Coexisting problems for wireless sensor networks working in 2.4 GHz frequency band

Textbook 2019 136 Pages

Computer Science - Internet, New Technologies








1 Introduction
1.1 Introduction
1.2 The Introduction to Smart Grid Communication System Scenario
1.2.1 The Home Area Networks for SG Applications
1.2.2 The Neighbourhood Area Network (NAN) for SG Applications
1.2.3 The WAN for SG Applications
1.3 The WSN Protocol design goals for SG applications
1.3.1 Reliability of WSN
1.3.2 Quality of Service Requirements for WSN
1.3.3 Interference Avoidance
1.3.4 Energy Consumption
1.3.5 Interoperability
1.3.6 Memory Management
1.3.7 Security
1.3.8 Heterogeneous system conditions
1.4 Research Motivation
1.5 Research Objectives

2 A Review on Interference Avoiding Methods for WSN working in the 2.4GHzISM Band
2.1 Review of Literature
2.2 Interference
2.2.1 Interference from other coexisting technologies working in same frequency band
2.2.2 Interference from the nodes of same network
2.3 Evaluation and Modeling of Interference
2.3.1 Measurement of Interference
2.3.2 The Identification of Interferer
2.3.3 Modeling Interference
2.4 Observations
2.5 Open Research Issues
2.5.1 Reliability of data communication
2.5.2 Cross-layer dynamics
2.5.3 MAC layer
2.5.4 Channel Selection
2.6 Simulation Environment Utilized for the Research
2.6.1 The Network Simulator(ns)
2.6.2 Directories of ns-
2.6.3 Basic Architecture
2.6.4 The Role of C++ and OTcl in ns-
2.6.5 Main ns-2.34 Simulation Steps
2.6.6 Tracing of the Data Packets

3 Cross-layerbased Interference Mitigation and Encoding for Multi-channel ZigBeeNetworks
3.1 Introduction
3.2 >Related Works
3.3 Cross-Layer Multi Channel MAC Protocol
3.3.1 Overview
3.3.2 Estimation of Interference Level
3.3.3 Prediction of future of Hidden Markov Model
3.3.4 Data transmission through channel with least interference
3.4 Forward Error Correction based Encoding Technique for WSN
3.4.1 Transmission Scheme using (CMCMAC-FEC) Encoding
3.5 Simulation Results of CMCMAC and CMCMAC-FEC
3.5.1 Analysis of network parameters based on varying number of nodes (ZigBee) and fixed data flows (WiFi)
3.5.2 Analysis of network parameters of CMCMAC-FEC based on vary- ing number of nodes and fixed data flows
3.5.3 Analysis of network parameters based on Varying number of flows (WiFi) to the fixed number of nodes(ZigBee)
3.5.4 Analysis of CMCMAC-FEC based network parameters by vary- ing number of flows
3.6 Conclusion

4 Load Aware Channel Estimation and Channel Scheduling for 2.4GHz Frequency Band BasedWirelessNetworks For SmartGrid Applications 55
4.1 Introduction
4.2 Related Works
4.3 Partile Swarm Optimization Based Load Aware Channel Estimation and Channel Scheduling for ZigBee Networks Working Under the Influence of WiFi
4.3.1 Pseudorandom-Based Interference Evading Scheme
4.3.2 Load Aware Channel Estimation
4.3.3 Traffic Weight Assignment
4.3.4 Particle Swarm Optimization (PSO) based Load Aware Channel Estimation
4.4 Simulation Results
4.4.1 Verification of various wireless technologies by changing the Num- ber of Nodes
4.4.2 Varying the Data Flows
4.5 Summary

5 A Collaborative Framework for Avoiding Interference between Zig- bee andWiFi for Effective Smart Metering Applications
5.1 Introduction
5.2 Related Works
5.3 Proposed Work
5.3.1 The Collaborative Framework for Avoiding Interference between ZigBee and WiFi networks
5.3.2 Realization of the Distance and RSSI
5.3.3 Realization of the Distance and RSSI
5.3.4 Throughput Estimation
5.4 Performance Evaluation
5.5 Conclusion

