Chapter 4: IEEE 802.15.4 Based Wireless Sensor

Network Design for Smart Grid Communications

Chun-Hao Lo and Nirwan AnsariAdvanced Networking Laboratory

Department of Electrical & Computer Engineering

New Jersey Institute of TechnologyNewark, New Jersey, USA

HANDBOOK ON GREEN INFORMATION AND COMMUNICATION SYSTEMS

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AgendaWireless sensor networks (WSN) and associated

applications supported in Smart Grid CommunicationsA comparison of IEEE 802.15.4 and Power Line

Communications technologiesAn introduction of IEEE 802.15 Task Groups,

particularly the IEEE 802.15.4g Task Group (TG4g) in developing the Smart Utility Network/Neighborhood (SUN) design

Discussion of studies and challenges in IEEE 802.15.4 LR-WPAN with respect to network design in PHY/MAC layers, fairness, routing, and security/privacy issues

Conclusions

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WSNs in Smart Grid Communications (1/4)

Wireless Sensor Networks (WSNs) are deployed throughout the electric power system from generation, transmission, distribution, to end-use sectors

Applications: equipment sensing and monitoring, fault diagnosis, meter reading, etc.

Components: Supervisory Control and Data Acquisition and Energy Management Systems (SCADA/EMS), Phasor Management Units and Phasor Data Concentrators (PMU/PDC), Advanced Metering Infrastructure (AMI), and a wide range of Remote Terminal Units (RTUs), etc.

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WSNs in Smart Grid Communications (2/4)

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WSNs in Smart Grid Communications (3/4)

Five major domains Traditional power plants, transformers and substations

control, Distributed Energy Resources (DERs), power lines monitoring, and demand-side customers

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WSNs in Smart Grid Communications (4/4)

Types of sensors chemical, electrical, environmental, pressure, smart

appliances sensors, smart meters, etc.Different classes of sensor data to meet different

latency requirements, e.g., voltage and frequency control (< 100ms), smart metering (> 1s)

Collected data may be shared and reused for multiple applications (Ref. [9]) Challenges: modification to data packet headers may

be required; data may not carry sufficient information for some specific applications

Developments: Advanced sensors and associated sensor data management

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IEEE 802.15.4 vs. PLC TechnologyIEEE 802.15.4 (Ref. [17][18])

Fast deployment, low implementation cost, low complexity, low energy consumption

Matured technology used in various applications and tailored by popular working groups Alliances, e.g., ZigBee, WirelessHART, ISA100

Power line Communications (PLC) (Ref. [2][12][58]) Another viable approach that utilizes existing power line cables as

the communications medium for data transmission Shortcomings: 1) high bit error rates (due to noisy power line, e.g.,

motors, power supplies), 2) limited capacity (attributed to the number of concurrent network users and applications concurrently being used), 3) high signal attenuation (dependent of geographical locations), 4) phase change between indoor and outdoor environments, and 5) disconnected communications due to opened circuits

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IEEE 802.15 Task Groups

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PHY specifications in IEEE 802.15.4a, b, c, and d

The legacy IEEE 802.15.4 standards adopt BPSK, ASK, O-QPSK modulations, support data rates 20, 40, 100, 250 kbps, and operate in 868/915 MHz and 2.4 GHz frequency bands

The standards only specify PHY and MAC layers and leave the upper layers to be designed by the application designers

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IEEE 802.15.4g Task Group (TG4g) TG4g specifies Smart Utility Network/Neighborhood

(SUN) development by tackling a number of technical challenges in communications systems for the utility operators, especially the interference and coexistence issues TG4g amends the legacy IEEE 802.15.4 standard for SUN PHYs while IEEE

802.15.4e is tailored for SUN MAC (Ref. [59]) Three major SUN PHYs are proposed: multi-rate/multi-regional frequency

shift keying (MR-FSK), multi-rate orthogonal frequency division multiplexing (MR-OFDM), and multi-rate offset quadrature phase shift keying (MR-OQPSK) (Ref. [59])

Bands allocated in domains/countries for SUN are 470–510 MHz (China), 863–870 MHz (Europe), 902–928 MHz (United States), 950–958 MHz (Japan), and 2.4–2.4835 GHz (worldwide)

Keys: utilization of sub-GHz frequency bands (i.e., license-exempt bands below 1 GHz), and development of multi-PHY management (MPM) (Ref. [60])

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Other ApproachesOther techniques have been proposed to

enhance the network performance in smart grid communications from the PHY perspective Multi-channel access (Ref. [14]) WiFi features adoption (Ref. [15]) Cognitive radio (Ref. [16]) TV White Space (Ref. [59])

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IEEE 802.15.4 Studies and Challenges (1/4)

LR-WPAN generally employs TDMA with CSMA-CA, and adopts DSSS for various modulation schemes

Network variables and metrics in LR-WPAN design are predominantly based on topology control and traffic engineering Network size Node placement Data packet size Traffic loads

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IEEE 802.15.4 Studies and Challenges (2/4)

The network performance of LR-WPAN is determined by several key factors Frequency of wireless medium contention Successful data delivery ratio; collisions from

hidden node transmission, congestions from heavy traffic loads, and packet losses and drops from wireless deterioration and buffer overflow

Latency; unnecessary delayed transmission from the exposed node problem, a clumsy increase in MAC CSMA backoff periods, and inflexible routing design

Energy depletion rate; affected by the duty-cycle arrangement as well as data aggregation and fusion mechanisms.

