MAC SCHEDULING IN INDUSTRIAL
WIRELESS CELL-BASED MESH SENSOR
NETWORKS
Imran Yousaf
Master’s Degree Thesis 2011
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MAC SCHEDULING IN INDUSTRIAL
WIRELESS CELL-BASED MESH SENSOR
NETWORKS
Imran Yousaf
This thesis work has been carried out at the School of Engineering, Jönköping University within the subject area of embedded systems. The work is a part of the Master programme in Electrical Engineering.
The author takes full responsibility for opinions, conclusions and findings presented.
Examiner: Youzhi Xu Supervisor: Youzhi Xu
Scope: 30 credits (second cycle) Date: December 07, 2011
Abstract
Undergoing developments for the adaptation of Wireless Sensor Networks (WSNs) in automation industry is creating several research questions. The usage of wireless technologies in industrial environments requires real-time reliability and security. Many standards for WSNs and Industrial Wireless Sensor Networks (IWSNs) have been developed. The list includes WirelessHART [4], ISA100.11a [10], Zigbee [16], IEEE 802.15.4, and IEEE 802.15.4a etc.
Recently a new network topology “Cell-Based Mesh Networks” [12] has been developed in an effort to make IWSNs feasible for large scale deployments in process automation industries. Cell-Based Mesh Network topology inherits the qualities of star-mesh topology and mesh topology, and also offers many additional features. Reliability of an IWSN significantly depends on the real-time scheduling of the network. During this thesis work a scheduling mechanism has been developed by exploiting the features of a Cell-based Mesh Network. The idea of superframes’ further partitioning into cells of 100ms duration is presented, these 100ms time-cells guarantees interlocking data transmission [9] within 100ms. The closed loop control data [9] transmission is guaranteed by assigning dedicated time-slots. The performance evaluation of the presented scheduling mechanism is done by considering two case studies i.e. oil-industry and paper & pulp industry.
Keywords
Wireless Sensor Networks (WSN)
Industrial Wireless Sensor Networks (IWSN) Wireless Sensor and Actuator Networks (WSAN) WirelessHART
Cell-Based Mesh Networks MAC Scheduling Algorithms Real-time scheduling for IWSN Network Topologies for WSNs MAC Scheduling in WirelessHART
Acknowledgements
First of all, I would like to thank Allah almighty for all his blessings that he bestows on us.
I would like to thank my supervisor Prof. Youzhi Xu, he has been very encouraging and helpful for me during the whole thesis work. I really liked the way he explains the research problems and involves the student in such a way that he can easily come up with new ideas and innovations.
I would also like to thank our programme coordinator Alf Johansson for his guidance and encouragement throughout the master programme and to all my teachers who have given me invaluable knowledge during this master programme and to all my colleagues.
Finally, I would like to thank my parents and family for their prayers, support, and love throughout my whole life.
Contents
Abstract ... iii
Keywords ... iv
Acknowledgements ... v
Contents ... vi
List of Abbreviations ... viii
1
Introduction ... 1
1.1 WIRELESS SENSOR NETWORKS ... 1
1.2 INDUSTRIAL WIRELESS SENSOR NETWORKS ... 2
1.3 THESIS OBJECTIVES AND TASKS ... 3
1.4 THESIS STRUCTURE ... 3
2
Background ... 4
2.1 CELL-BASED MESH NETWORKS ... 4
2.2 WIRELESSHARTPROTOCOL ... 5
2.3 SCHEDULING IN WIRELESSHART... 10
2.3.1 Location of Scheduling Algorithm in WirelessHART ... 10
2.3.2 Requirements for Scheduling ... 10
2.3.3 Performance Measurers for MAC Scheduling Algorithms ... 11
2.4 STATE-OF-THE-ART SCHEDULING MECHANISMS ... 11
2.4.1 Optimal Branch-and-Bound (B&B) Scheduling ... 11
2.4.2 Conflict-aware Least Laxity First (C-LLF) Scheduling ... 12
2.4.3 Communication Schedule Defined in [1] ... 12
3
Design and Implementation ... 14
3.1 PROBLEM FORMULATION ... 14
3.1.1 Payload ... 14
Monitoring and Supervision ... 14
Closed Loop Control ... 14
Interlocking ... 15 Network Management ... 15 3.1.2 Network Topology ... 15 3.1.3 Superframe ... 15 3.1.4 Scheduling ... 16 Time-Slots ... 16 Dedicated ... 16 Shared ... 16 Reserved... 16 Unused ... 16 3.2 SCHEDULING ALGORITHM ... 16 3.2.1 Flow Diagram ... 19 3.3 IMPLEMENTATION... 21
4
Performance Evaluation ... 24
4.1 CASE-1:OIL INDUSTRY ... 244.1.1 Schedule for Cell-1 ... 27
4.1.2 Schedule for Cell-2 ... 29
4.2 CASE-2:PAPER AND PULP INDUSTRY ... 32
4.2.1 Schedule for Cell-1 ... 35
4.2.2 Schedule for Cell-2 ... 37
5
Conclusions and Future Work ... 41
5.1 CONCLUSION ... 41
5.2 FUTURE WORK ... 41
6
References ... 42
7
Appendices ... 44
7.1 APPENDIX ASTATE-OF-THE-ART NETWORK TOPOLOGIES ... 44
7.1.1 Star Topology ... 44
7.1.2 Mesh Topology ... 44
7.1.3 Star-Mesh Topology ... 44
7.1.4 Hub-and-Spoke Topology ... 45
List of Abbreviations
WSN Wireless Sensor NetworkIWSN Industrial Wireless Sensor Network
HART Highway Addressable Remote Transducer Protocol
DLL Data Link Layer
B&B Optimal Branch-and-Bound Scheduling C-LLF Conflict-aware Least Laxity First TDMA Time Division Multiple Access MAC Media Access Control
ASN Absolution Slot Number
DSSS Direct Sequence Spread Spectrum
ISM Industrial, Scientific, and Medical radio bands OSI Open Systems Interconnection
1 Introduction
The developments in wireless communication technologies have proven to be part of various aspects of automation that include buildings, home, shipboard, transportation systems, industry etc. Every environment has various distinct requirements for the deployment of a wireless communication system e.g. for a temperature control system in a building, the coverage area should be large in contrast to an industrial process control system where the timing requirements are stringent though coverage area can also be large in this case but not so important. Such wireless communication has been made possible with the help of wireless sensor networks (WSNs). Research and development at a large scale is undergoing to take this evolutionary step in the area of automation. Many WSN standards have been developed though there are still lots of research problems that need to be solved since WSNs are targeting a wide range of environments.
This thesis work is related to industrial WSNs, that has stringent requirements for wireless communication. Recently a new network topology called ‘Cell-Based Mesh Networks’ [12] has been developed for industrial WSNs. In this thesis report a mac layer scheduling mechanism for Industrial Wireless Cell-Based Mesh Networks has been proposed.
1.1 Wireless Sensor Networks
A wireless sensor network (WSN) consists of spatially distributed autonomous sensors to monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants and to cooperatively pass their data through the network to a main location [8]. Each of the sensor nodes of a WSN is equipped with a radio transceiver, a small microprocessor and a number of sensors. The sensor nodes are capable of forming the network autonomously and wirelessly communicate with a central control, the data transmission can be in either direction. An abstract picture of a WSN is shown in Fig 1.1a.
Wireless sensor networks are bringing a revolutionary change in a wide variety of application areas. These areas include;
Environmental monitoring Healthcare
Critical industrial areas Warehouse and supply chain Military surveillance
Building automation etc.