6 Interference Aware Adaptive Transmission Power Control Algorithm for ZigBeeWirelessNetworks 88
6.1 Introduction
6.2 Related Works
6.3 Interference aware Adaptive Transmission Power Control Algorithm
6.3.1 Problem Identification and Objectives
6.3.2 Initialization stage
6.3.3 Operational stage
6.4 Simulation Results
6.4.1 Simulation Parameters
6.4.2 Performance Metrics
6.4.3 Results and Analysis
6.5 Conclusion

7 Conclusion
7.1 Future Scope




With the introduction of Information and Data-Communication Technology (ICT) to the present electrical power systems, the traditional electrical-grid system is becoming more intelligent and adaptive. The ICT successfully establishes bi-directional commu- nication between Utility companies and the consumer for improving the generation and utilization of power. Wireless Sensor Network (WSN) is efficiently utilized by wide- ranging Smart Grid (SG) applications. Despite many advantages, WSN faces a chal- lenge of avoiding interference experiencing from other coexisting wireless technolo- gies working in the 2.4GHz unlicensed frequency band. Providing support for WSN in terms of avoiding interference is a very challenging issue due to the dynamic wireless communication environment and extremely limited resources. In the present thesis, the problem of interference experienced by WSN in 2.4GHz has been investigated. The challenges, limitations and requirements for avoiding the interference for WSN work- ing in the vicinity of other technologies like WiFi and Bluetooth have been identified. As a result of the literature survey carried out, it was identified that proper channel se- lection and channel prioritization for WSNs working in the coexisting environment had not been adequately developed till then. Hence, there was a requirement for addressing these issues. The contribution of this thesis consists of five novel schemes for improving the performance of WSNs working under the influence of WiFi.

Firstly, a Cross Layer Multi Channel Medium Access Control (CMCMAC) Algo- rithm is proposed. This algorithm estimates the initial channel parameters like Received Signal Strength Indicator (RSSI) and Channel Occupancy Rate (COR). Then,these pa- rameters are applied to the Hidden Markov Model (HMM). Then, based on the esti- mation, the channel with less interference is identified and is selected for data commu- nication. The CMCMAC performance was compared to the existing protocol, FDRX. CMCMAC outperforms 11% in terms of Packet Delivery Ratio (PDR) and 21% better in terms of Energy Consumed (EC) for different scenarios, based on the varying number of nodes and different data traffic scenarios.

Secondly, Forward Error Correction for CMCMAC (CMCMAC-FEC) is proposed with an aim of better data recovery of partially collided packets at the destination side. This algorithm further enhanced the performance of CMCMAC. Thus, with varying number of nodes and constant WiFi data rate, CMCMAC-FEC outperformed by 7% in terms of PDR as compared to CMCMAC. CMCMAC-FEC performed 9% better in terms of PDR when number of nodes are constant and WiFi data rates are changing.

Thirdly, Particle Swarm Optimization Based Load Aware Channel Estimation and Channel Scheduling (PSOLACES) Algorithm is proposed. Development of PSOLACES recommends the channel shifting with a minimum frequency shift of 7MHz for the im- proved performance of WSN working under the influence of WiFi.

Fourthly, Collaborative Framework for Avoiding the Interference (CFAI) is pro- posed. CFAI Algorithm assures better channel utilization. The average number of pack- ets generated by ZigBee network based on CFAI gets reduced in number. Also, CFAI assures better throughput compared to the existing works like CFMSS, PSOLACES, K.Hong et al.,and RDBS.

Finally, Interference Aware Adaptive Transmission Power Control (IAATPC) is pro- posed for WSN. IAATPC analyzes the power level needed by a node in the network to ensure reliable data delivery. The data transmission is performed under different net- work conditions by adaptively controlling the transmission power; and in turn, ensuring network efficiency. From the results, it can be inferred that the average residual energy of a node based on IAATPC is 9.6% higher than AMTPC.

