Geographical forwarding algorithm based video content delivery scheme for internet of vehicles (IoV)

This is an accepted manuscript of an article published by IEEE Multimedia Communications Technical Committee in MMTC Communications – Frontiers on 31/07/2020, available online: https://mmc.committees.comsoc.org/files/2020/07/MMTC_Communication_Frontier_July_2020.pdf The accepted version of the publication may differ from the final published version.An evolved form of Vehicular Ad hoc Networks (VANET) has recently emerged as the Internet of Vehicles (IoV). Though, there are still some challenges that need to be addressed in support IoV applications. The objective of this research is to achieve an efficient video content transmission over vehicular networks. We propose a balanced video-forwarding algorithm for delivering video-based content delivery scheme. The available neighboring vehicles will be ranked to the vehicle in forwarding progress before transmitting the video frames using proposed multi-score function. Considering the current beacon reception rate, forwarding progress and direction to destination, in addition to residual buffer length; the proposed algorithm can elect the best candidate to forward the video frames to the next highest ranked vehicles in a balanced way taking in account their residual buffer lengths. To facilitate the proposed video content delivery scheme, an approach of H.264/SVC was improvised to divide video packets into various segments, to be delivered into three defined groups. These created segments can be encoded and decoded independently and integrated back to produce the original packet sent by source vehicle. Simulation results demonstrate the efficiency of our proposed algorithm in improving the perceived video quality compared with other approache

Smart handoff technique for internet of vehicles communication using dynamic edge-backup node

© 2020 The Authors. Published by MDPI. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.3390/electronics9030524A vehicular adhoc network (VANET) recently emerged in the the Internet of Vehicles (IoV); it involves the computational processing of moving vehicles. Nowadays, IoV has turned into an interesting field of research as vehicles can be equipped with processors, sensors, and communication devices. IoV gives rise to handoff, which involves changing the connection points during the online communication session. This presents a major challenge for which many standardized solutions are recommended. Although there are various proposed techniques and methods to support seamless handover procedure in IoV, there are still some open research issues, such as unavoidable packet loss rate and latency. On the other hand, the emerged concept of edge mobile computing has gained crucial attention by researchers that could help in reducing computational complexities and decreasing communication delay. Hence, this paper specifically studies the handoff challenges in cluster based handoff using new concept of dynamic edge-backup node. The outcomes are evaluated and contrasted with the network mobility method, our proposed technique, and other cluster-based technologies. The results show that coherence in communication during the handoff method can be upgraded, enhanced, and improved utilizing the proposed technique.Published onlin

Comprehensive survey on big data privacy protection

In recent years, the ever-mounting problem of Internet phishing has been threatening the secure propagation of sensitive data over the web, thereby resulting in either outright decline of data distribution or inaccurate data distribution from several data providers. Therefore, user privacy has evolved into a critical issue in various data mining operations. User privacy has turned out to be a foremost criterion for allowing the transfer of confidential information. The intense surge in storing the personal data of customers (i.e., big data) has resulted in a new research area, which is referred to as privacy-preserving data mining (PPDM). A key issue of PPDM is how to manipulate data using a specific approach to enable the development of a good data mining model on modified data, thereby meeting a specified privacy need with minimum loss of information for the intended data analysis task. The current review study aims to utilize the tasks of data mining operations without risking the security of individuals’ sensitive information, particularly at the record level. To this end, PPDM techniques are reviewed and classified using various approaches for data modification. Furthermore, a critical comparative analysis is performed for the advantages and drawbacks of PPDM techniques. This review study also elaborates on the existing challenges and unresolved issues in PPDM.Published versio

A conditional opposition-based particle swarm optimization for feature selection

© 2021 The Authors. Published by Taylor & Francis. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1080/09540091.2021.2002266Because of the existence of irrelevant, redundant, and noisy attributes in large datasets, the accuracy of a classification model has degraded. Hence, feature selection is a necessary pre-processing stage to select the important features that may considerably increase the efficiency of underlying classification algorithms. As a popular metaheuristic algorithm, particle swarm optimization has successfully applied to various feature selection approaches. Nevertheless, particle swarm optimization tends to suffer from immature convergence and low convergence rate. Besides, the imbalance between exploration and exploitation is another key issue that can significantly affect the performance of particle swarm optimization. In this paper, a conditional opposition-based particle swarm optimization is proposed and used to develop a wrapper feature selection. Two schemes, namely opposition-based learning and conditional strategy are introduced to enhance the performance of the particle swarm optimization. Twenty-four benchmark datasets are used to validate the performance of the proposed approach. Furthermore, nine metaheuristics are chosen for performance verification. The findings show the supremacy of the proposed approach not only in obtaining high prediction accuracy but also in small feature sizes