Let’s take the example of environmental monitoring; a WSN can be deployed in a forest that has caught fire, to monitor the further consequences and temperature in the surroundings. The deployment can be done via an airplane since the sensor nodes are autonomous so these will create a network autonomously and transmit data to the central control to help the fire fighters to cope with the situation in a more efficient way.
1.2 Industrial Wireless Sensor Networks
An industrial wireless sensor network can be defined as a WSN that can fulfil stringent requirements on security and real-time reliability. Mostly the IWSNs are centrally controlled and the dominate data traffic is sensed data from sensors to the central control and actuation data to the actuators from the central control. A typical industrial wireless sensor network is depicted in Fig 1.2a.
Figure 1.2a A typical Industrial Wireless Sensor Network [4]
These days, developments are on the go to make large scale deployment of wireless communication technologies possible in industrial environments. Recently new
standards have been developed that are particularly targeting industrial automation domain, these include WirelessHART [4], ISA 100.11a [10] etc.
1.3 Thesis Objectives and Tasks
The main objective of this thesis project is to design and implement a feasible scheduling algorithm/mechanism for Industrial Wireless Cell-Based Mesh Networks. Although, the target IWSNs can be based on WirelessHART, ISA-100 or other similar standards based on IEEE 802.15.4 but in this thesis work we will stick to the WirelessHART standard for design and implementation details. More precisely WirelessHART standard will be leveraged by cell-based mesh network topology for network routing and for communication scheduling a feasible mechanism will be proposed. Performance evaluation of the proposed scheduling algorithm will be for one cell of a cell-based mesh network, the complete network’s performance evaluation is out of scope of this thesis work.
1.4 Thesis Structure
The remainder of this thesis has been structured as follows. In Chapter 2, the significance of scheduling in WSNs will be described by introducing Cell-Based Mesh Networks and taking the case of WirelessHART protocol for scheduling. The design and implementation of the proposed scheduling algorithm is described in Chapter 3 and the performance evaluation is done in Chapter 4. The thesis report is concluded in Chapter 5, some possible future work related to this project is also given there.
2 Background
This chapter is meant for describing the significance of scheduling in WSNs. Firstly, Cell-Based Mesh Networks and WirelessHART protocol are introduced, and then the significance of communication schedule in WirelessHART and State-Of-The-Art Scheduling Mechanisms are given in this chapter.
2.1 Cell-Based Mesh Networks
State-of-the-art network topologies1 for IWSNs include star topology, mesh topology, star-mesh topology, and hub-and-spoke topology, but IWSNs require a more suitable network topology that can fulfil the stringent requirements of IWSNs that include security, reliability, real-time, and low power consumption. Mostly the IWSNs are centrally controlled and the dominate data traffic is sensed data from sensors to the central control and actuation to the actuators from the central control. Cell-based mesh network topology has been developed to provide a feasible solution for IWSNs.
Figure 2.1a A Cell-Based Mesh Network
The basic architecture of a Cell-based mesh network is depicted in Fig 2.1a. Its basic elements include field devices, backbone routers, a gateway, a security manager, and a network manager. The network is built up by linking multiple cells or clusters via backbone to the network manager. Each cell has a backbone router that works as cluster head, responsible for providing basic links to each field device with few hops one or two and maximally 3 hops in the cell. Redundant routes are also available in the form of intra-cell and inter-cell links [12]. Two frequency channels will be utilized by each cell.
By inheriting the properties of a multiple-star-clusters network and a mesh network, a cell-based mesh network provides a solution with significant improvements. The main advantageous properties [12] are as follows:
i. High network reliability
1
ii. Reduced retry times
iii. Improved network size and scalability iv. Low latency
v. Simplicity
vi. High time synchronization accuracy vii. High failure tolerance
2.2 WirelessHART Protocol
WirelessHART protocol is part of the HART 7 (www.hartcomm.org) standard. HART was developed in the late 80’s. Initially HART communications protocol offered a simple two-communications by using 4-20mA signals. After more than two decades HART has evolved from its simple two-communication capability to the wired and wireless communication capabilities with extensive features that includes security, unsolicited data transfers, event notifications, block mode transfers, and advanced diagnostics. The evolution of HART standard is depicted in Fig 2.2a. The most recent version of HART standard is version 7 or simply HART 7. Along with many other new features HART 7 introduced wireless mesh networking in the form of WirelessHART communication protocol.
Figure 2.2a Evolution of HART standard [3]
WirelessHARTTM protocol is designed for communication within Wireless Sensor Networks (WSNs). The main target markets for WirelessHART communication protocol are real-time process measurement and control applications. WirelessHART is the first global wireless communication standard approved by IEC [4] which claims to provide simple, reliable, and secure communication. A typical WirelessHART based network is shown in Fig 2.2b. In addition to wireless communication capability, WirelessHART also offers all the capabilities of the wired HART protocol.
Figure 2.2b A typical WirelessHART network [1]
The architecture of HART protocol is shown in Fig 2.2c in comparison to the OSI model. The architecture of the WirelessHART protocol can be seen in the right side of Fig 2.2c, since it is a part of HART protocol.
The physical layer of WirelessHART protocol is based on the IEEE 802.15.4-2006
2.4GHz DSSS physical layer. The WirelessHART protocol operates in the 2400-2483.5MHz license-free ISM band with a data rate of up to 250 Kbits/s. Two adjacent channels in WirelessHART have 5MHz gap, and the channels are numbered from 11 to 26 [18].
The data link layer of WirelessHART is not compatible with IEEE 802.15.4-2006
DLL, rather it defines its own time-synchronized DLL. WirelessHART defines a strict 10ms time-slot and utilizes TDMA technology to provide collision free and deterministic communications [17]. The concept of superframe is introduced to group a sequence of consecutive time slots. Note a superframe is periodical, with the total length of the member slots as the period. All superframes in a WirelessHART network start from the ASN (absolution slot number) 0, the time when the network is
first created. Each superframe then repeats itself along the time based on its period. In WirelessHART, a transaction in a time slot is described by a vector:
{frame id, index, type, src addr, dst addr, channel offset}
Figure 2.2c The architecture of HART communication protocol [1]
where frame id identifies the specific superframe; index is the index of the slot in the superframe; type indicates the type of the slot (transmit/receive/idle); src addr and dst
addr are the addresses of the source device and destination device, respectively; channel offset provides the logical channel to be used in the transaction. To fine-tune
the channel usage, WirelessHART introduces the idea of channel blacklisting. Channels affected Figure 2. WirelessHART Data Link Layer Architecture by consistent interferences could be put in the black list. In this way, the network administrator can disable the use of those channels in the black list totally. To support channel hopping, each device maintains an active channel table. Due to channel blacklisting, the table may have less than 16 entries. For a given slot and channel offset, the actual channel is determined from the formula:
ActualChannel = (ChannelOffset + ASN) % NumChannels
The actual channel number is used as an index into the active channel table to get the physical channel number. Since the ASN is increasing constantly, the same channel offset may be mapped to different physical channels in different slots. This shows that WirelessHART offers channel diversity and enhanced communication reliability. Along with strict 10 ms timeslot, network-wide time synchronization, channel hopping, channel blacklisting, WirelessHART DLL also offers industry-standard AES-128 ciphers and keys.
The architecture of WirelessHART DLL is shown in Fig 2.2d. The WirelessHART DLL has six major modules i.e.
Interfaces
The interfaces between layers are meant for providing service primitives to the corresponding higher layers e.g. the interface between the MAC and physical layer defines the service primitives provided by the physical layer.