The proposed schemes in this thesis are based on simulation results obtained. All the presented schemes avoid interference by proper channel selection under diverse op- erational conditions by considering different Quality of Service (QoS) parameters; and assure better PDR, EC, reduced Frame Error Rate (FER) and proper channel utiliza- tion. The performance of WSN has been improved by strictly following the latency requirements of SG applications.

Keywords: Home Area Networks,Interference Avoidance,Smart Grid Communica- tions,The 2.4GHz F r equency Band,W i r eless Sensor Networks.


With immense pleasure and deep sense of gratitude, I dedicate this book to Lord Dharmapuri Lakshmi NarashimhaSwamy.

I could able to complete this book only with the blessings of MahaperiyaSri Sri Sri Chandrashekarendra Saraswathi Swami

I wish to extend my profound sense of gratitude to my parents Mr. Madhusud- han Rao and Mrs. Vijaya for all the sacrifices they made during my research and also providing me with moral support and encouragement whenever required.

Last but not the least, I would like to thank my wife Mrs. Ravali and my daughter Maithreyi for their constant encouragement and moral support along with patience and understanding.



Every figure was created by the author

1.1 The Pictorial Representation of different Smart Grid functions

1.2 The representation of three important areas of different Smart Grid functions

1.3 Network model with different networks for SG

2.1 The modern wireless technology-based applications operating in 2.4GHz frequency band

2.2 The modern smart home considering ZigBee for automation, WiFi for accessing Internet for SG Applications

2.3 Channel specifications of the wireless technologies operating in 2.4GHz frequency band

2.4 The directories in the ns

2.5 The basic architecture of ns

2.6 The internal structure ns

2.7 The simulation steps of ns

2.8 The Trace file format

3.1 The CMCMAC block diagram

3.2 The comparison of packet delivery ratio to number of nodes

3.3 The comparison of number of packets lost due to collision to the number of nodes

3.4 The comparison of energy consumed (mJ) to the number of nodes

3.5 The comparison of throughput to number of nodes

3.6 The comparison of packet delivery ratio(CMCMAC-FEC) to number of nodes

3.7 The comparison of throughput(CMCMAC-FEC) to number of nodes

3.8 The comparison of packet delivery ratio to number of flows

3.9 The comparison of number of packets lost due to collision to the number number of flows

3.10 The comparison of energy consumed to number of flows

3.11 The comparison of throughput to number of flows

3.12 The comparison of packet delivery (CMCMAC-FEC) to number of flows

3.13 The comparison of throughput (CMCMAC-FEC) to number of flows

4.1 The Superframe architecture

4.2 The Block diagram of PSOLACES

4.3 The Pseudorandom Order Generator (PROG)

4.4 The 2.4GHz ISM frequency based channels distribution for WLAN and WPAN technologies

4.5 Evaluation of FER for IEEE 802.15.4 under the coexistence of 802.11b transmission (when packet size is 20 bytes)

4.6 Evaluation of FER for IEEE 802.15.4 under the coexistence of 802.11b transmission (when packet size is 40 bytes)

4.7 Evaluation of FER for IEEE 802.15.4 under the coexistence of 802.11b transmission (when packet size is 127 bytes)

4.8 Comparison of packet delivery ratio (%) by varying number of nodes

4.9 Comparison of Average Energy consumed (mJ) to by varying number of nodes

4.10 Comparison of packet delivery ratio (%) by varying number of flows

4.11 Comparison of AVG. Energy consumed to varying number of flows

5.1 Channel distribution of different technologies in 2.4GHz frequency band

5.2 The block diagram of the proposed CFAI

5.3 The architecture of smart home environment

5.4 Transmission delay in Zigbee network.Delay D=10ms

5.5 Transmission delay in Zigbee network.Delay D=50ms

5.6 Average Number of Packets Generated per Second

5.7 Average Number of Packets Generated per Second

6.1 Comparison of Number of Nodes to End-End Delay (ms)

6.2 Comparison of Number of Nodes to Packet delivery Ratio

6.3 Comparison of Number of Nodes to Overhead

6.4 Comparison of Number of Nodes to Throughput