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IEEE 802.15.4 Studies and Challenges (3/4)

Wireless impairments such as background noise, signal attenuation, path loss, multipath/fading, and interference are also found in LR-WPAN

Several measurements and parameters specified in LR-WPAN PHY/MAC are principal attributes to the network performance and design Receiver energy detection (ED) within the current channel Link quality indicator (LQI) for received packets and channel

frequency selection Clear channel assessment (CCA) for CSMA-CA NB: the number of times that CSMA-CA is required to backoff BE: a backoff exponent that is used to calculate the backoff period CW: the contention window length

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IEEE 802.15.4 Studies and Challenges (4/4)

The PHY payload in IEEE 802.15.4 is limited to 127 bytes; the application payload (useful information) is reduced to 60 bytes ~ 80 bytes after an inclusion of control bits. Since the ratio of overhead to data payload is considerably large, one needs to determine How to use bandwidths in LR-WPAN efficiently? How to manage packet size with useful data to achieve low

delay and low packet-loss rate during transmission? (Ref. [38]) Two types of data packet collision can also be found in

LR-WPAN (RTS/CTS is not supported in IEEE 802.15.4) Collision due to regular medium contention Collision due to hidden node problem (Ref. [34][35][37])

Exposed node problem can occur in LR-WPAN as well (Ref. [36])

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IEEE 802.15.4 Superframe structure (1/2)

Two operation modes beacon-enabled (B-E) with slotted CSMA-CA mode, and beaconless (BL,

i.e., beacon-disabled) with unslotted CSMA-CA mode In the B-E mode, the superframe is bounded by two consecutive

beacons, and constructed by the active and inactive parts The active portion is divided into 16 equal time slots that comprises

CAP and CFP, which defines GTS Up to 7 GTSs can be allocated by a WPAN coordinator and each GTS

may occupy more than one slot period (i.e., 1 BSD)

CAP – Contention access periodCFP – Contention free periodBSD – Base slot durationSD – Superframe durationBSFD – Base superframe durationNSFS – Number of superframe slotsBI – Beacon intervalSO – Superframe orderBO – Beacon order

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IEEE 802.15.4 Superframe structure (2/2)

GTS allocation and management specify starting slot, length, direction (i.e., transmit or receive), and associated node address. Each GTS is allocated first come first serve and released when it is not required

Slot boundary rule: a node begins to transmit on the next available slot boundary when the channel is idle. Otherwise, it allocates the boundary of the next backoff slot before it goes into the backoff stage. If the time between the next available backoff slot and the end of the active period is not long enough for a node to complete its transmission, it may have to wait until the arrival of the next superframe

CAP – Contention access periodCFP – Contention free periodBSD – Base slot durationSD – Superframe durationBSFD – Base superframe durationNSFS – Number of superframe slotsBI – Beacon intervalSO – Superframe orderBO – Beacon order

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Network design for IEEE802.15.4-based WSN (1/9)

A number of principal research issues in IEEE 802.15.4 are categorized into four areas: PHY/MAC layers, fairness, routing, and security

Analysis in PHY/MAC under different network environments is grouped into B-E and BL studies In B-E study, CAP/CFP

and BO/SO are examined In both studies, ED/LQI,

CCA, CC/HNC/ENP, and NB/BE/CW are investigated

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Network design for IEEE802.15.4-based WSN (2/9)

CAP and CFP (with GTS) Management QoS consideration in data transmission specified in

smart grid applications, e.g., GTSs are allocated to nodes with mission-critical data

The positions of CAP and CFP are swapped (modification to the standard is required) in order to grant the retransmission attempt of GTS to proceed in CAP of the same superframe upon a failed transmission in GTS (Ref. [42])

Analysis of GTS request drop due to possible collisions in CAP when BO is considerably small (Ref. [43])

Two-traffic class is proposed to allow nodes with higher-priority data to transmit by assigning CW=1 (Ref. [44])

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Network design for IEEE802.15.4-based WSN (3/9)

SO and BO Measurement Consideration of the need for power saving on each

node at the cost of transmission latency, i.e., SO=BO (100% duty cycle) if a node is not power-constrained

