Cognitive radio for M2M and Internet of Things: A survey
Introduction
Imagine a scenario, where our alarm clocks tell the curtains when to open and the coffee-maker when to start preparing the morning coffee and the car to start melting the ice gathered in overnight snow storms; our refrigerators text us grocery lists, our washing machines text us when a load of laundry is done and our doctors update the prescriptions using data beamed from tiny sensors attached to our bodies. All this will be a reality through the Internet of Things (IoT) in the near future, where almost all the things will communicate with each other and develop their own intelligence. According to forecasts from Cisco Systems, by 2020 (see Fig. 1), the Internet will consist of over 50 billion connected things including televisions, cars, kitchen appliances, surveillance cameras, smart-phones, utility meters, cardiac monitors, thermostats, and almost anything that we can imagine [1]. In tune with these figures, Cisco projects $14.4 trillion profits for the IoT technology industry globally, in the next decade [2], with the IoT connecting everyday things (e.g., keys, refrigerators, washing machines), pets, energy grids, healthcare facilities, and transportation systems to the Internet as illustrated in Fig. 2.
The concept of the Internet of Things (IoT) [3], [4], [5], [6], [7], [8], [9], [10], [11] has captured the attention of people and research community worldwide with a vision of extending Internet connectivity to a large number of “things” in the physical world. This will in turn transform our ability to interact with real-world objects, process information, and make decisions in addition to saving us time and money. In general, the IoT represents the next phase of the Internet in which virtually everything will be on the Internet. Each day, the number of objects connected to the Internet is increasing multi-fold and the penetration of connected objects in total things in the world is expected to reach 2.7% in 2020 from 0.6% in 2012 (see Fig. 1) [1]. Recently, Cisco launched the IoE (Internet of Everything) connections counter that tracks the number of things in real-time as things come online. According to the forecasts [12] on the potential economic impact of the IoT, for every person living on earth, there will be at least 2 “things” by 2020. The adoption of emerging M2M (Machine to Machine) technologies that are defined as technologies that connect machines, devices, and objects to the Internet, transforming them into “intelligent” assets that can communicate will eventually accelerate the growth of the IoT. There will be 11.6 billion mobile-connected devices by 2020, including M2M modules exceeding the world’s projected population at that time (7.8 billion). Globally, M2M connections are projected to grow from 604 million in 2015 to 3.1 billion by 2020 resulting in M2M traffic flows forming a huge share of the whole Internet traffic in the coming years [13]. The market segment specific surveys [12] on the IoT adoption project manufacturing and healthcare as the largest IoT market segments. In particular, Oil&Gas as a subsegment of manufacturing is currently leading the IoT adoption along with the energy sector as well as applications in mobility and transportation. Within consumer-facing applications, Home automation (smart thermostats, security systems, and refrigerators) is expected to dominate the market in the next years.
The application of IoT products and services will pervade every sector and industry from smart home and smart city, education, healthcare, manufacturing, mining, oil and gas, energy, utilities, commerce, transportation, surveillance, infrastructure management, to supply chain and logistics. In general, the opportunities presented by the IoT are endless and its full potential will be realised in near future with more and more devices getting connected to the Internet.
Though the concept of IoT has been in existence since 1999 [11], it is now becoming a reality thanks to the availability of tiny low-power and low-cost devices (e.g., sensors, actuators, RFID tags, low power tiny computers) as well as emergence of new advanced enabling technologies and protocols (e.g., M2M, WSN, RFID, cognitive radio, IPv6, 6LoWPAN, RPL, CoAP). Low-cost sensors and communication modules enable embedding Internet connectivity into billions of devices economical. The IPv6 protocol, the new version of IP with a large address space (2128 addresses) will provide identification/addresses for virtually all connected objects worldwide. The enabling technologies like M2M communications facilitate the implementation and deployment of numerous IoT applications. Furthermore, growing wireless networks and wireless sensor networks (WSNs) provide a way to communicate data to and from “things” with efficiency and reliability. The availability of a large number of development platforms also make it easier for the potential users to develop their own application software. The standardization bodies are addressing the issue of interoperable protocol stacks and open standards for the practical realization of IoT. Currently, there is a good momentum on IoT standardisation as well as the IoT workshops facilitating interoperability testing events to reach consensus on IoT standards development [14]. The IoT is a popular buzzword in the computing industry; it appears in the marketing campaigns of major networking companies such as Cisco and microprocessor giants such as Intel. Moreover, it serves as the theme of conferences, such as the “Internet of Things” World Forum [15]. In order to realize the successful IoT deployment, the IETF working groups such as 6lo [16], ROLL [17], 6TiSCH [18] are developing standards to allow seamless integration of low-power wireless networks into the Internet, by proposing mainly solutions for address assignment and routing. At the same time, the 3rd Generation Partnership Project (3GPP) has been working toward supporting M2M applications on 4G mobile networks, such as UMTS, and LTE/LTE-A, with the goal of eventually embedding M2M communications in the future 5G systems. Palattella et al. [3] overview the modern IoT connectivity landscape and describe the potential technologies for enabling a global IoT in the emerging 5G era.