6.5 Comparison of Number of Nodes to Residual Energy

6.6 Comparision of Number of Flows to End to End Delay (ms)

6.7 Comparison of Number of Flows to Packet Delivery Ratio

6.8 Comparison of Number of Flows to Overhead

6.9 Comparison of Number of Flows to Throughput

6.10 Comparison of Number of Flows Residual Energy (mJ)


1.1 The Comparison of HAN Communication Technologies

3.1 Simulation Parameters

4.1 Identification of Cluster key

4.2 Simulation Parameters

5.1 Parameters and Values for Simulation

6.1 Nomenclature: Initialization Phase

6.2 Nomenclature: Operational Phase

6.3 Parameters and Values for Simulation


Abbildung in dieser Leseprobe nicht enthalten



1.1 Introduction

The advanced research on power system issues for almost a decade has introduced the SG to the countries across the world. The SG represents modernized power delivery system. The initiation of advanced Information and Data-Communication Technol- ogy (ICT) for SG has significantly improved the quality of power transmission and dis- tribution from power generation plants to end-users. The SG introduces the advanced technologies like modern automation, two-way communication, advanced monitoring, and control to optimize the power quality, efficiency, and reliability of all its inter- connected power system elements. With the advent of integrating ICT into the power systems has improved the working capabilities of the utility companies in terms of bet- ter asset management and ensures the advanced energy management for the end-user (Gungor et al. 2010).

In the scenario, to execute the desired operations like effective monitoring and con- trolling the SG assets, it requires a well-established and reliable automation using ICT. The management of the present SG technologies can be done in terms of integrating the heterogeneous entities into the grid network as shown in the Fig.1.1. The power gen- eration, transmission, and distribution are managed accordingly and intelligently based on the proactive scheduling of loads by SG (Gungor et al. 2011).

The most important advantage for utilities with SG is the availability of real-time data. The data received in a timely manner makes utilities more intelligent. The data received by utility servers is very huge. With the intelligent and efficient data analyt- ics programming the data assessment is carried so as to make intelligent decisions for reducing power costs, maintenance costs and assure fewer outage costs with the in- creased life of power system assets. The data decisions are combined with advanced ICT and improved control technologies, this progression decreases the power disorders, segregate faults, results in rapid restoration of power outages and manages the integra- tion of renewable energy resources. An efficient transmission network plays a key role in carrying the power from generation stations to distribution stations. The smartness of SG lies in the integration of an extensive range of physical power assets and in- formation resources for advanced operations in terms of monitoring and control. The SG makes distribution infrastructure more intelligent by employing multiple advanced technologies based on WSN like Home Energy Management Systems, Distributed Au- tomation (DA), Smart Meter System, and Advanced Metering Infrastructure (AMI) (Hu et al. 2018).

Abbildung in dieser Leseprobe nicht enthalten

Fig. 1.1 The Pictorial Representation of different Smart Grid functions

The SG architecture consists of three important layers as presented in Fig.1.2. These layers play a key role in advanced control and automation operations that needed to be carried by SG. The three layers include,

1. Traditional Power System layer,
2. Data-Communication layer, and
3. Information technology layer.

The traditional power system layer comprises of power generation (using conven- tional and non-conventional energy sources), transmission (Wide area monitoring using Phasor-Measurement Units), distribution systems (like Network management and effi- cient outage management system), and end-user premises (Smart Meter and appliances

Abbildung in dieser Leseprobe nicht enthalten

Fig. 1.2 The representation of three important areas of different Smart Grid functions.