Timer
Timer is a fundamental module in the WirelessHART standard since WirelessHART offers centralized network control/management. Its main purpose is to keep those 10ms timeslots in synchronization.
Communication Tables
Each network device maintains a collection of tables in the data link layer. The information regarding the communication configurations and scheduling mechanism is kept in the superframe table and link table. The neighbor table is meant for keeping the list of neighbor nodes that the device can reach directly and the graph table is used to collaborate with the network layer and record routing information.
Figure 2.2d WirelessHART data link layer architecture [3]
Link Scheduler
The link scheduler is meant for determining the next timeslot to be serviced based on the schedule mechanism that is kept in the superframe table and link table. The scheduler is complicated by such factors as transaction priorities, the link changes, and the enabling and disabling of superframes. Every event that can affect link scheduling will cause the link schedule to be re-assessed.
The functionality of the message handling module is to buffer packets from the network layer and physical layer separately.
State Machine
The state machine in the data link layer consists of three primary components: the TDMA state machine, the XMIT and RECV engines. The TDMA state machine is meant for executing the transaction in a slot and synchronizing the timer clock. The XMIT and RECV engines deal with the hardware directly, which send and receive packets over the transceiver [3].
The network layer and transport layer provide secure and reliable end-to-end
communication for network devices. The overall design of the network layer and transport layer is depicted in Fig 2.2e.
Figure 2.2e WirelessHART Network Layer [3]
The basic elements of a typical WirelessHART network include: Field Devices, Handhelds, a gateway and a network manager. WirelessHART is centrally controlled by the network manager. Network manager is responsible for configuring the network, scheduling and managing communication between WirelessHART devices. To support the mesh communication technology, Each WirelessHART device is required to be capable of forwarding packets on behalf of other devices since it is a requirement for mesh communication technology. There are three routing protocols defined in the WirelessHART standard i.e. source routing, graph routing, and superframe routing [3].
The application layer is the highest level layer in WirelessHART standard that
provides infrastructure for building applications for WirelessHART based networks. In the WirelessHART standard, the communication between the devices and gateway is based on commands and responses. The responsibilities of the application layer
include parsing the message content, extracting the command number, executing the specified command, and generating responses [3].
2.3 Scheduling in WirelessHART
Since the data link layer (DLL) in WirelessHART is time-synchronized. WirelessHART defines a strict 10ms time slot and utilizes TDMA technology to provide collision free and deterministic communications. Transactions happen in these 10ms time slots which are further divided as depicted in Fig 2.3a, each division of the 10ms timeslot is used for a specific purpose. Infrastructure for time-synchronization is defined in the WirelessHART standard but it is not defined that which device should do the transaction in which time slot through which communication channel? Thus a schedule (or scheduling algorithm) is required to assign time slots of a communication channel for particular transactions for particular devices.
Figure 2.3a WirelessHART slot timing
2.3.1 Location of Scheduling Algorithm in WirelessHART
The main scheduling algorithm resides in the network manager by using which the network manager defines schedules. These schedules are broadcasted to the field devices by using control and configuration messages. Field devices maintain these schedules using link tables and superframe tables.
2.3.2 Requirements for Scheduling
The construction of the communication schedule is subject to several practical constraints in WirelessHART networks [1]:
The maximum number of concurrent active channels is 16. Each device can only be scheduled to TX/RX once in a slot.
Multiple devices can compete to transmit to the same device simultaneously (in shared timeslot).
On a multi-hop path, early hops must be scheduled first.
The practical sample rates are defined as 2n sec (−2 ≤ n ≤ 9) from 250ms (2−2sec) to 8min and 32sec (29sec).
2.3.3 Performance Measurers for MAC Scheduling Algorithms
Different performance measures are defined in literature for evaluating MAC scheduling in WirelessHART mesh-networks. Some of these are:
Schedulable Ratio [2] Buffer Size [2]
Scheduling Success Ratio [1] Network Utilization [1] Power Consumption
Packet Loss Rate or Delivery Rate Throughput
Average and Maximum Delay Power Consumption
2.4 State-Of-The-Art Scheduling Mechanisms
There are various scheduling mechanisms developed for WirelessHART network that are given below, there might have also been developed other scheduling mechanisms for the same purpose but I could have found these up till August 2011.
Optimal Branch-and-Bound (B&B) Scheduling [2]
Conflict-aware Least Laxity First (C-LLF) Scheduling [2] Communication Schedules defined in [1]
Multihop multi-channel scheduling for wireless control in WirelessHART networks [5]
Deadline-constrained transmission scheduling and data evacuation in WirelessHART networks [6]
Optimal link scheduling and channel assignment for convergecast in linear WirelessHART networks [7]
In this report the first three scheduling mechanisms/algorithms will be described since these are the latest one and seem to be interesting but the details for any of the above mentioned scheduling mechanism can be seen in the given references.
2.4.1 Optimal Branch-and-Bound (B&B) Scheduling
The B&B scheduling algorithm exploits the necessary condition established in Theorem 2 (which states that for a set of flows F, let be the set of unscheduled transmissions at slot s. If these transmissions are schedulable, then
[2]) to effectively discard infeasible branches in the search space. The B&B scheduling algorithm guarantees to find a schedule whenever a feasible one exits that makes it optimal and complete. The algorithm made decision at every node by estimating an upper bound of the laxity of the schedule that the node
may lead to. The laxity of a packet is “its remaining time slots minus its remaining number of transmissions”, and the laxity of a schedule is “the minimum laxity among all packets”. According to Theorem 2, for transmissions to be scheduled on or after slot s, following is an upper bound (UB) of its schedule’s laxity:
(2.4a)
A global lower bound (LB) of schedule laxity 0 is maintained by the search. Two decisions are made i.e. unschedulable or may be schedulable by computing UB at a node (using Equation 2.4a). If UB < LB at a node, it is guaranteed that this node will not lead to any feasible schedule and, hence, is discarded without further consideration. And if UB LB, then this node may lead to a feasible solution and, hence, is expanded further. The algorithm terminates as soon as it finds a feasible complete schedule that meets all deadlines. If the original problem is infeasible, the algorithm will also terminate as soon as it determines that this is the case [2].
2.4.2 Conflict-aware Least Laxity First (C-LLF) Scheduling
Conflict-aware least laxity first (C-LLF) scheduling is suitable for dynamic environments where network topology changes frequently. In traditional Least Laxity First (LLF) have been developed without taking, conflicts between transmissions, into consideration and these are effective in end-to-end real-time scheduling over wired networks, but in WSNs e.g. in WirelessHART based networks transmission conflicts are highly expected that can easily decrease the effectiveness of the communication schedule. Moreover, different nodes experience different degree of conflicts as different nodes have different number of neighbors in a routing graph. The gateway and the nodes with high connectivity in the routing graph tend to experience significantly higher degrees of conflicts. Hence, scheduling algorithms for
WirelessHART networks must be cognizant of conflicts between transmissions [2].
Based on this key insight into the WirelessHART networks, an efficient scheduling policy called Conflict-aware Least Laxity First (C-LLF) have been developed. It uses
conflict-aware laxity of every released transmission as the decision variable. The conflict-aware laxity of a transmission is determined by considering the length of time
windows in which the transmission must be scheduled as well as the potential conflicts that the transmission may experience in these windows. That is, the approach combines LLF and the degree of conflicts associated with a transmission. Thus, it can schedule a transmission while the remaining ones are likely to retain the necessary condition established in Theorem 2 (which states that for a set of flows F, let be the set of unscheduled transmissions at slot s. If these transmissions are schedulable, then
[2]). Specifically, the algorithm identifies some critical time windows in which too many conflicting transmissions have to be scheduled, thereby determining the criticality of each released transmission. Criticality of a transmission is quantified by its conflict-aware laxity. Transmissions exhibiting lower conflict-aware laxity are assessed to be more critical. C-LLF gives the highest priority to the transmissions exhibiting lower conflict-aware laxity [2].
