be able to enter and leave low-power sleep modes when needed, and within strict timing regulations. An interrupt driven regime or precise operating system functionality is needed to achieve this. In addition, to be able to fully utilize the benefits from this low-power operation, the processing of sensor data and the handling of network traffic must be performed as efficient and fast as possible on a platform with scarce available resources for executing such tasks.

3.4. WSN network layer

Industrial WSNs have strict requirements regarding

the availability, stability and reliability of the network. Stable and reliable performance can be achieved by using self-organizing, self-healing and self-configuring multi-hop, ad-hoc networks. The main challenge with

such networks is routing, which is exacerbated by a time-varying network topology, power constraints, and the characteristics of the wireless channel.

In order to achieve approximately 100 % data reliability in a WSN, the network has to be capable of dealing with the temporary or permanent loss of any communication link in the network. For wireless communication, the performance can be affected by changes in the RF environment due to noise, interference, jamming, temperature variations or the introduction of personnel or equipment in the physical area. To combat these threats, redundant paths are created and maintained in routing tables on each device in the network, such that alternate routes are available should one or more of the communication links fail. This re-routing of traffic can also be used to handle temporary or permanent decrease in the quality of a communication link between two devices in the network, so that latency and stability issues from retransmissions of lost data packets can be avoided.

The software implementation of these mechanisms are a major challenge, as they have strict real-time requirements, and the embedded environment on which they reside usually consists of low-power microprocessors with low CPU speed and little available memory and storage.

3.5. WSN middleware

Middleware is traditionally used as a bridge

between the operating system (and similar low-level constructs) and the application, easing the development of distributed applications [20]. As WSNs exert many of the same properties as conventional distributed systems, distributed computing middleware is naturally considered for use in sensor networks.

However, common middleware systems for traditional distributed systems, such as Corba [15], and the IndustrialIT [16] framework developed by ABB specifically for distributed industrial systems, are not capable of supporting the dynamic and adaptive environment found in WSN systems. This has lead to the research and development of middleware specifically designed to meet the challenges of resource-constrained WSNs. These challenges are dictated by the WSN characteristics on the one hand, and by the application on the other. A survey performed in [17], identifies the following challenging areas for WSN middleware:

• Managing limited power and resources

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• Scalability, mobility and dynamic network topology

• Heterogeneity • Dynamic network organization • Real-word integration • Application knowledge • Data aggregation • Quality of Service • Security Early WSN specific middleware, such as Autosec

[18] and Impala [19], are designed for efficient use of the wireless sensor network, but they do not consider the properties of the network itself. They are thus not able to change the network properties in order to save energy, and they are not flexible enough to support different protocol stacks or different QoS (Quality of Service) requirements from different applications.

Recent research, such as the development of the MiLAN middleware for WSNs [20], concludes that while conventional middleware operates above the network layer, for WSN applications it is not a viable approach to handle the network management independent of the needs of the application. By integrating these two aspects into a single unified middleware system, the middleware can trade application performance for network cost, while still maintaining the separation between the policy specifying the reaction to a dynamic environment and the mechanisms to implement such as policy.

4. User application challenges

The software challenges regarding the user

applications for wireless technology falls into two categories, namely the user interfaces for configuring, monitoring and controlling the wireless system itself, and the user applications into which the wireless technology is deployed. For the latter, unless it is a new application, the wireless system will have to be integrated into an existing network infrastructure and existing user applications.

4.1. User interfaces for wireless technology

All wireless systems need to be configured,

monitored and controlled throughout its entire lifetime. In an Oil & Gas facility, it is desirable that these tasks can be performed by personnel who often posses neither understanding nor knowledge of the underlying wireless technology. If this is not the case, one would have to rely on technical experts to be brought on-site whenever parameters of the wireless systems have to

be altered, or technical problems have arisen. This is both expensive and time consuming, and in situations where a problem with a wireless system theoretically can lead to a production stop or a facility shut down, the delay of having to transport a technical expert on-site is simply not an option. This is especially important for offshore facilities.

As a consequence, the user interfaces for wireless systems must be able to provide a simple and intuitive interface for advanced configuration, control and management. Creating such applications is a challenge, and it requires the software developers not only to have extensive expertise of the wireless systems, but also to understand the psychological phenomena behind the art of creating good user interfaces.

4.2. Wireless technology integration

Certain wireless technologies, such as WSNs, do

not enable new applications, but bring enhancements to already existing applications. The new wireless systems are then required to be seamlessly integrated into the existing systems, regarding both IT infrastructure and software applications. For example, when introducing wireless sensors in a facility, it should be transparent to the operator whether or not the sensors in the system are wired or wireless.

Studies performed in [7] shows that the required changes in factory and plant work processes might be the largest hindrance for the introduction of wireless technology in the Oil & Gas industry. A typical problem when exploring new technology areas is to overlook the human factors in the adoption of the technology.

5. Conclusion

In this paper, a survey of the layered software

challenges related to the introduction of wireless technology in the Oil & Gas industry has been presented. Most of these challenges are related to wireless sensor networks with the implementation and execution of software stacks for complex network protocols with real-time requirements on embedded platforms with limited available resources. In addition, there are challenges related to the user applications, both for the user interfaces of the wireless systems themselves, and for the integration of wireless systems with existing IT infrastructure and applications.