with data communication ability). The communications layer is responsible for data communication based on latency requirements defined as per the policies of SG. It al- lows bi-directional flow of information from all the electrical components in the grid to utility centers and vice-versa. Information technology layer is responsible for data collection, data analysis, data management and security aspects. The combination of all the above three areas very helpful for load scheduling and energy management based decisions by utility companies. The exchanged information between end-user and util- ity consists of both (i) Tariff-per-unit of power as fixed by utilities allowing for a balance between energy demand and supply, and (ii) Controlling, supervising, and maintenance information of SG components and allowing remote operations based on systematic au- thentication. The modern viable methodologies, tools and advanced technologies in the areas of data analytics, control and data communications allow the power grids to self- regulate. Thus, with the increased monitoring there shall be reduced failures, reduced maintenance, fewer outages costs and assures the increased life of the power system assets. The efficient communication of data among the power system entities is consid- ered as significant because it has a major role in coordinating different functionalities of SG. The complete power system arrangement can be observed as a logical informa- tion network, consisting of the electrical appliances considered as nodes (information sources), transmits information to sinks (data aggregator) interconnected through differ- ent level communication protocols. The information is transmitted from source nodes to sink (destination) nodes over information links bridging across different systems, utility organizations, customers, and communication protocols. To support optimal commu- nication between these nodes, a set of interoperability standards are required (Kabalci 2016).

1.2 The Introduction to Smart Grid Communication System Scenario

The SG technologies have made the availability of real-time data to benefit the utili- ties for making more intelligent decisions during normal and hostile situations. The advanced control technologies integrated with the advanced data communication tech- nologies will reduce the power disorders and segregate faults and results in rapid restora- tion of outages. The communication set-up plays an important role in coordinating generation plants, transmission system, distribution system, system operator, power market, and end-user (Gao et al. 2012). The advanced data communication for AMI involves the bi-directional flow of information from end-user to utility and vice versa. For this purpose, different communication networks like Wireless communication net- works, Broadband over Power Line (BPL), Fiber Optic Communications, Power Line Communication (PLC), public networks can be used. The data gathered by the smart meter can be communicated to utility via the wired or wireless connection. It should also update the information from utility to end-user, so that end-user can respond ac- cording to the utility decisions. The smart meter is a sensitive and complex device that handles large data between home appliances and utility center without any dis- ruptions. The smart meter data is most trustworthy, and the access is limited to few people. The communication standards and strategies are framed to safeguard the data transfer within the network and should be protected. Every smart meter is assigned with a specific IP address that can connect both the higher hierarchy SG systems and HAN based appliances based on the type of data communications systems they adapt. The communication network should also support the smart meter even if power outage hap- pens. Communication technologies employed should be economic, should have better transmission ranges, with standard security features, and should provide the required bandwidth (Amin 2011).

The SG networking for data-communication purpose is broadly classified into three important areas based on the type and purpose of the application

1. Home Area Network (HAN) from home appliances to Smart meter and vice- versa.
2. Neighbourhood Area Network (NAN) from smart meter to Local aggregator and vice-versa.
3. Wide Area Network (WAN) from local aggregator to utility center and vice-versa.

These three networks are responsible for managing the entire appliances and appli- cations from centralized utility center. Fig. 1.3 shows a network model with different networks for SG.

Abbildung in dieser Leseprobe nicht enthalten

Fig. 1.3 Network model with different networks for SG.

The HAN is a communication network between the home appliances and smart meter. The Smart meter is an important device that receives the data from the appli- ances and communicates this data to the local data aggregator using NAN. The NAN or Field area networks are mainly employed in between HAN and WAN. There are two IEEE standards that are carefully related to NANs. The IEEE standard 802.15.4G mainly deals with an out-of-door environment with relatively low data rates ( less than 10kbps) and associated with wireless smart metering utility network (SUN). Secondly, IEEE 802.11s is closely related to the network operations like node delivery and route selection of smart grid NANs. The privacy of data must be ensured from cyber-attacks for smart grid NANs. WANs serves for smart grid between the NAN and utility cen- ter. WAN employs a high-bandwidth network for providing backhaul communication between different substations, distributed automation, and data aggregation points cov- ering for thousands of kilometers apart. Reliability and security are the most important aspects of all the networks. Most of the utility operators like AT and T, Verizon, and Sprint shall make use of private WANs for increased security instead of depending on public networks.

