User-centric plug-and-play functionality for IPv6-enabled wireless sensor networks

“Copyright © [2010] IEEE. Reprinted from 2010 IEEE International Conference on Communications. ISBN:978-1-4244-6402-9. This material is posted here with permission of the IEEE. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.”Smart nodes that sense the environment and communicate wirelessly to reach a sink node create wireless sensor networks. One of the main research challenges regarding wireless sensor networks is user deployment, namely in terms of configuration and management. On non-commercial solutions the user typically must be aware of the underlying technology to obtain sensing services. Internet connectivity is also desirable, so future deployments must take into consideration this feature, enabling realistic ubiquitous computing. This paper presents a user-centric solution for IPv6-enabled wireless sensor networks, using the Contiki operating system and Crossbow TelosB motes, featuring a Plug-and-Play like experience. One of the motes provides sink node capability to the network, through USB connection with a personal computer, which sends and receives data, presenting it to the user. A dedicated serial protocol for USB communication with the sink was developed and extensively debugged, featuring sink querying and network configuration. The current testbed uses User Datagram Protocol over IPv6, with 6LoWPAN, and IEEE 802.15.4 wireless communication between the sensor network motes and the sink device. A Plug-and-Play like operation is achieved through zero-user configuration, since the user only needs to plug in the sink and give power to the remote motes

Security in 5G-Enabled Internet of Things Communication: Issues: Challenges, and Future Research Roadmap

5G mobile communication systems promote the mobile network to not only interconnect people, but also interconnect and control the machine and other devices. 5G-enabled Internet of Things (IoT) communication environment supports a wide-variety of applications, such as remote surgery, self-driving car, virtual reality, flying IoT drones, security and surveillance and many more. These applications help and assist the routine works of the community. In such communication environment, all the devices and users communicate through the Internet. Therefore, this communication agonizes from different types of security and privacy issues. It is also vulnerable to different types of possible attacks (for example, replay, impersonation, password reckoning, physical device stealing, session key computation, privileged-insider, malware, man-in-the-middle, malicious routing, and so on). It is then very crucial to protect the infrastructure of 5G-enabled IoT communication environment against these attacks. This necessitates the researchers working in this domain to propose various types of security protocols under different types of categories, like key management, user authentication/device authentication, access control/user access control and intrusion detection. In this survey paper, the details of various system models (i.e., network model and threat model) required for 5G-enabled IoT communication environment are provided. The details of security requirements and attacks possible in this communication environment are further added. The different types of security protocols are also provided. The analysis and comparison of the existing security protocols in 5G-enabled IoT communication environment are conducted. Some of the future research challenges and directions in the security of 5G-enabled IoT environment are displayed. The motivation of this work is to bring the details of different types of security protocols in 5G-enabled IoT under one roof so that the future researchers will be benefited with the conducted work

IoMT Malware Detection Approaches: Analysis and Research Challenges

The advancement in Information and Communications Technology (ICT) has changed the entire paradigm of computing. Because of such advancement, we have new types of computing and communication environments, for example, Internet of Things (IoT) that is a collection of smart IoT devices. The Internet of Medical Things (IoMT) is a specific type of IoT communication environment which deals with communication through the smart healthcare (medical) devices. Though IoT communication environment facilitates and supports our day-to-day activities, but at the same time it has also certain drawbacks as it suffers from several security and privacy issues, such as replay, man-in-the-middle, impersonation, privileged-insider, remote hijacking, password guessing and denial of service (DoS) attacks, and malware attacks. Among these attacks, the attacks which are performed through the malware botnet (i.e., Mirai) are the malignant attacks. The existence of malware botnets leads to attacks on confidentiality, integrity, authenticity and availability of the data and other resources of the system. In presence of such attacks, the sensitive data of IoT communication may be disclosed, altered or even may not be available to the authorized users. Therefore, it becomes essential to protect the IoT/IoMT environment from malware attacks. In this review paper, we first perform the study of various types of malware attacks, and their symptoms. We also discuss some architectures of IoT environment along with their applications. Next, a taxonomy of security protocols in IoT environment is provided. Moreover, we conduct a comparative study on various existing schemes for malware detection and prevention in IoT environment. Finally, some future research challenges and directions of malware detection in IoT/IoMT environment are highlighted

Efficient scheduling of video camera sensor networks for IoT systems in smart cities

© 2019 John Wiley & Sons, Ltd. Video camera sensor networks (VCSN) has numerous applications in smart cities, including vehicular networks, environmental monitoring, and smart houses. Scheduling of video camera sensor networks (VCSN) can reduce the computational complexity, increase energy efficiency, and enhance throughput for the Internet of things (IoT) systems. In this paper, we apply the iterative low-complexity probabilistic evolutionary method for scheduling video cameras to maximize throughput in VCSNs for IoT systems. Scheduling of video cameras in VCSNs to maximize throughput is a combinatorial optimization problem whose computational complexity increases exponentially with the increase in the number of video cameras. We propose an iterative probabilistic method named as cross-entropy optimization (CEO), which is an evolutionary algorithm. The combinatorial optimization problems can be solved using the CEO which is a generalized Monte Carlo technique. The proposed method updates its selected population (video cameras) at each iteration based on the Kullback Leibler (KL) distance/divergence. The KL distance/divergence is minimized using the probability distribution obtained from the learned from the group of selected samples of better solutions found in the previous iterations. The effectiveness of the CEO is verified in terms of optimality and simplicity through simulations. In addition, the results of the CEO are better than the suboptimal algorithms (ie, best norm-based algorithm, genetic algorithm, and capacity upper-bound–based greedy algorithm) and maximum of 2%-3% deviation from the exhaustive search (optimal) with less complexity. The trade-off between CEO and optimal is the computational complexity