Analysis of end-to-end delay and packet loss by studying the packet inter-arrival time and the ratio of BO to SO (Ref. [45])

Tradeoff between latency and energy consumption under the same duty cycle, which can be constructed by different combination sets (Ref. [46]), e.g., both BO=3/SO=2 and BO=11/SO=10 cases have 50% duty cycle

1Duty cycle , 0 142

BO SO

BO SO

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Network design for IEEE802.15.4-based WSN (4/9)

ED and LQI Assessment (Ref. [47]) Determination of ED and LQI to identify the radio

condition While using LQI and RSSI (or ED) metrics for a

number of field tests in real-world power delivery and distribution systems, several conclusions are made: 1) the background noise (varied in temperature and time) is higher for the indoor than the outdoor environment; 2) channel 26 in IEEE 802.15.4 is not influenced by IEEE 802.11b interference; and 3) LQI is a good estimator when the signal is found below and close to the sensitivity threshold, i.e., -94 dBm; otherwise, RSSI (or ED) is recommended

 RSSI – Received signal strength indicator

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Network design for IEEE802.15.4-based WSN (5/9)

CCA Analysis Determination of whether a specific radio channel is

busy or idle prior to the data transmission Collision may occur during the receive-to-transmit

(Rx-to-Tx and vice versa) turnaround time even if a channel was initially detected as idle (Ref. [48])

An adaptive MAC engine containing a collection of preset optimal protocols for different network conditions is proposed to avoid time spent on restarting the design process each time (Ref. [49])

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Network design for IEEE802.15.4-based WSN (6/9)

NB, BE, and CW Examination (Ref. [50]) NB and BE parameters can be directly affected in

consequence of CCA, which is related to CW assignment

Under light or medium traffic condition, increasing the BE value seems to bring down the probability of packet loss, however, at the cost of increased latency

Under heavy traffic condition, adjusting BE becomes insignificant to improve network performance

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Network design for IEEE802.15.4-based WSN (7/9)

Fairness An adaptive GTS allocation scheme is proposed to

determine the success of GTS requests and the present traffic-level state of a node (Ref. [51])

A node generating heavy or more recent data traffic is likely to have a higher probability of staying in a higher priority state

A node staying in a higher-level state with temporary transmission interruption will slightly be demoted to a lower state. On the other hand, a node in a lower-level state can be promoted to a higher state if a consecutive success of GTS requests is achieved

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Network design for IEEE802.15.4-based WSN (8/9)

Routing Arrangement While the standard does not specify

network/transport layer, various routing protocols based on AODV have been proposed (Ref. [52][53][54])

A routing strategy based on OLSR that responds to the requirements specified in power generation industry is also proposed (Ref. [10])

A hybrid routing scheme unifying flat and hierarchical multi-hop algorithms with respect to power consumption is also proposed (Ref. [33])

New integrated routing techniques in supporting IPv6 via 6LoWPAN need to be developed (Ref. [55])

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Network design for IEEE802.15.4-based WSN (9/9)Security and Privacy

Owing to the low computation capability and high overhead constraints, limit of number of access control list (ACL) entries and lack of group keying are identified (Ref. [56])

Security architecture for smart grid WSNs specifying security standards and testing/evaluation for both hardware and software need to be developed (Ref. [13])

Privacy in smart grid communications is comparable to patients' medical records in home and hospital

Elliptic curve cryptography adopted in healthcare WSN is proven to be lightweight computationally and uses smaller key sizes for obtaining the same security level as compared to RSA (Ref. [57])

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A Summary of Network design and challenges in IEEE802.15.4-based WSN

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Conclusions (1/2) Smart grid applications with different bandwidth and

latency requirements can be provisioned in HR-WPAN (IEEE 802.15.3 based) and LR-WPAN (IEEE 802.15.4 based), which require further investigations for smart grid communications (improvement to legacy IEEE 802.15.4) Design of data prioritization related to specific applications and

QoS requirements Adequacy of control (i.e., overheads) and data packet size

(including commands) Schemes for multi-PHY management Assessment of communications link quality Innovation of MAC medium contention Flexibility of routing mechanisms Fairness issues upon adopted schemes Security/privacy models for protecting data and associated

transmission

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Conclusions (2/2) Proposed techniques to alleviate interference and

coexistence problems by utilizing spectrums more effectively and efficiently, e.g., operating frequency bands below 1 GHz and developing multi-PHY management (specified in IEEE 802.15.4g), and adopting TV White space, WiFi features, multi-channel access, as well as cognitive radio in the legacy IEEE 802.15.4 standard (spectrum use efficiency)

Complementary strategy of combining IEEE 802.15.4 with PLC technologies should be considered to provision sensor applications in various smart grid domains (interoperability)

Innovative mechanisms and models of integrating IP and other technologies with WSNs need to be developed to facilitate smart grid communications and management (integration)

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Thanks for your attention!