1.2.1 The Home Area Networks for SG Applications

The HAN is the most important technology for SG that enables bi-directional data communication from smart meter to the utilities and vice-versa. The HAN is enabled by Wireless Sensor Network (WSN) which is efficiently carrying data communication from appliances to smart meter and vice-versa. Also based on the user recommenda- tion and requirements, the HAN is also responsible for controlling the actuators. The home automation, and building automation are the important applications of HAN. The HAN is responsible for integrating the following devices like intelligent electronic de- vices, smart sensors, actuators, smart appliances and the smart meter acting as a home gateway. A star topology is adopted either with wired technologies (e.g. Ethernet, PLC) or by using different wireless technologies like (e.g., ZigBee, and Wireless Fi- delity (WiFi)). Authorization of an appliance for communicating the data and con- trolling an appliance when required, are two significant functionalities in the HAN. Authorizing is quantified to recognize and manage different appliances that form a self- organizing network. Control is an important functionality for safeguarding interoper- ability within the SG. The end-user premises enabled by HAN mainly implements AMI and Demand Response (DR). For coordinating smart meter for its monitoring purposes HAN deploys various wireless technologies like WiFi and ZigBee. Wired solutions may include the use of Ethernet and PLC. Though wired communication supports good data rates and security, Ethernet involves high cabling costs and less flexibility compared to wireless. The usage of PLC for HAN is still in preliminary stages (Mahmood et al. 2015). The Table 1.1 shows the comparison of HAN communication Technologies.

Table 1.1 The Comparison of HAN Communication Technologies

Abbildung in dieser Leseprobe nicht enthalten

The role of HAN is also becoming important in remote monitoring and controlling of the electrical appliances like thermostats, air conditioning (A.C.), vehicle charging etc. The smart meter has an ability for connecting all the home applications using wire- less connection based on ZigBee. The ZigBee works in 2.4GHz frequency band and is under the influence of WiFi(become unavoidable in the HAN premises) that is also usually working in the same unlicensed 2.4GHz band. The wireless technologies con- sidered for HAN are operating under the frequency band i.e, 2.4GHz band (Industrial, Scientific, Medical (ISM) band). The 2.4GHz frequency band is unlicensed band and allows different wireless networks to utilize the frequency band.

The modern applications like Home automation, SG, Smart Cities are dependent on wireless networks based data communication. The factors affecting the performance of the interference is an important phenomena that is to be considered for increasing the ef- ficiency of WSN. Interference is a phenomena where a node operating in a network with high power (WiFi), is influencing the performance of low power nodes (ZigBee). As the both WiFi and ZigBee are operating in the same frequency band and as the WiFi node operating with high signal strength when compared to ZigBee, the WiFi node gains the channel for data transmission. Thus ZigBee node has to wait or search for other channel to transmit the data. For the efficient operation of low power network there is a need for a mechanism to avoid interference under the coexisting environment. For efficient operation of WSN (based on ZigBee norms operating under IEEE 802.15.4) interference must be avoided that is experienced from WiFi. The aim of this thesis is avoiding interference for WSN working under the influence of WiFi. The interference phenomena is presented in detail in the following chapter 2.

Advantages of HAN

- HAN permits the end-users and lets the SG infrastructure to be benefited by the end-users openly; this involvement of end-users will benefit the utilities to man- age peak loads.
- The main aim of HAN is to make the SG hassle-free by controlling or shifting the loads so as to save from potential blackouts.
- HAN enables end-users to control their energy bills by shifting their loads from peak timing to normal load timings.
- Utilities are informed using HAN about the electricity usage of every individ- ual end-user and provides centralized access for utility centers to control all the appliances at the end-user premises.
Challenges of HAN
- The integration of various technologies like automation, wireless connections, and security is a challenging task.
- Interoperability of all the technologies for a common cause like home energy management is an important concern and modern solutions should be acceptable by the market.
- The addressing end-user confidentiality and data security is very important.

1.2.2 The Neighbourhood Area Network (NAN) for SG Applications

The NAN shall connect the intelligent electronic devices like Smart meters to the AMI. NAN plays a major role in connecting the distribution side appliances. The NAN covers an area of 1 to 10Kms, working with the data rates between 10-100Kbps. NAN is operated by various technologies like, WiFi, RF technologies, WiMAX, cellular (3G, 4G, 5G) and LTE-3GPP on the wireless side and on the wired side, PLC, Ethernet, DOCSIS are promising preferences to use. The most important applications of NAN are as enlisted below, meter reading, DA, DR, prepaid payment, electric transmission and distribution monitoring, utility updates, program and configuration updates, outage resource management, time-of-use pricing, service-based switching operation, end-user information and message alerts, buildings network.