We suggest that further work should be to conduct research into the challenges related to the many layers of software for wireless technology in the Oil & Gas industry. Specifically, this could be the development of

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energy-aware software stacks for the new industrial WSN standards, the design and implementation of a middleware specifically designed for the needs of industrial WSNs, optimal design of simple and intuitive user interfaces for the monitoring and control of wireless systems and the creation of a common methodology and system for integration of wireless technology into existing industrial IT infrastructure.

Wireless technologies as such are fit for deployment, and can provide benefits such as reduced costs or increased production, but without a proper study on how they can be incorporated into existing work processes; these benefits will not be fully realized.

6. References

[1] IEEE Computer Society, “IEEE 802.11-1999: Wireless

LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications”, Standard, July 1999.

[2] IEEE Computer Society, “IEEE 802.11a-1999: High-speed Physical Layer in the 5 GHz Band”, Standard, Feb. 1999.

[3] IEEE Computer Society, “IEEE 802.11b-1999: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications: Higher-Speed Physical Layer Extension in the 2.4 GHz Band”, Standard, Oct. 1999.

[4] IEEE Computer Society, “IEEE 802.11g-2003: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications: Further Higher Data Rate Extension in the 2.4 GHz Band”, Standard, June 2003.

[5] IEEE Computer Society, “IEEE 802.15.4-2006: Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (LR_WPANs)”, Standard, Dec. 2006.

[6] Petersen, S., et al., “Requirements, Drivers and Analysis of Wireless Sensor Networks for the Oil & Gas Industry”, Proceedings of the 12th IEEE International Conference on Emerging Technologies and Factory Automation, 25-28 Sept. 2007, pp 219-226.

[7] Petersen, S., et al., “A Survey of Wireless Technology for the Oil & Gas Industry”, Proceedings of the SPE Intelligent Energy Conference, 25-27 Feb. 2008.

[8] ZigBee Alliance, “ZigBee-2006 Specification”, Standard, Dec. 2006.

[9] ZigBee Alliance, “ZigBee PRO Specification”, Standard, Oct. 2007.

[10] HART Communication Foundation, “HART Field Communication Protocol Specification, Revision 7.0”, Standard, Sept. 2007.

[11] ISA100 Standards Committee, “ISA100.11a, Release 1 – An Update on the First Wireless Standard Emerging from the Industry for the Industry”, ISA EXPO 2007, Oct. 2007.

[12] Cisco Systems, “Wi-Fi Location-Based Services – Design and Deployment Considerations”, White Paper, 2006.

[13] Bluetooth SIG, “Bluetooth Specification, Version 2.1 + EDR”, Standard, July 2007.

[14] Akyildiz, I. F., et al.,”A Survey of Sensor Networks”, IEEE Communications Magazine, Aug. 2002, pp 102-114.

[15] OMG, “Common Object Request Broker Architecture: Core Specification”, Version 3.0.3, March 2004.

[16] Bratthall, L.G., et al., “Integrating Hundred’s of Products through One Architecture – The Industrial IT Architecture”, Proceedings of the 24th International Conferenceon Software Engineering, May 2002, pp 604-614.

[17] Hadim, S., and Mohamed, N., “Middleware Challenges and Approaches for Wireless Sensor Networks”, IEEE Distributed Systems Online, vol. 7, no. 3, 2006.

[18] Han, Q., and Venkatasubramanian, N., “Autosec: An Integrated Middleware Framework for Dynamic Service Brokering”, IEEE Distributed Systems Online, Vol. 2, no. 7, 2001.

[19] Liu, T., and Martonosi, M., “Impala: A Middleware System for Managing Autonomic, Parallel Sensor Systems”, ACM SIGPLAN Symp. Principles and Practice of Parallel Programming, June 2003.

[20] Heinzelman, W. B., Murphy, A. L., Carvalho, H. S., and Perillo, M. A., “Middleware to Support Sensor Network Applications”, IEEE Network, Jan./Feb. 2004, pp 6-14.

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Stig Petersen (M.Sc) is a Research Scientist with SINTEF ICT / Dept. of Communication Systems, Norway, has worked as a Research Scientist at SINTEF ICT in Trondheim, Norway since 2002, within the area of wireless communication, both standardized (Bluetooth, IEEE 802.11a/b/g, IEEE 802.15.4) and custom-made solutions. His work has ranged from implementing Medium Access Control and network protocols in microcontrollers on embedded platforms, to creating Windows and Linux based control and user applications. Recently, he has focused on the field of wireless communication within the confines of the Oil & Gas industry. This work has included theoretical assessments of both current and forthcoming international standards (IEEE 802.11a/b/g, IEEE 802.15.4, WirelessHART), as well as practical analysis and measurements of proprietary state-of-the-art wireless solutions.

Simon Carlsen is working as a Systems Engineer in the field of Industrial IT in StatoilHydro. His work fields cover wireless communication, sensor technology and real-time data acquisition. He has been working on standardizing Wireless LAN solutions in StatoilHydro’s Oil & Gas production environments, as well as examining different wireless protocols and implementations of wireless sensor technologies. During the last year Simon Carlsen has currently focused on wireless sensor networks (IEEE 802.15.4, WirelessHART, IEEE 802.11 b/g/a) as a member of an experts group working on wireless sensor technology for the Oil & Gas industry.

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