Novel congestion avoidance scheme for Internet of Drones
Introduction
Internet of Drones (IoDs) comprises of a number of drones that can communicate to share information by reporting an event at certain region [1]. Drones are aircrafts which are capable to fly without passengers [2]. In IoDs, drones perform a collision free navigation through planned route among nodes [1], [3], [4]. There are many applications for IoDs where drones share the packet delivery, traffic or security surveillance, accident detection, inspection of agriculture, emergency and rescue [1], [4], [5], privacy and security [5], [6]. Under IoTs, growing rate of drones may lead to congestion during communication. IoDs is a dynamic communication network that allows to control air space and provide navigation services among nodes. These nodes are at various locations to transmit continuous information about their current position and future path [5]. The intensive use of IoDs results into communication and computation constraints such as security and congestion during communication [6], [7]. The information can be sensitive and critical about any emergency event. Drones transmits messages among drones for communication. These continuous transmitted messages or packets among drones causes congestion.
Congestion is a challenging issue for IoDs during information dissemination. To deal with this issue, a few of the existing approaches depend on hosts transmit smart amount of messages and control bandwidth [1]. Host drone is an initiator that start transmitting messages about an event. A limited research is done for congestion during communication for IoDs. Most of the previous congestion avoidance approaches deals with air traffic control. These approaches are not useful in context of IoDs due to scalability and variety in applications. With the growing number of drones, IoDs need to be explored for various applications [4], [8].
Unmanned Ariel vehicles (UAV) are needed to update main server where congestion is a challenging issue in IoDs environment. These UAVs may update main server regularly for delivering Emergency messages (EMs) about nearby accident, jam traffic, storm or foggy weather ahead [1], [3]. In such cases, the initiator drone does not stop to broadcasting messages till rescue team is not arrived. It turns out to be worse when the nearby passing drones also keep on overflowing EMs causes message overhead. The UAVs involve multi-hop message that may end in storm and hence congestion. It causes packet loss, low latency energy overhead and delay in sharing messages [8], [9], [10], [11]. Timely packet delivery is challenging in communication by avoiding terrible consequences and congestion. This problem is raised in [11], [12] but need to explore for reliable communication. Therefore, congestion avoidance schemes are quite essential in IoDs. Now, fog computing is an innovative area of edge computing which is used to deal with issues like latency, location tracking, information distribution and mobility [13], [14]. It computes at network edges in distribution manner by sharing computation workload [15], [16]. Fog servers are positioned locally in order to handle computation at local level. Smart nodes help to access fog server by using different access networks like wireless access points [17]. The architectural design of fog computing gives various features such as resource distribution, services to user and fast computational capability is illustrated in Fig. 1. Moreover, fog assisted congestion avoidance scheme for internet of vehicles is presented in [18], [19] where E2MD reduces congestion by involving smart vehicles and un-equipped vehicles. There is a limitation that E2MD only works for defined smart vehicles having internet access and wireless points.
This paper presents a fog-based congestion avoidance approach using drones for Smooth Message Dissemination (SMD). It assists to escape congestion and share messages among drones for reliable communication in a timely manner. It demands a group of suitable drone which may have short distance to fog server and inform in its one-hop circle. It can stop forwarding message as it has delivered the message to fog server. Afterwards fog server is responsible to inform petroleum services to deal with emergency scenarios. It confirms message delivery and timely intimation of emergency events. SMD opts local distribution feature of fog computing. The main contribution of our work are as follows;
- (1)
We categorized the schemes for IoDs and then explored the congestion avoidance schemes. A summary of these schemes is also presented in tabular format.
- (2)
We propose SMD scheme for congestion avoidance using drone networks for emergency scenarios including road accidents, earth quake and flood.
- (3)
Next, a message forwarding algorithm is proposed to select the next-hop drone from the suitable layer. The drone in a layer near to fog node is considered to be more suitable.
- (4)
Finally, we validate our work through extensive simulations in NS 2.35 where TCL is used for nodes deployment, mobility and message initiation. C language is used to implement send, receive and proposed algorithm.
Rest of the article is organized as follows; Section 2 presents the system model and problem statement. Literature review is explored in Section 3. In Section 4, we present the proposed SMD scheme having an algorithm for suitable next-hop drone selection. Section 5 presents the results and analysis. Section 6 concludes our work and indicate future directions.
Section snippets
Literature review
Congestion assisted approaches in drones are explained in this Section. All these schemes are cataloged under various groups. We have evaluated the schemes in literature to present a summary of congestion based schemes using drone’s networks.
System model and problem statement
System model of this paper lies on Emergency scenarios where emergency information need to spread. Emergency information can be pictures of accidents or gases sensed by the integrated drone sensors. N-heterogeneous autonomous adaptive objects take action at each step [14]. Besides the many benefits of drones, such as marketing, agriculture, science etc, UAV are being used as aerial based stations in the wireless sensor networks. Sensory devices have evolved from stationary environmental to
Smooth messade dissemination scheme
In this Section, we present the Smooth Message Dissemination (SMD) scheme that can handle the congestion scenario using drone network. In smart cities, drones are capable of quick identification of emergency and timely reporting to alert the rescue teams. In this case, delays can occur if the rate of packets exceeds the limit and make congestion. An ideal situation would be if there is no delay, then packets are delivered timely. On the contrary, excessive message transmission cause congestion.
