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Presentation on theme: "HANDBOOK ON GREEN INFORMATION AND COMMUNICATION SYSTEMS"— Presentation transcript:

Chapter 4: IEEE Based Wireless Sensor Network Design for Smart Grid Communications Chun-Hao Lo and Nirwan Ansari Advanced Networking Laboratory Department of Electrical & Computer Engineering New Jersey Institute of Technology Newark, New Jersey, USA

2 Agenda Wireless sensor networks (WSN) and associated applications supported in Smart Grid Communications A comparison of IEEE and Power Line Communications technologies An introduction of IEEE Task Groups, particularly the IEEE g Task Group (TG4g) in developing the Smart Utility Network/Neighborhood (SUN) design Discussion of studies and challenges in IEEE LR-WPAN with respect to network design in PHY/MAC layers, fairness, routing, and security/privacy issues Conclusions

3 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.

4 WSNs in Smart Grid Communications (2/4)

5 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

6 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

7 IEEE 802.15.4 vs. PLC Technology IEEE 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

8 IEEE Task Groups

9 PHY specifications in IEEE 802.15.4a, b, c, and d
The legacy IEEE 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

10 IEEE g 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 standard for SUN PHYs while IEEE e 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– 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])

11 Other Approaches Other 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])

12 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

13 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.

14 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

15 IEEE 802.15.4 Studies and Challenges (4/4)
The PHY payload in IEEE 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 ) 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])

16 IEEE 802.15.4 Superframe structure (1/2)
CAP – Contention access period CFP – Contention free period BSD – Base slot duration SD – Superframe duration BSFD – Base superframe duration NSFS – Number of superframe slots BI – Beacon interval SO – Superframe order BO – Beacon order 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)

17 IEEE 802.15.4 Superframe structure (2/2)
CAP – Contention access period CFP – Contention free period BSD – Base slot duration SD – Superframe duration BSFD – Base superframe duration NSFS – Number of superframe slots BI – Beacon interval SO – Superframe order BO – Beacon order 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

18 Network design for IEEE802.15.4-based WSN (1/9)
A number of principal research issues in IEEE 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

19 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])

20 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

21 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 is not influenced by IEEE b 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

22 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])

23 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

24 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

25 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])

26 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])

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

28 Conclusions (1/2) Smart grid applications with different bandwidth and latency requirements can be provisioned in HR-WPAN (IEEE based) and LR-WPAN (IEEE based), which require further investigations for smart grid communications (improvement to legacy IEEE ) 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

29 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 g), and adopting TV White space, WiFi features, multi-channel access, as well as cognitive radio in the legacy IEEE standard (spectrum use efficiency) Complementary strategy of combining IEEE 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)

30 Thanks for your attention!


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