The diversity of current and emerging IoT applications make IoT an attractive domain to the researchers as well as the industry. Numerous IoT applications are being deployed and the number will further increase rapidly in the Future Internet. The current and emerging technologies (including Wi-Fi/IEEE802.11 [19], 3G/4G mobile networks and 5G in the future [20], [21], [22], HSDPA [23], LTE/LTE-A [21], ZigBee [24], Z-Wave [25], Bluetooth Low Energy 4.0 [26], [27], and other IEEE 802.15.4 standards [28], [29]), which implement IoT applications, all operate in non-license ISM bands that are becoming congested. Consequently, new challenges have arisen to deal with the management and usage of the spectrum resources for an efficient and effective realization of IoT. Since, the IoT will be a part of the Future Internet, covering almost all different kinds of domains, industry and sectors, it will generate enormous wireless access data including machine to machine communication as well as machine to human communication. Thus, if not addressed, the shortage of spectrum resources might become the bottleneck of the IoT’s development in the recent future. In IoT, it will be a high priority to ensure that there is sufficient spectrum to handle the traffic with billions of new wireless nodes being connected to the Internet.
The IoT can benefit by using the emerging CR technology to enable more efficient radio spectrum usage. With IoT becoming a reality, ever-increasing demands for spectral resources results in overcrowding in ISM bands while spectrum utilization measurements over the years have indicated many unused or underused licensed bands over different space and time, for example, spectrum bands for TV broadcasting, resulting in considerable spectrum wastage [30], [31], [32]. This has prompted the regulatory agencies, such as Federal Communications Commission (FCC) [33] to open the licensed bands to unlicensed/secondary users through the use of CR [34], [35], [36], [37], [38], [39], [40]. CR is an emerging technology to improve the spectrum usage and alleviate the spectrum scarcity that exploits underused spectral resources by reusing the unused spectrum in an opportunistic manner. Along similar lines, the IEEE has created the IEEE 802.22 WRAN working group [41], [42] to develop a standard for a cognitive radio-based network for non-interfering opportunistic secondary access in TV whitespaces (TVWS). The research community has adopted CR for dynamic radio spectrum management to enhance spectrum usage, e.g., in ISM bands and as secondary users in unused TV bands. Moreover, several companies, such as Motorola, Philips, Qualcomm, are now investing in the development of CR technology [43]. Recently, the European Research Cluster on the Internet of Things (IERC) has provided the roadmap on standardization for IoT technologies [44]. One of the IERC projets, namely RERUM [45] is working on adapting CR on the IoT devices. The focus is on investigating the adaptation of CR technology in smart objects to minimize wireless interference and ensure the “always connected” concept.
The advanced capabilities of cognitive radio that include spectrum sensing, awareness of its surroundings, learning and self-adapting allow to maintain efficient communication in an opportunistic manner. The CR technology can automatically detect and learn from radio environment, adapt the transmission parameters in real-time, multi-dimensionally share the wireless spectrum in space, time, frequency, modulation mode, thereby improving the spectrum efficiency. Cognitive radio and cognitive radio networking (CRN) are considered as key IoT enabling technologies and their integration with future IoT architectures and services is expected to empower the IoT paradigm. Overall, the cognitive and self-organization capabilities and reconfigurable nature of CR along with the advances brought about by CR technologies will drive and enable an efficient IoT. In view of this, we survey the cognitive radio approaches and challenges for M2M and IoT. The rest of the paper is structured as follows. In Section 2, we identify various challenges and requirements of the IoT paradigm followed by current and emerging technologies that enable IoT in Section 3. Section 4, introduces CR as a promising enabler for M2M and IoT and describes the architectural and operational aspects of cognitive radio and cognitive radio networking followed by emerging IoT and M2M applications with CR. Section 5 and 6 discuss recent advances in CR and summarize how CR will empower IoT respectively. Section 7 identifies open research challenges. Finally, we conclude in Section 8. It is noteworthy to mention that though there exist some surveys treating common aspects of CR, the novelty of our survey lies in that we present recent advances and ongoing research directions in cognitive radio from 2013 to 2015 as well as previous work, in the context of M2M and IoT.
Section snippets
Challenges and requirements
We are experiencing a novel evolution with Internet of things towards a global communication infrastructure, supporting new services, and consequently, significant economical, industrial and societal impacts are expected.