There are two important latest IEEE standards that are most relative to SG based NANs. Firstly, IEEE 802.15.4g insist on Physical layer and Medium Access Control (MAC) layer architecture of SG communication networks. The IEEE 802.15.4g focus is mainly on low data speed wireless communication in the outdoor environment. This standard has aimed for wireless network based Smart-Metering Utility Network (SUN) necessities. The SUN mainly aims for the very large dispersed network operates with low power requirements. SUN consists of a many wireless nodes that are widespread over a large area and operates with efficient routing algorithms for data communication (IEEE std.P802.15.4g, 2011). SUN operates in unlicensed frequency bands (2.4GHz) and has to withstand interference with another wireless communication system (Gao et al. 2012). Secondly, IEEE 802.11s addresses network operation issues of SG. The IEEE 802.11s is an improvement for the existing protocol IEEE 802.11 on the basis of better frame delivery ratio and path selection for multi-hop networks by improving the RF parameters at MAC layer. This protocol also includes the features of demand based routing protocol and tree structure type proactive routing protocol. IEEE 802.11s offers high reliability and high-speed data transmission with better routing for Wireless NAN applications.

1.2.3 The WAN for SG Applications

The WAN offers communications linkage between SG applications and utility systems. WAN include two types of networks: core network and backhaul communication net- work. The core network connects a metropolitan network of the utility and substa- tions. The backhaul network connects NAN’s (data aggregation points) to the core network. The WAN is a very large network covering thousands of Sq. Miles with the data transmission range up to 10 to 100Mbps. In most of the cases, communication technologies used for WAN operations are public networks such as wired broadband lines or cellular networks (4G or 3G). But in recent times security issues are question- ing the viability of the public networks and to address the issues of WAN particularly data security, private networks based communication is adapted or thoughtful in the recent times. For reducing the cost of infrastructure, The concept Virtual Private Net- work (VPN) is emerging which is a combination of both public and private network but with special traffic segmentation and including security features that make VPN like the private network. The applications of WAN include Wide Area Monitoring Protection and Control (WAMPAC), most important next generation-based solutions. The above strategies improve the power system planning and operations to enhance the reliability of the monitoring techniques. The infrastructure used for establishing wireless WAN includes similar protocols like WiMAXp, 3GPP networking, GSM and RF Mesh are used for backhauling network and can be considered as part of the NANs. For wired options, Passive Optical Networks or Digital Subscriber Line can be employed. The Metro Ethernet can be employed for the core network with some wired protocol like Internet Protocol/Multi-Protocol Label switching and SONET- fiber (Gao et al. 2012).

1.3 The WSN Protocol design goals for SG applications

For implementing the envisioned SG the situational data awareness plays a major role for a number of critical operations mainly in the areas of sensing the appropriate data, data-communication, effective monitoring and efficient decision making. It is very es- sential that all the applications of SG should always be effectively monitored. WSN was identified as a promising technology for monitoring and controlling purposes in SG applications. The WSN plays a key role in gathering information from individual electrical appliances provides it to electric utilities and vice-versa. Thus, the WSN will enable SG to achieve high system efficiency and reliability. The wireless sensors in ad- dition with actuators in the SG network will appreciably improve the existing networks capability and can assure more affluent application favored control actions (Khan and Khan 2013).

The SG needs a well-organized MAC approach for, prioritization of data and should assure specific latency requirements. The WSN based data communication within SG system is based on important metrics like latency, data rate, end-end delay, and conges- tion. The data is accumulated in a reliable and timely approach from all the sources in the considered system and based on this information the complete power systems is su- pervised and advanced controlling can be initiated based on the requirements (Ancillotti et al. 2013).

