Transport Layer for Cognitive Radio Sensor Networks

Efficient Delivery ◽

New Directions

The transport layer is responsible for reliable and energy-efficient delivery of packets from source to destination. Since Cognitive Radio Sensor Network (CRSN) is an emerging technology, there is a need to develop efficient transport layer protocols for it. Therefore, the main goal of this chapter is to provide design guidelines and highlight design issues and challenges of transport protocols for cognitive radio sensor networks. In this chapter, the authors provide a foundation for development of new transport protocols for cognitive radio sensor networks by presenting characteristics and major existing schemes of traditional transport protocols. Additionally, they provide design guidelines and challenges for the development of transport protocols for cognitive radio sensor networks including a guideline on simulation ground for transport protocols. In summary, this chapter is an initial step towards new directions of research and development of transport protocols for cognitive radio sensor networks.

Advances in Wireless Technologies and Telecommunication - Cognitive Radio Sensor Networks ◽

Cognitive Radio Sensor Networks

10.4018/978-1-4666-6212-4.ch007 ◽

2014 ◽

pp. 160-195 ◽

Cited By ~ 2

Author(s):

Ejaz Ahmed ◽

Salman Ali ◽

Adnan Akhunzada ◽

Ibrar Yaqoob

Keyword(s):

Cognitive Radio ◽

Sensor Networks ◽

Sensor Network ◽

Ad Hoc ◽

Network Communication ◽

Ad Hoc Routing ◽

Medium Access ◽

Network Operation

This chapter provides a review of design practices in network communication for Cognitive Radio Sensor Networks. The basics of networking and Medium Access Control functionalities with focus on data routing and spectrum usage are discussed. Technical differences manifest in various network layouts, hence the role of various specialized nodes, such as relay, aggregator, or gateway in Cognitive Radio Sensor Networks need analysis. Optimal routing techniques suitable for different topologies are also summarized. Data delivery protocols are categorized under priority-based, energy-efficient, ad hoc routing-based, attribute-based, and location-aware routing. Broadcast, unicast, and detection of silence periods are discussed for network operation with slotted or unslotted time. Efficient spectrum usage finds the most important application here involving use of dynamic, opportunistic, and fixed spectrum usage. Finally, a thorough discussion on the open issues and challenges for Cognitive Radio Sensor Network communication and internetworking in Cognitive Radio Sensor Network-based deployments and methods to address them are provided.

Advances in Wireless Technologies and Telecommunication - Cognitive Radio Sensor Networks ◽

Spectrum Sensing in Cognitive Radio Sensor Networks

10.4018/978-1-4666-6212-4.ch003 ◽

2014 ◽

pp. 48-72 ◽

Cited By ~ 1

Author(s):

Farooq Alam ◽

Zahooruddin ◽

Ayaz Ahmad ◽

Muhammad Iqbal

Keyword(s):

Wireless Sensor Networks ◽

Cognitive Radio ◽

Sensor Networks ◽

Spectrum Sensing ◽

Wireless Sensor ◽

Research Issues ◽

Comprehensive Review ◽

Core Issues

In this chapter, the authors provide a comprehensive review of spectrum sensing in cognitive radio sensor networks. Firstly, they focus on general techniques utilized for spectrum sensing in wireless sensor networks. To have good understanding of core issues of spectrum sensing, the authors then give a brief description of cognitive radio networks. Then they give a thorough description of the main techniques that can be helpful in doing spectrum sensing in cognitive radio sensor network. The authors conclude this chapter with open research issues and challenges that need to be addressed to provide efficient spectrum sensing in order to minimize the limitations in cognitive radio sensor networks.

Energy-efficient distributed heterogeneous clustered spectrum-aware cognitive radio sensor network for guaranteed quality of service in smart grid

International Journal of Distributed Sensor Networks ◽

10.1177/15501477211028399 ◽

2021 ◽

Vol 17 (7) ◽

pp. 155014772110283

Author(s):

Emmanuel Ogbodo ◽

David Dorrell ◽

Adnan Abu-Mahfouz

Keyword(s):

Quality Of Service ◽

Cognitive Radio ◽

Sensor Networks ◽

Smart Grid ◽

Sensor Network ◽

Smart Grids ◽

Guaranteed Quality

The development of a modern electric power grid has triggered the need for large-scale monitoring and communication in smart grids for efficient grid automation. This has led to the development of smart grids, which utilize cognitive radio sensor networks, which are combinations of cognitive radios and wireless sensor networks. Cognitive radio sensor networks can overcome spectrum limitations and interference challenges. The implementation of dense cognitive radio sensor networks, based on the specific topology of smart grids, is one of the critical issues for guaranteed quality of service through a communication network. In this article, various topologies of ZigBee cognitive radio sensor networks are investigated. Suitable topologies with energy-efficient spectrum-aware algorithms of ZigBee cognitive radio sensor networks in smart grids are proposed. The performance of the proposed ZigBee cognitive radio sensor network model with its control algorithms is analyzed and compared with existing ZigBee sensor network topologies within the smart grid environment. The quality of service metrics used for evaluating the performance are the end-to-end delay, bit error rate, and energy consumption. The simulation results confirm that the proposed topology model is preferable for sensor network deployment in smart grids based on reduced bit error rate, end-to-end delay (latency), and energy consumption. Smart grid applications require prompt, reliable, and efficient communication with low latency. Hence, the proposed topology model supports heterogeneous cognitive radio sensor networks and guarantees network connectivity with spectrum-awareness. Hence, it is suitable for efficient grid automation in cognitive radio sensor network–based smart grids. The traditional model lacks these capability features.