2.4.3 Communication Schedule Defined in [1]
This scheduling mechanism is based on the routing graphs that are defined in [1]. This scheduling technique allows multiple devices to compete for the retry links to the
same device, and split the traffic from one device among all its successors, thus reduces the bandwidth allocation on each of them. By designing the communication schedules on the successors so that their combination has the same communication pattern as the original device, the global communication schedule is then spliced into sub-schedules and distributed to the corresponding devices. These sub-schedules work together and guarantee that the periodic process/control data between devices and the Gateway can be forwarded through multi-hops in a timely manner.
The design philosophy for constructing this communication schedule is to spread out the channel usage in the network as much as possible and to apply the Fastest Sample Rate First policy1 (FSRF) to schedule the devices’ periodic publishing and control data.
1
3 Design and Implementation
It is clear that optimized scheduling plays a significant role in enhancing the reliability, network throughput, latency, and delay etc. of an IWSN but there is still need of actual industry requirements analysis more precisely what is currently required in the industry. Thus before designing the scheduling algorithm a detailed requirement analysis has also been carried out by mainly focussing on process automation industry.
Table 3a Typical Requirements for IWSNs in Process Automation Domain [9]
The process automation industry has mainly three types of data that need to be communicated over an IWSN i.e. monitoring and supervision, closed loop control, and interlocking and control. The wireless communication requirements for these data types are tabulated in Table 3a.
3.1 Problem Formulation
The scheduling problem is formulated by defining the following properties for an industrial wireless sensor network.
3.1.1 Payload
The payload of packets can contain four types of data i.e.
Monitoring and Supervision
For this type of data transmission, only sensors are involved and no actuators involved means that only uplink communication is expected. Monitoring and supervision sensors would be the 30% of the total number of sensor nodes. The update rate for these sensors would be greater or equal to 1 sec. Allowed data loss is 1 packet/sec and in case of data loss the allowed delay is 250ms or less. This type of data transmission has the lowest priority.
Closed Loop Control
For this type of data transmission both uplink and downlink communication is involved. These sensors and actuators would be the 70% of the total number of sensor nodes out of which 52% would be the sensors and 18% would be the actuators. The
update rate for these sensors would be greater or equal to 500ms. Allowed data loss delay is 250ms or less. This type of data transmission has the middle priority.
Interlocking
This type of data transmission would be event driven and would involve the closed loop control actuators. Allowed data loss delay is 100ms or less. This type of data transmission has the highest priority.
Network Management
In this data the information of network configuration and management is involved that will be broadcasted time to time as required by the network manager.
The properties of the above mentioned data types are summarized in Table 3.1a.
Table 3.1a Properties of IWSN Data Traffic
Data Type % of total Nodes
Sensors Actuators Update Frequency
Data Loss Delay Priority
Monitoring & Supervision 30 30% 0% 1 sec or greater 1 packet/sec 250 ms 4th Closed Loop Control 70 52% 18% 500 ms or greater very low 250 ms 3rd Interlocking - - 18% or less
event driven ideally no 100 ms 2nd
Network Management
100 82% 18% event driven - - 1st
3.1.2 Network Topology
Routing is done according to the Cell-based Mesh Network topology. A routing table would be available for building the schedule which contains routing details and link cost for each link. Update rate of each node is also appended in the routing table for the purpose of building the schedule. Several routing tables for different scenarios have been generated on the basis of experimentation and mathematical models of Cell-based Mesh Networks which are presented in [11]. Each cell will have one backbone router and it should have a maximum of 30 sensors nodes in total.
3.1.3 Superframe
Superframe is defined as a group of consecutive time-slots with a fixed period i.e. the total time taken by these slots. For instance in case of WirelessHART each time-slot is 10 ms long, so if we consider a superframe of 25 time-time-slots then the period of the superframe would be 250 ms.
3.1.4 Scheduling Time-Slots
In this scheduling solution four types of 10ms duration time-slots in the superframe are considered i.e.
Dedicated
These time-slots will be assigned for closed loop data transmission.
Shared
These time-slots will be assigned for monitoring & supervision data and retransmissions of closed loop data.
Reserved
These time-slots will be used for broadcast data and network management.
Unused
These time-slots can be assigned for inter-cell communication or for any other purpose.
3.2 Scheduling Algorithm
The scheduling is designed in such a way that it will always guaranty the periodic closed loop data transmissions and event-driven interlocking data transmissions; this is accomplished by defining reserved and shared time-slots with a period of 100ms. For instance if a data packet couldn’t reach its destination within the dedicated time-slot then the network manager can notify other nodes in the upcoming reserved time-slot of the superframe about the retransmission and a shared slot or an unused slot will be assigned for this retransmission; and in the event of interlocking first the network manager will notify all the nodes using the reserved slots and then notify the actuators in question using a reserved slot, a shared slot, or an unused slot within 100ms. It is assumed that each cell can use only two channels at the maximum and there would be four types of time-slots i.e. dedicated, shared, reserved, and unused. One superframe will be assigned to each channel in the cell and the period of each superframe would be the maximum update rate from the closed loop sensors. Thus each cell would have two superframes working at the same time. Following is given a scheduling algorithm that can be used to build a schedule for one cell; same procedure can be repeated for all the cells in the network. The steps of the algorithm are;
1. Find the maximum update rate out of the closed loop control sensors; this would be the period of the superframes.
2. Extract information of all the nodes related to one cell say Cell#01 from the routing table.
3. Take the first generation of sensors in the cell; these sensors are directly connected to the backbone router. This can be done using the routing table. 4. Initialize the first superframe with period that was found in step-1 by assigning
the first time-slot and one time-slot after every 90ms as reserved slot in the superframe. The reason for having these time-slots with a period of 100ms is to cope with the stringent requirement of the event-driven interlocking data transmission which must be transmitted within 100ms. These time-slots can also be used to notify for any retransmissions of closed loop data.
5. Assign two time slots after every reserved slot as shared slot in the superframe. Normally these shared slots will be used for monitoring and supervision data but in case of packet loss these can be assigned for retransmissions of closed loop data as required by the network manager. 6. After doing steps 4 and 5 we have actually created 100ms time-cells within the
superframe, and each time-cell contains reserved, dedicated, shared, and may also contain unused slots.
7. Assign dedicated time slots to the closed loop sensors according to rate monotonic priority assignment (Rate monotonic is used here because it is optimal [13] and static policy). Also assign dedicated time slots to the monitoring sensors that are in the route of closed loop sensors.
8. While assigning time-slots to the routing nodes make sure that each of its closed loop sensor child nodes is assigned one time-slot for transmission1 from the routing node to the backbone router or to the parent node in case of second superframe. In case of second superframe an additional time-slot to each closed loop sensor child node will also be assigned to complete the communication link up till first generation.
9. For more optimization, group the sensors and actuators that belong to closed loop control with same update rate. Assign time slots to the sensors first then to the actuators with the same update rate (here it is assumed that there is no delay for the control loop processing and transmission between backbone router (BR) and the network manager/gateway). In case of the control loop processing delay and BR – Gateway transmission delay; the actuators will be assigned at least two time slots after the sensors of the same update rate (in this way we can give room of 20ms for processing and BR – Gateway transmission).