ASCP-IoMT: AI-Enabled Lightweight Secure Communication Protocol for Internet of Medical Things

The Internet of Medical Things (IoMT) is a unification of smart healthcare devices, tools, and software, which connect various patients and other users to the healthcare information system through the networking technology. It further reduces unnecessary hospital visits and the burden on healthcare systems by connecting the patients to their healthcare experts (i.e., doctors) and allows secure transmission of healthcare data over an insecure channel (e.g., the Internet). Since Artificial Intelligence (AI) has a great impact on the performance and usability of an information system, it is important to include its modules in a healthcare information system, which will be very helpful for the prediction of some phenomena, such as chances of getting a heart attack and possibility of a tumor, from the collected and analysed healthcare data. To mitigate these issues, in this paper, a new AI-enabled lightweight, secure communication scheme for an IoMT environment has been designed and named as ASCP-IoMT, in short. The security analysis of ASCP-IoMT is performed in different ways, such as an informal way and a formal way (through the random oracle model). ASCP-IoMT performs better than other similar schemes and provides superior security with extra functionality features as compared those for the existing state of art solutions. A practical implementation of ASCP-IoMT is also performed in order to measure its impact on various network performance parameters. The end to end delay values of ASCP-IoMT are 0.01587, 0.07440 and 0.17097 seconds and the throughput values of ASCP-IoMT are 5.05, 10.88 and 16.41 bits per second (bps) under the different considered cases, respectively. For AI-based Big data analytics phase, the values of computation time (seconds) for decision tree, support vector machine (SVM), and logistic regression are measured as 0.19, 0.23, and 0.27, respectively. Moreover, the different values of accuracy for decision tree, SVM and logistic regression are 84.24%, 87.57%, and 85.20%, respectively. From these values, it is clear that decision tree method requires less time than the other considered techniques, whereas accuracy is high in case of SVM

Planning Fog networks for time-critical IoT requests

The massive growth of the Internet of Things (IoT) applications and the challenges of Cloud computing have increased the importance of Fog networks for timely processing the requests from delay-sensitive applications. A Fog network provides local aggregation, analysis, and processing of IoT requests that may or may not be time-critical. One of the major issues of Fog is its capacity planning considering the traffic load of time-critical requests. The response time can be huge if a time-critical request is processed on Cloud. The response time of a time-critical request can be big on the Fog layer if it is not prioritized. Hence, there is a need to handle the time-critical traffic on a priority basis at the Fog layer. In this paper, a priority queuing model with preemption has been proposed considering the mixed types of requests at the Fog layer. The proposed approach determines the required number of Fog nodes in order to satisfy the desired Quality of Service (QoS) requirements of IoT requests. The proposed mechanism is evaluated through simulations using the iFogSim simulator. The work can be used in the capacity planning of Fog networks

Vehicular delay-tolerant networks – an overview

Vehicular Delay-Tolerant Networks (VDTNs) are a networking paradigm based on concepts of Delay-Tolerant Networks (DTNs) and Opportunistic Networks. Opportunistic contacts, intermittent connectivity, frequent network partition, long propagation delays and no contemporaneous end-to-end paths characterize VDTNs. VDTNs have been proposed to interconnect developing communities, or to implement disaster recovery networks when all other networks fail. Other possible application scenarios for these networks include traffic monitoring, accident warnings, advertisements, or data gathering applications. The diversity of these network environments introduces challenging issues related to the architecture, protocols design, interoperability, security, management, and stability of VDTNs. This communication starts with the presentation of VDTNs architecture. In the sequence, it focuses on problems that arise from low network node density and missed transmission opportunities, vehicle movement models, constrained network resources on routing strategies, and scheduling and drop policies.info:eu-repo/semantics/publishedVersio

Exploring blind online scheduling for mobile cloud multimedia services

Mobile cloud is a new emerging technology which can be used to enable users to enjoy abundant multimedia applications in a pervasive computing environment. Therefore, the scheduling of massive multimedia flows with heterogeneous QoS guarantees becomes an important issue for the mobile cloud. Generally, the predominant popular cloud-based scheduling algorithms assume that the request rate and service time, are available for the system operator. However, this assumption can hardly be maintained in many practical scenarios, especially for the largescale mobile cloud. In this article, we consider the scheduling problem for a practical mobile cloud in which the above parameters are unavailable and unknown. Taking into account the performance of the users and the impartial free time among the servers, the highlight of this article lies in proposing a blind online scheduling algorithm (BOSA). Specifically, we assign available multimedia servers based on the last timeslot information of the users' requests, and route all the multimedia flows according to the firstcome- first-served rule. Moreover, we design detailed steps to apply the BOSA to a content recommendation system, and show that the proposed BOSA can achieve asymptotic optimality. 2013 IEEE.Scopus2-s2.0-8489776548