1.3.1 Reliability of WSN

The WSN based smart grid applications experiences unreliable wireless networking issues because of various problems like asymmetry of wireless links, interference ex- perienced from other technologies, fading and multipath propagation. Though many of the protocols were proposed taking into consideration for ideal conditions, these are not well suitable for harsh conditions of smart grid operations. The inconsistent link quality and inadequate battery levels is considered as important research area and motivates the researchers to improve the performance of proposed protocol for this environment. The protocol proposed should deliver the data packets to destination node within the speci- fied latency by maintaining the high packet delivery ratio. For the increased reliability the MAC and routing protocol based on smart grid applications must be implemented. The systematic MAC layer should be developed so as to control the retransmissions of the lost packets using automatic repeat requests (ARQ). The packet retransmissions can also be decreased by including some redundant bits to the initial packets by means of the forward error correction techniques.

1.3.2 Quality of Service Requirements for WSN

The WSN is mainly utilized for supervising and restricting the SG applications that have different QoS requirements. These standards are defined by organizations like IEEE, SGIP, NIST, ISGF etc. For example, consider a situation like active pricing notifications and activating the actuators based on the alarm conditions. It is very important to bring together the data from the different sources according to the timely manner so as to take an appropriate decision. The outdated data will generally suffer from discrepancy and results in undesired actions that may lead to wrong decisions in pricing and control. Hence, there is a requirement for good research on the QoS aware protocols that suits the SG applications.

1.3.3 Interference Avoidance

The WSN (based on ZigBee nodes) functions on the basis of IEEE 802.15.4 regula- tions in 2.4GHz frequency band. The 2.4GHz is considered as unlicensed ISM band and hence shared by other technologies like Wi-Fi and Bluetooth. The domestic ap- plications like microwave oven and cordless phone will be emitting radiation in same 2.4GHz band. Though IEEE 802.15.4 have provided some mechanisms like Low duty cycle, Channel assignment, clear channel assignment, still there is a need for better mechanisms to avoid interference because of its dynamic nature. Among potential in- terferers, the effects of IEEE 802.11(Wi-Fi) is considered as high for WSN. WiFi has become essential at buildings and offices mainly for Internet connection.

1.3.4 Energy Consumption

The sensor node operations like sensing, logical computation, routing, and communica- tion with other nodes, are the important functions of the node(appliance) in the network. The wireless node is equipped with the battery, and for all the above operations the en- ergy is consumed. Hence systematic power control techniques need to be implemented for efficient power management of node for assuring prolonged life of a node and indeed network. Thus, there is a demand for the energy efficient protocols for the WSN.

1.3.5 Interoperability

The SG covers various sensor, actuators and intelligent devices for its efficient oper- ations for energy management. The intelligent electronic devices play a key role in communicating the data from the end-user to utility-center and vice-versa. Hence there is a need for standard communication protocols to support the interoperability among different technologies to serve a common purpose i.e, to support the SG environment.

1.3.6 Memory Management

The sensor nodes are equipped with very little memory and hence there is a need for the efficient memory management for hassle free operations. The algorithms must support proper battery management, processing power so that the processing can be faster and reliable in SG environment. Hence there is a need for lightweight protocols.

1.3.7 Security

The SG environment deals with very important, sensitive and restricted data so ensure the security of the data being transmitted from the smart appliances to smart meters to utility centers. Security is an important issue so as to secure the data transmission that finds threat because of DoS (Denial of Service) attacks reported earlier. There are also some attacks need to be addressed keeping in the view of SG platform deployment strategies, different communication systems, and type of SG applications. Hence there is a need for securing the data between source-to-destination and need to be imple- mented specifically on WSN-based SG applications.

1.3.8 Heterogeneous system conditions

The WSN based SG applications deals with different complex and dynamic conditions. Hence single communication technology cannot handle the different type of applica- tions keeping in the view of flexibility, security, cost-effective and reliability. There is a need of combination of different communication technologies and should be having better interoperability fulling the conditions of SG.



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coexisting avoiding




Title: Coexisting problems for wireless sensor networks working in 2.4 GHz frequency band