Results and analysis
We performed simulations using NS2.35 to validate proposed scheme. Tool Command Language (TCL) is used for mapping and message starting for node at different intervals of time especially in emergency scenarios. Trace file is an outcome of running simulation. This trace file consists of related information about sent and receive packets along with properties. There is an awk file like PERL. Formula for any script is to be written in awk file whereas extract result from trace file. For simulation
Conclusion
IoDs is a network of drones used for smooth communication in air traffic. Message congestion occurs due to repeated or excessive message transmissions. This congestion causes packet drop that may hinder timely delivery of message. To address this issue, this paper proposed SMD scheme that presents the layered architecture for communication from drones to higher servers and repositories at fog and cloud. We present a MFA-CA algorithm that ensures to select the best suitable nodes in the layer
CRediT authorship contribution statement
Shumayla Yaqoob: Conceptualization, Data curation, Formal analysis, Investigation, Software, Visualization, Writing - original draft. Ata Ullah: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Supervision, Validation, Visualization, Writing - original draft, Writing - review & editing. Muhammad Awais: Formal analysis, Investigation, Methodology, Project administration, Resources, Supervision, Writing - original draft, Writing -
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
This work is partially funded by FCT/MCTES, Portugal through national funds and when applicable co-funded EU funds under the Project UIDB/50008/2020; and by Brazilian National Council for Scientific and Technological Development - CNPq, via Grant No.309335/2017-5. This research was funded by the Deanship of Scientific Research (DSR) at the King Abdulaziz University, Jeddah, under grant number RG-10-611-38.
Shumayla Yaqoob received MCS and MS(Computer Science) degrees in 2014 and 2018 respectively from NUML Islamabad Pakistan. She has published several papers in ISI indexed impact factor journals and international conferences. Her research interest includes Vehicular IoTs, Cyber Security, Artificial Intelligence based games and Media files conversion.
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Shumayla Yaqoob received MCS and MS(Computer Science) degrees in 2014 and 2018 respectively from NUML Islamabad Pakistan. She has published several papers in ISI indexed impact factor journals and international conferences. Her research interest includes Vehicular IoTs, Cyber Security, Artificial Intelligence based games and Media files conversion.
Ata Ullah received the B.S. and M.S. degrees in computer science from COMSATS University Islamabad, Pakistan, in 2005 and 2007, respectively, and the Ph.D. degree in computer science from International Islamic University Islamabad (IIUI), Pakistan, in 2016. He is Asst. Prof/Head ITCON at National University of Modern Languages (NUML), Islamabad, Pakistan since 2008. He was at USTB, China during 2017–18. His areas of interest include WSN, IoT, IoV and MANET.
Dr. Muhammad Awais is a Senior Lecturer at Edge Hill University, UK. Previously he was research Fellow in Data Analytics and AI at University of Leeds and University of Hull. His research interests are in data mining, signal processing, applied machine learning and deep learning to develop ICT based systems for remote sensing, Internet of things, Industry 4.0 analytics, biomedical and health care domain.
Iyad Katib (Member, IEEE) is an Associate Professor with the Computer Science Department and the current Vice Dean and the College Council Secretary of the Faculty of Computing and Information Technology (FCIT) in King Abdulaziz University (KAU). He is also the Director of KAU High Performance Computing Center. Iyad received his Ph.D. and MS degrees in Computer Science from University of Missouri-Kansas City in 2011 and 2004.
Aiiad Albeshri received M.S. and Ph.D. degrees in Information Technology from Queensland University of Technology, Brisbane, Australia in 2007 and 2013 respectively. He has been an assistant professor at the Computer Science Department of the King Abdulaziz University, Jeddah, Saudi Arabia since 2013. His current research focuses on Security and Trust in Cloud computing and big data.
Rashid Mehmood (Senior Member, IEEE) is the Research Professor of Big Data Systems and the Director of Research, Training, and Consultancy at the High Performance Computing Centre, King Abdulaziz University, Saudi Arabia. He has gained qualifications and work experience from universities in the UK including Cambridge and Oxford Universities.
Dr Mohsin Raza is Senior Lecturer at Edge Hill University, UK. Prior to this, he worked as a lecturer (2019–20) at Northumbria University, UK, post-doctoral fellow (2018–19) at Middlesex University, UK, Junior lecturer (2010–12) and later as Lecturer (2012–15) in at Mohammad Ali Jinnah University, Pakistan, and Hardware Engineer (2009–10) at USS, Pakistan. His research interests include IoT, 5G, ITS, machine learning, Industry 4.0 and digital twins.
Saif ul Islam received his Ph.D. in Computer Science at the University Toulouse III Paul Sabatier, France in 2015. He is Assistant Professor at the Department of Computer Science, KICSIT, Institute of Space Technology (IST). His research interests include resource and energy management in large-scale distributed systems (Edge/Fog, Cloud, Content Distribution Network) and Internet of Things.
Joel J. P. C. Rodrigues [S’01, M’06, SM’06, F’20] is a professor at the Federal University of Piauí, Brazil; senior researcher at the Instituto de Telecomunicações, Portugal; and collaborator of the Post-Graduation Program on Teleinformatics Engineering at the Federal University of Ceará (UFC), Brazil. He is the leader of the Next Generation Networks and Applications (NetGNA) research group (CNPq), an IEEE Distinguished Lecturer, Member Representative of the IEEE Communications Society on the IEEE Biometrics Council. He was Director for Conference Development - IEEE ComSoc Board of Governors, a Past-Chair of the IEEE ComSoc TCs on eHealth and on Communications Software, and Steering Committee member of the IEEE Life Sciences Technical Community. He is the editor-in-chief of the International Journal on E-Health and Medical Communications and editorial board member of several journals. He has authored or coauthored over 950 papers in refereed international journals and conferences, 3 books, 2 patents, and 1 ITU-T Recommendation.