R ES ER V ED SH A R ED SH A R ED R ES ER V ED SH A R ED SH A R ED R ESE R VE D SH A R ED SH A R ED R ESE R VE D SH A R ED SH A R ED FIRST SUPERFRAME SECOND SUPERFRAME
Figure 3.2a Basic structure of superframes in a cell
10. The first superframe is done.
1
The word transmission is used just for explaining purpose, the schedule is valid for both uplink as well as downlink communication.
11. Now take all the remaining generations of sensors in the cell, and initialize the second superframe by assigning two shared slots as done in the first superframe but the reserved slots will come just after the shared slots in this superframe. The reserved slots are assigned after the shared slots to make sure that a packet transmitted in a reserved slot of superframe can be transmitted to higher generations by a routing node of first generation using the reserved slot of second superframe within 100ms.
12. Repeat steps 6 – 9 to get the second superframe ready.
This scheduling mechanism is optimized for maximum 3 hops since in a Cell-based Mesh network the maximum number of hops in a cell is 3. This algorithm can be used to build schedule for more than 3 hops but the event-driven interlocking data transmissions would not be guaranteed within 100ms in that case. The basic structure of the two superframes in a cell is depicted in Fig 3.2a.
BR M2 A4 M5 S3 S6 S7 Generation 1 Generation 2 Generation 3 M8
Figure 3.2b The hierarchy of nodes in a cell
To analyze the above mentioned scheduling algorithm let’s take the example of a cell presented in Fig 3.2b. BR is the backbone router through which every node in the cell communicates with the network manager. M is for monitoring nodes, S is for closed loop sensor nodes, and A is for closed loop actuator nodes. In first superframe S3 will be allocated a dedicated time-slot, M8 will not be assigned dedicated time-slot since it’s a monitoring sensor but M2 will be assigned 3 time-slots since it has three closed loop control child nodes i.e. A4, S6, and S7. In the second superframe A4 will be assigned only one time-slot but M5 will be assigned four time-slots out of which two meant for transmissions from child nodes to M5 and two meant for transmissions from M5 to parent node i.e. M2.
3.3 Implementation
The implementation of the algorithm is done using LabVIEW [15] development environment. The application program for generating the schedule is based on a GUI. The GUI (top level VI1) reads the routing table from a .csv file, then generates the schedule by using the given scheduling algorithm and outputs the schedule in the form of two superframes. The GUI of the application is shown in Fig 3.3a.
1
Figure 3.3a GUI for Calculating the Schedule
The VI hierarchy of the GUI based application program is shown in Fig 3.3b. The VI hierarchy presents the dependencies of VIs among each other. The top level VI calls three subVIs, the first subVI reads the routing table from a given .csv file. The other two subVIs are meant for calculating the two superframes. The superframes are output in the form of 2-D arrays. Each row of the array defines one time-slot and the columns in the row have information about that particular time-slot. The first column is ‘slot type’, the second is ‘source node’, and the third is ‘destination node’. Six types of time-slots are defined within the scope of application program, i.e.
Unused = 0 (numeric representation) Reserved = 1
Shared = 2 Dedicated = 3
TxFailure = 4 (this time-slot can be used to keep track of transmission failures)
Figure 3.3b VI hierarchy of the GUI based Application Program
The application program has been tested by testing and analyzing each of its sub-part (SubVI). Superframes for two different cells were generated for testing purpose, and then analyzed by comparing with the proposed scheduling algorithm and the routing table and found no errors. Thus, this application program is reliable for doing the performance analysis of the proposed algorithm.
4 Performance Evaluation
The real-time scheduling problem for a WirelessHART network is NP-hard [2], so heuristic approach will be used to analyze the reliability of the proposed scheduling algorithm. Performance evaluation is done by considering two case studies from the industry. For each case study, first the details about the cells of the scenario in question are presented then the schedule is presented in tabular form. Afterwards the throughput is calculated using the following equation;
Throughput =
The transmission failure is predicted using Poisson process that is given by the following equation [14].
The value of is set to 0.25 for transmission failures.
4.1 Case-1: Oil Industry
In this case the area in question is in which there are 60 Sensor nodes in total. The area is further divided into two cells and each cell is covered by one backbone router i.e. BR1 and BR2 as shown in Fig 4.1a. Each cell will be utilizing two frequency channels. Normally each backbone router should be responsible for routing data of 30 sensor nodes.
Thus, most of the time each cell will have;
30% of 30 equals to 9 monitoring and supervision sensor nodes. 52% of 30 equals to 15 closed loop control sensor nodes.
18% of 30 equals to 6 closed loop actuator nodes.
The routing information for this scenario is given in Table 4.1a. The table header is pretty straight forward except ‘A, S, or M’ column, this is meant for describing the type of the sensor node i.e. A for closed loop actuators presented by numeric 1, S for closed loop sensors presented by numeric 2, and M for monitoring sensors presented by numeric 3 in the table.
Figure 4.1a Distribution of sensor nodes in Case-1 [11]
Table 4.1a Routing table for Case-1
Node# Cell # Direct
father Generation# A, S, or M Route cost Update Period (ms) 9 1 36 2 2 2 500 10 1 67 2 3 2 1000 11 2 46 2 2 2 500 12 1 36 2 2 2 500 13 1 1 1 2 1 500 14 1 67 2 2 2 500 15 2 57 2 3 2 1000 16 1 1 1 2 1.02 500 17 2 60 2 2 2 500 18 2 2 1 2 1 500 19 2 43 2 2 2 500 20 2 28 2 1 2 500 21 1 48 2 2 2 500 22 2 2 1 3 1.12 1000 23 1 13 2 2 2 500 24 2 2 1 3 1 1000 25 1 64 3 2 3 500 26 2 28 2 3 2 1000 27 2 57 2 1 2 500 28 2 2 1 3 1 1000 29 1 48 2 2 2 500 30 2 2 1 3 1 1000 31 1 62 2 2 2 500 32 2 60 2 2 2 500 33 2 46 2 2 2 500
34 1 67 2 1 2 500 35 2 50 2 2 2 500 36 1 1 1 2 1 500 37 1 36 2 3 2 1000 38 1 62 2 1 2 500 39 2 60 2 1 2 500 40 2 18 2 2 2 500 41 1 48 2 3 2 1000 42 2 2 1 1 1 500 43 2 2 1 2 1 500 44 1 1 1 2 1 500 45 1 1 1 3 1.29 1000 46 2 2 1 2 1 500 47 1 1 1 1 1 500 48 1 1 1 2 1 500 49 1 16 2 1 2.02 500 50 2 2 1 2 1 500 51 2 60 2 1 2 500 52 1 67 2 3 2 1000 53 2 22 2 3 2.12 1000 54 2 50 2 3 2 1000 55 1 62 2 1 2 500 56 1 13 2 3 2 1000 57 2 2 1 2 1 500 58 2 50 2 2 2 500 59 1 67 2 3 2 1000 60 2 2 1 2 1 500 61 1 16 2 3 2.02 1000 62 1 1 1 1 1 500 63 2 30 2 3 2 1000 64 1 36 2 2 2 500 65 2 28 2 2 2 500 66 1 36 2 2 2 500 67 1 1 1 3 1 1000 68 2 50 2 1 2 500
4.1.1 Schedule for Cell-1
A detailed picture of the links in Cell-1 is shown in Fig 4.1b. After having all the details about the Cell it’s time to build a schedule for it. The schedule is generated using the GUI application program described in the previous chapter.