However, if IoT offers many advantages then at the same time it poses new challenges. A combined initiative between Carnot Institutes and industry (Orange, Alcatel Lucent, Thales etc.,) identified some of the technical and applicative challenges for Smart networked objects and
Enabling technologies and protocols for IoT
IoT presents a huge potential for enabling diverse applications thanks to the support provided by the emergence of advanced technologies and protocols. A recent survey [6] on Internet of Things provides an overview of the latest developments in enabling technologies and protocols. This section reviews key existing technologies like RFID and WSN that support the provision of IoT services as well as emerging M2M technologies that enable the direct connectivity of “machines” to the Internet
Cognitive radio for IoT and M2M
In Section 2, we discussed some challenges posed by IoT that need to be addressed such as heterogeneity, energy efficient designs, self organisation capabilities, etc. It is interesting to note that the unique features like high flexibility and reconfigurability require advanced algorithms similar to those in cognitive radio systems. Use of opportunistic radio resource utilization based on CR can provide efficiency as well as reliability.
CR also improves spectrum efficiency. Most of the IoT
Recent advances in cognitive radio
In the previous sections, we presented motivations and potential applications for CR-IoT. In Section 2, we discussed many challenges related to IoT, such as heterogeneity, and how CR can be an enabler. The protocol stack of cognitive radio-enabled node usually has functionalities related to spectrum discovery (either through sensing or geolocation database or both), spectrum management based on learned knowledge and policies. It also has spectrum aware algorithms for MAC, routing and upper
How cognitive radio empowers Internet of Things?
In this section, we summarize the potential benefits brought to IoT by applying various mechanisms and techniques for CR discussed in Section 5 to show how CR will empower IoT.
In the beginning of Section 5, we described various parameters that are addressed or managed by CR, such as issues like autonomicity, scalability, tackling heterogeneity, energy efficiency, etc. Subsequently, in order to give a global picture of various CR approaches that can be applied in the context of IoT, we provided
Other research challenges
In the previous sections, we discussed some ongoing research directions and discussed some relevant research challenges to explore further. Here, we provide some more research challenges.
New theory on distributed multi Agents: Many aspects of CRNs are currently studied using game theory. However, as pointed out in [39], some progress needs to be made so that we can arrive to a new theory on distributed multi Agents.
Better PU activity models: Most of the works use simple ON/OFF models for PU
Concluding remarks
We are experiencing a new evolution with Internet of Things and Machine to Machine towards a global communication infrastructure, supporting new services. Consequently, significant economical, industrial and societal impacts are expected in the near future. The diversity of potential IoT applications ranging from smart and green cities, logistics, to aeronautics make IoT an attractive domain to the researchers as well as the industry. However, to support such diversity of applications and
Priyanka Rawat received the B.Tech. degree in Electrical Engineering from Indian Institute of Technology (IITD), Delhi, India. She received her Ph.D. degree in computer science from Telecom Bretagne, France in 2010. She then worked as Postdoc researcher at Telecom SudParis and at INRIA Lille. She is currently working at University of Avignon, France. Her research interests include mobile networks, wireless and sensor networks, Internet of Things, Cognitive Radio and Machine-to-Machine
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Priyanka Rawat received the B.Tech. degree in Electrical Engineering from Indian Institute of Technology (IITD), Delhi, India. She received her Ph.D. degree in computer science from Telecom Bretagne, France in 2010. She then worked as Postdoc researcher at Telecom SudParis and at INRIA Lille. She is currently working at University of Avignon, France. Her research interests include mobile networks, wireless and sensor networks, Internet of Things, Cognitive Radio and Machine-to-Machine communications in 5G, heterogeneous networks, Multi-path TCP, and QoE.
Kamal D. Singh received the B.Tech. degree in Electrical Engineering from Indian Institute of Technology (IITD), Delhi, India in 2002. He obtained his Ph.D. degree in computer science from University Rennes 1, France in 2007. He then worked as a Postdoc researcher in the Dionysos group at INRIA and at Telecom Bretagne, Rennes where he developed many components of QoE estimation tools and worked on the analysis of video-based applications. He is currently an Assistant Professor at Telecom Saint Etienne / University Jean Monnet, France. His research interests include Quality of Experience (QoE), Quality of Service (QoS), Wireless and mobile networks, Internet of Things, Wireless sensor networks and Cognitive Radio.
Jean Marie Bonnin is currently a professor and head of RSM department at Telecom Bretagne, Rennes, France. He is also a member of the IRISA / OCIF research team. He obtained his PhD degree in computer science at the university of Strasbourg in 1998. His research interests include convergence between IP networks and mobile telephony networks.