Figure 4.1b The spanning tree of Cell-1 of Case-1 [11]
The schedule is for Cell-1 is presented in Table 4.1b in the form of two superframes. The first superframe will work in channel no. 1 and the second will work in channel no. 2 of the cell.
Table 4.1b Schedule for Cell-1
Slot No. SUPERFRAME 1 SUPERFRAME 2 Slot Type
Source Node Destination
Node
Slot Type
Source Node Destination
Node 1 1 0 0 3 9 36 2 2 0 0 2 0 0 3 2 0 0 2 0 0 4 3 44 1 1 0 0 5 3 13 1 3 12 36 6 3 13 1 3 14 67 7 3 16 1 3 21 48 8 3 16 1 3 23 13 9 3 36 1 3 29 48 10 3 36 1 3 31 62 11 1 0 0 3 34 67 12 2 0 0 2 0 0 13 2 0 0 2 0 0 14 3 47 1 1 0 0
15 3 36 1 3 38 62 16 3 36 1 3 49 16 17 3 36 1 3 55 62 18 3 36 1 3 25 64 19 3 48 1 3 64 36 20 3 48 1 3 64 36 21 1 0 0 3 66 36 22 2 0 0 2 0 0 23 2 0 0 2 0 0 24 5 0 0 1 0 0 25 3 48 1 0 0 0 26 3 62 1 0 0 0 27 3 62 1 0 0 0 28 3 62 1 0 0 0 29 3 62 1 0 0 0 30 3 67 1 0 0 0 31 1 0 0 0 0 0 32 2 0 0 2 0 0 33 2 0 0 2 0 0 34 5 0 0 1 0 0 35 3 67 1 0 0 0 36 0 0 0 0 0 0 37 0 0 0 0 0 0 38 0 0 0 0 0 0 39 0 0 0 0 0 0 40 0 0 0 0 0 0 41 1 0 0 0 0 0 42 2 0 0 2 0 0 43 2 0 0 2 0 0 44 5 0 0 1 0 0 45 0 0 0 0 0 0 46 0 0 0 0 0 0 47 0 0 0 0 0 0 48 0 0 0 0 0 0 49 0 0 0 0 0 0 50 0 0 0 0 0 0
The performance of the generated schedule can be analyzed from the plots presented in Fig 4.1c and Fig 4.2d. In Fig 4.1c the successful packet transmissions are plotted against required time-slots for these transmissions. In Fig 4.1d the Cell’s throughput is plotted against required time-slots for the successful transmissions.
Figure 4.1c Successfully Transmitted Packets in Cell-1 of Case-1
Figure 4.1d Throughput in Cell-1 of Case-1 4.1.2 Schedule for Cell-2
A detailed picture of the links in Cell-2 is shown in Fig 4.1e. The schedule for Cell-2 is given in Table 4.1c and the results are shown in Fig 4.1f and Fig 4.1g.
Figure 4.1e The spanning tree of Cell-2 in Case-1 [11]
Table 4.1c Schedule for Cell-2
Slot No. SUPERFRAME 1 SUPERFRAME 2 Slot Type
Source Node Destination
Node
Slot Type
Source Node Destination
Node 1 1 0 0 3 11 46 2 2 0 0 2 0 0 3 2 0 0 2 0 0 4 3 42 2 1 0 0 5 3 18 2 3 17 60 6 3 18 2 3 19 43 7 3 28 2 3 27 57 8 3 28 2 3 32 60 9 3 43 2 3 20 28 10 3 43 2 3 33 46 11 1 0 0 3 35 50 12 2 0 0 2 0 0 13 2 0 0 2 0 0 14 5 0 0 1 0 0 15 3 46 2 3 39 60 16 3 46 2 3 40 18 17 3 46 2 3 51 60 18 3 50 2 3 65 28
19 3 50 2 0 0 0 20 3 50 2 0 0 0 21 1 0 0 3 58 50 22 2 0 0 2 0 0 23 2 0 0 2 0 0 24 5 0 0 1 0 0 25 3 50 2 0 0 0 26 3 57 2 3 68 50 27 3 57 2 0 0 0 28 3 60 2 0 0 0 29 3 60 2 0 0 0 30 3 60 2 0 0 0 31 1 0 0 0 0 0 32 2 0 0 2 0 0 33 2 0 0 2 0 0 34 5 0 0 1 0 0 35 3 60 2 0 0 0 36 3 60 2 0 0 0 37 0 0 0 0 0 0 38 0 0 0 0 0 0 39 0 0 0 0 0 0 40 0 0 0 0 0 0 41 1 0 0 0 0 0 42 2 0 0 2 0 0 43 2 0 0 2 0 0 44 5 0 0 1 0 0 45 0 0 0 0 0 0 46 0 0 0 0 0 0 47 0 0 0 0 0 0 48 0 0 0 0 0 0 49 0 0 0 0 0 0 50 0 0 0 0 0 0
Figure 4.1f Successfully Transmitted Packets in Cell-2 of Case-1
Figure 4.1g Throughput in Cell-2 of Case-1
4.2 Case-2: Paper and Pulp Industry
In this case the area in question is in which there are 100 Sensor nodes in total. The area is further divided into three cells and each cell is covered by one backbone router i.e. BR1, BR2, and BR3 as shown in Fig 4.2a. Each cell will be utilizing two frequency channels. Normally each backbone router should be responsible for routing data of 30 sensor nodes but in this case Cell-1, Cell-2 and Cell-3 have 29, 42, and 29 nodes respectively. To focus on the results of the generated schedule, the schedule tables for each Cell in this case are given in Appendix B. For each cell first the distribution the nodes is depicted then result plots are shown.
The routing information for this scenario is given in Table 4.2a.
Figure 4.2a Distribution of sensor nodes in Case-2 [11]
Table 4.2a Routing table for Case-2
Node# Cell # Direct
father Generation# A, S, or M Route cost Update Period (ms) 9 2 17 2 2 2 500 10 1 104 2 2 2 500 11 3 90 2 2 2 500 12 2 91 2 3 2 1000 13 1 1 1 3 1 1000 14 3 71 3 3 3 1000 15 2 82 2 1 2 500 16 2 108 2 2 2 500 17 2 2 1 1 1 500 18 2 92 2 1 2 500 19 1 1 1 1 1 500 20 3 86 3 2 3 500 21 2 108 2 3 2 1000 22 1 19 2 3 2 1000 23 3 93 2 3 2 1000 24 2 2 1 2 1 500 25 1 19 2 2 2 500 26 2 100 2 2 2 500 27 2 57 2 3 2 1000 28 1 1 1 1 1 500 29 3 66 2 2 2.19 500 30 3 93 2 1 2 500 31 1 28 2 2 2 500
32 2 91 2 1 2 500 33 2 84 3 2 3 500 34 3 105 3 2 3 500 35 3 3 1 3 1 1000 36 1 1 1 2 1 500 37 1 52 2 3 2 1000 38 3 63 2 2 2 500 39 2 2 1 2 1 500 40 1 1 1 3 1 1000 41 2 108 2 3 2 1000 42 2 39 2 3 2 1000 43 1 19 2 1 2 500 44 1 36 2 3 2 1000 45 1 19 2 3 2 1000 46 1 19 2 2 2 500 47 1 13 2 2 2 500 48 2 91 2 2 2 500 49 1 104 2 1 2 500 50 1 62 2 2 2.07 500 51 2 103 3 2 3 500 52 1 1 1 3 1 1000 53 2 16 3 2 3 500 54 2 39 2 2 2 500 55 3 63 2 2 2 500 56 3 63 2 3 2.47 1000 57 2 2 1 3 1 1000 58 2 108 2 3 2 1000 59 3 93 2 2 2 500 60 2 2 1 2 1 500 61 2 91 2 2 2 500 62 1 1 1 2 1.07 500 63 3 3 1 2 1 500 64 1 94 2 3 2 1000 65 2 82 2 2 2 500 66 3 3 1 3 1.19 1000 67 1 13 2 2 2 500 68 3 78 2 2 2 500 69 1 52 2 1 2 500 70 3 90 2 3 2 1000 71 3 93 2 3 2 1000 72 2 82 2 2 2 500 73 1 104 2 2 2 500 74 1 13 2 3 2 1000 75 2 108 2 1 2 500
76 1 28 2 2 2 500 77 2 88 3 2 3 500 78 3 3 1 2 1 500 79 3 55 3 2 3 500 80 2 92 2 3 2 1000 81 2 108 2 2 2 500 82 2 2 1 2 1 500 83 3 106 2 1 2 500 84 2 82 2 2 2 500 85 2 15 3 3 3 1000 86 3 35 2 1 2 500 87 3 78 2 2 2 500 88 2 24 2 2 2 500 89 1 1 1 2 1.03 500 90 3 3 1 3 1 1000 91 2 2 1 2 1 500 92 2 2 1 3 1 1000 93 3 3 1 3 1 1000 94 1 1 1 2 1 500 95 2 91 2 3 2 1000 96 2 80 3 3 3 1000 97 3 106 2 1 2 500 98 3 106 2 2 2 500 99 2 57 2 2 2 500 100 2 2 1 1 1 500 101 3 93 2 2 2 500 102 1 19 2 2 2 500 103 2 91 2 1 2 500 104 1 1 1 2 1 500 105 3 93 2 1 2 500 106 3 3 1 2 1 500 107 2 91 2 2 2 500 108 2 2 1 3 1 1000
4.2.1 Schedule for Cell-1
A detailed picture of the links in Cell-1 is shown in Fig 4.2b and the results are shown in Fig 4.2c and Fig 4.2d.
Figure 4.2b The spanning tree of Cell-1 in Case-2 [11]
Figure 4.2d Throughput in Cell-1 of Case-2
4.2.2 Schedule for Cell-2
A detailed picture of the links in Cell-2 is shown in Fig 4.2e and the results are shown in Fig 4.2f and Fig 4.2g.
Figure 4.2f Successfully Transmitted Packets in Cell-2 of Case-2
4.2.3 Schedule for Cell-3
A detailed picture of the links in Cell-3 is shown in Fig 4.2h and the results are shown in Fig 4.1i and Fig 4.1j.
Figure 4.2h The spanning tree of Cell-3 in Case-2 [11]
Figure 4.2j Throughput in Cell-3 of Case-2
Throughput is around 0.8 for different number of transmissions in almost every cell of the presented case studies. Thus the proposed scheduling mechanism is suitable for these industrial scenarios. Interestingly it also worked fine when the number of nodes was 42 in Cell-2 of Case-2 and the successful packet transmissions crossed 400 by utilizing 600 time-slots.
5 Conclusions and Future Work
5.1 Conclusion
The results calculated in the previous chapter have proven that the proposed mechanism is workable for different industrial scenarios by keeping the prominent feature of transmitting interlocking data within 100ms. If we analyze the delays in the different cases, we will reach the point that the delay is always less than or equal to
maximum update period of the closed loop control data i.e. the period of the
superframes. Latency is also less than or equal to the period of superframes.
It has been concluded that the proposed scheduling algorithm should be adopted for the Cell-Based Mesh Networks, to have meet the stringent timing requirements of IWSNs.
5.2 Future Work
Dynamic simulations of the proposed scheduling algorithm would be a beneficial future work before experimenting it on a real-time test bed. Since both the Cell-Based Mesh Network topology and the scheduling mechanism for it, are recently developed, so it would be really handy if we develop a simulator that can do real-time simulations and also analyze dynamic behavior of the network.
I had given it a try during my thesis work to develop a basis for such simulator using National Instruments’ LabVIEW [15] development environment because using LabVIEW real-time, we can develop real-time applications that can run on a real-time target and the development time is considerably low as compared to other programming languages. A GUI has been designed in an effort to start working on it but due to shortage of time and more emphasis on developing a reliable scheduling mechanism, it could not be completed. The designed GUI is shown in Fig 5.2a.
Figure 5.2a GUI Design for a Simulator
These are some of the efforts towards achieving the actual goal i.e. to develop infrastructure for a reliable and secure Industrial Wireless Sensor Network.
6 References
[1] Song Han, Xiuming Zhu, Aloysius K. Mok, Deji Chen, Mark Nixon. “Reliable and Real-time Communication in Industrial Wireless Mesh Networks”. The University of Texas at Austin, Department of Computer Sciences. Report #TR-10-34 (regular tech report). October 7th, 2010.
[2] Abusayeed Saifulah, Chenyang Lu, You Xu, and Yixin Chen, “Real-time scheduling for WirelessHART networks”, in RTSS, 2010.
[3] Deji Chen, Mark Nixon, and Aloysius Mok. (2010) “WirelessHART™, Real-Time Mesh Network for Industrial Automation”, Springer. ISBN 978-1-4419-6046-7.
[4] “WirelessHART”,
http://www.hartcomm.org/protocol/wihart/wireless_technology.html (Acc. June 2011).
[5] Gabriella Fiore, Valeria Ercoli, Alf J. Isaksson, Krister Landernäs, and Maria Domenica Di Benedetto, “Multihop multi-channel scheduling for wireless control in WirelessHART networks”, in ETFA, 2009.
[6] Pablo Soldati, Haibo Zhang, and Mikael Johansson, “Deadline-constrained transmission scheduling and data evacuation in wirelessHART networks”, in
Technical Report TRITA-EE 2008:060, 2008.
[7] Haibo Zhang, Pablo Soldati, and Mikael Johansson, “Optimal link scheduling and channel assignment for convergecast in linear wirelessHART networks”, in
Technical Report TRITA-EE 2009:018, 2009.
[8] “Wireless Sensor Network”,
http://en.wikipedia.org/wiki/Wireless_sensor_network (Acc. November 2011). [9] Johan Åkerberg, Mikael Gidlund, and Mats Björkman, “Future Research
Challenges in Wireless Sensor and Actuator Networks Targeting Industrial Automation”, 2011.
[10] ISA100 http://www.isa.org/isa100 (Acc. Nov 2011).
[11] Yinchun Shen, “A Simulation Study of Cell-Based Mesh Network Topology and Routing for Industrial Wireless Applications”, Master Thesis, Jönköping University, December 2011.
[12] Youzhi Xu, Mikael Gidlund, Dong Yang, Wei Shen, and Tingting, “Robust Routing in Cell-Based Mesh Networks”, Invention Disclosure Document, January 2011.
[13] Joel Goossens. “Scheduling of Hard Real-Time Periodic Systems with Various Kinds of Deadline and Offset Constraints”. PhD Thesis, Universite Libre de Bruxelles, 1999.
[14] Poisson Process, http://en.wikipedia.org/wiki/Poisson_process (Acc. November 2011).
[15] “LabVIEW Development Environment of National Instruments”, http://www.ni.com/labview (Acc. November 2011).
[17] HART Communication Foundation, “TDMA Data Link Layer Specification”, HCF_SPEC-075, Revision 1.1, May 17, 2008.
[18] HART Communication Foundation, “2.4GHz DSSS O-QPSK Physical Layer Specification”, HCF_SPEC-065, Revision 1.0, September 01, 2007.
7 Appendices
7.1 Appendix A State-of-the-Art Network Topologies
7.1.1 Star TopologyA typical star network topology is shown in Fig 7.1a. In a star network all the field devices are connected directly to the gateway. It offers lower latency, simple architecture and higher reliability.
M2 A4 M5 S3 S6 S7 M8 GATEWAY
Fig 7.1a Star Topology 7.1.2 Mesh Topology
In case of a mesh topology network all the nodes in the network must have the capability to source and sink packets. The communication link is completed up till the gateway by some of the nodes in the network that are directly connected to the gateway. Mesh topology offers large area coverage but at the cost of increased no. of hops which adds complexity to the routing and scheduling algorithms, lower reliability, and higher latency.
7.1.3 Star-Mesh Topology
In case of star-mesh topology the network is divided into clusters and each cluster has a head which is directly connected to the gateway. This topology is efficient than mesh topology since it has lower no. of hops by the use of cluster heads, although the failure of the cluster head will make the whole cluster fail. A typical star-mesh network topology is shown in Fig 7.1b.
Fig 7.1b Star-Mesh Topology 7.1.4 Hub-and-Spoke Topology
Hub-and-spoke topology is similar to star-mesh topology but in hub-and-spoke topology only backbone routers can be cluster heads as compared to star-mesh topology where any node can become a cluster head [12].
7.2 Appendix B Schedule Tables of Case-2
Table 7.2a Schedule for Cell-1Slot No. SUPERFRAME 1 SUPERFRAME 2 Slot Type
Source Node Destination
Node
Slot Type
Source Node Destination
Node 1 1 0 0 3 10 104 2 2 0 0 2 0 0 3 2 0 0 2 0 0 4 3 89 1 1 0 0 5 3 13 1 3 25 19 6 3 13 1 3 31 28 7 3 19 1 3 47 13 8 3 19 1 3 49 104 9 3 19 1 3 50 62 10 3 19 1 3 67 13 11 1 0 0 3 43 19 12 2 0 0 2 0 0 13 2 0 0 2 0 0 14 5 0 0 1 0 0
15 3 19 1 3 69 52 16 3 28 1 3 46 19 17 3 28 1 3 73 104 18 3 28 1 3 102 19 19 3 36 1 3 76 28 20 3 52 1 0 0 0 21 1 0 0 0 0 0 22 2 0 0 2 0 0 23 2 0 0 2 0 0 24 5 0 0 1 0 0 25 3 62 1 0 0 0 26 3 62 1 0 0 0 27 3 94 1 0 0 0 28 3 104 1 0 0 0 29 3 104 1 0 0 0 30 3 104 1 0 0 0 31 1 0 0 0 0 0 32 2 0 0 2 0 0 33 2 0 0 2 0 0 34 5 0 0 1 0 0 35 3 104 1 0 0 0 36 0 0 0 0 0 0 37 0 0 0 0 0 0 38 0 0 0 0 0 0 39 0 0 0 0 0 0 40 0 0 0 0 0 0 41 1 0 0 0 0 0 42 2 0 0 2 0 0 43 2 0 0 2 0 0 44 5 0 0 1 0 0 45 0 0 0 0 0 0 46 0 0 0 0 0 0 47 0 0 0 0 0 0 48 0 0 0 0 0 0 49 0 0 0 0 0 0 50 0 0 0 0 0 0
Table 7.2b Schedule for Cell-2 Slot No. SUPERFRAME 1 SUPERFRAME 2 Slot Type
Source Node Destination
Node
Slot Type
Source Node Destination
Node 1 1 0 0 3 9 17 2 2 0 0 2 0 0 3 2 0 0 2 0 0 4 3 60 2 1 0 0 5 3 17 2 3 15 82 6 3 17 2 3 16 108 7 3 24 2 3 53 16 8 3 24 2 3 16 108 9 3 24 2 3 18 92 10 3 39 2 3 26 100 11 1 0 0 3 32 91 12 2 0 0 2 0 0 13 2 0 0 2 0 0 14 5 0 0 1 0 0 15 3 39 2 3 48 91 16 3 57 2 3 54 39 17 3 82 2 3 61 91 18 3 82 2 3 75 108 19 3 82 2 3 81 108 20 3 82 2 3 33 84 21 1 0 0 3 65 82 22 2 0 0 2 0 0 23 2 0 0 2 0 0 24 5 0 0 1 0 0 25 3 82 2 3 88 24 26 3 82 2 3 77 88 27 3 91 2 3 72 82 28 3 91 2 3 84 82 29 3 91 2 3 84 82 30 3 91 2 3 88 24 31 1 0 0 3 99 57 32 2 0 0 2 0 0 33 2 0 0 2 0 0 34 5 0 0 1 0 0 35 3 91 2 3 51 103 36 3 91 2 0 0 0 37 3 91 2 0 0 0
38 3 92 2 3 103 91 39 3 100 2 3 103 91 40 3 100 2 3 107 91 41 1 0 0 0 0 0 42 2 0 0 2 0 0 43 2 0 0 2 0 0 44 5 0 0 1 0 0 45 3 108 2 0 0 0 46 3 108 2 0 0 0 47 3 108 2 0 0 0 48 3 108 2 0 0 0 49 0 0 0 0 0 0 50 0 0 0 0 0 0
Table 7.2c Schedule for Cell-3
Slot No. SUPERFRAME 1 SUPERFRAME 2 Slot Type
Source Node Destination
Node
Slot Type
Source Node Destination
Node 1 1 0 0 3 11 90 2 2 0 0 2 0 0 3 2 0 0 2 0 0 4 5 0 0 1 0 0 5 3 35 3 3 29 66 6 3 35 3 3 30 93 7 3 63 3 3 79 55 8 3 63 3 3 59 93 9 3 63 3 3 68 78 10 3 63 3 3 83 106 11 1 0 0 3 38 63 12 2 0 0 2 0 0 13 2 0 0 2 0 0 14 5 0 0 1 0 0 15 3 66 3 3 55 63 16 3 78 3 3 55 63 17 3 78 3 3 86 35 18 3 78 3 3 20 86 19 3 90 3 3 86 35 20 3 93 3 3 87 78 21 1 0 0 3 97 106 22 2 0 0 2 0 0 23 2 0 0 2 0 0 24 5 0 0 1 0 0
25 3 93 3 3 98 106 26 3 93 3 3 34 105 27 3 93 3 0 0 0 28 3 93 3 0 0 0 29 3 106 3 3 101 93 30 3 106 3 3 105 93 31 1 0 0 3 105 93 32 2 0 0 2 0 0 33 2 0 0 2 0 0 34 5 0 0 1 0 0 35 3 106 3 0 0 0 36 3 106 3 0 0 0 37 0 0 0 0 0 0 38 0 0 0 0 0 0 39 0 0 0 0 0 0 40 0 0 0 0 0 0 41 1 0 0 0 0 0 42 2 0 0 2 0 0 43 2 0 0 2 0 0 44 5 0 0 1 0 0 45 0 0 0 0 0 0 46 0 0 0 0 0 0 47 0 0 0 0 0 0 48 0 0 0 0 0 0 49 1 0 0 3 11 90 50 2 0 0 2 0 0