Dynamic Reciprocal Authentication Protocol for Mobile Cloud Computing

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.A combination of mobile and cloud computing delivers many advantages such as mobility, resources, and accessibility through seamless data transmission via the Internet anywhere at any time. However, data transmission through vulnerable channels poses security threats such as man-in-the-middle, playback, impersonation, and asynchronization attacks. To address these threats, we define an explicit security model that can precisely measure the practical capabilities of an adversary. A systematic methodology consisting of 16 evaluation criteria is used for comparative evaluation, thereby leading other approaches to be evaluated through a common scale. Finally, we propose a dynamic reciprocal authentication protocol to secure data transmission in mobile cloud computing (MCC). In particular, our proposed protocol develops a secure reciprocal authentication method, which is free of Diffie–Hellman limitations, and has immunity against basic or sophisticated known attacks. The protocol utilizes multifactor authentication of usernames, passwords, and a one-time password (OTP). The OTP is automatically generated and regularly updated for every connection. The proposed protocol is implemented and tested using Java to demonstrate its efficiency in authenticating communications and securing data transmitted in the MCC environment. Results of the evaluation process indicate that compared with the existing works, the proposed protocol possesses obvious capabilities in security and in communication and computation costs

Dynamic reciprocal authentication protocol for mobile cloud computing

A combination of mobile and cloud computing delivers many advantages such as mobility, resources, and accessibility through seamless data transmission via the Internet anywhere at any time. However, data transmission through vulnerable channels poses security threats such as man-in-the-middle, playback, impersonation, and asynchronization attacks. To address these threats, we define an explicit security model that can precisely measure the practical capabilities of an adversary. A systematic methodology consisting of 16 evaluation criteria is used for comparative evaluation, thereby leading other approaches to be evaluated through a common scale. Finally, we propose a dynamic reciprocal authentication protocol to secure data transmission in mobile cloud computing (MCC). In particular, our proposed protocol develops a secure reciprocal authentication method, which is free of Diffie–Hellman limitations, and has immunity against basic or sophisticated known attacks. The protocol utilizes multifactor authentication of usernames, passwords, and a one-time password (OTP). The OTP is automatically generated and regularly updated for every connection. The proposed protocol is implemented and tested using Java to demonstrate its efficiency in authenticating communications and securing data transmitted in the MCC environment. Results of the evaluation process indicate that compared with the existing works, the proposed protocol possesses obvious capabilities in security and in communication and computation costs

Minimum energy transmission forest-based Geocast in software-defined wireless sensor networks

© 2021 The Authors. Published by Wiley. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1002/ett.4253Wireless Sensor Networks (WSNs)-based geographic addressing and routing have many potential applications. Geocast protocols should be made energy efficient to increase the lifetime of nodes and packet delivery ratio. This technique will increase the number of live nodes, reduce message costs, and enhance network throughput. All geocast protocols in the literature of WSN apply mostly restricted flooding and perimeter flooding, which is why still the redundancy they produce significantly high message transmission costs and unnecessarily eats up immense energy in nodes. Moreover, perimeter flooding cannot succeed in the presence of holes. The present article models wireless sensor networks with software-defined constructs where the network area is divided into some zones. Energy-efficient transmission tree(s) are constructed in the geocast area to organize the flow of data packets and their links. Therefore, redundancy in the transmission is eliminated while maintaining network throughput as good as regular flooding. This proposed technique significantly reduces energy cost and improves nodes' lifetime to function for higher time duration and produce a higher data packet delivery ratio. To the best of the author's knowledge, this is the first work on geocast in SD-WSNs

Trust aware crowd associated network-based approach for optimal waste management in smart cities

This is an accepted manuscript of an article published by CRC Press (Taylor & Francis) in Security and Organization within IoT and Smart Cities (in press), available online: https://www.routledge.com/Security-and-Organization-within-IoT-and-Smart-Cities/Ghafoor-Curran-Kong-Sadiq/p/book/9780367893330 The accepted version of the publication may differ from the final published version.Waste management has been a serious issue in urban areas due to the population growth. An appropriate solid waste management system is needed to improve the cleanliness of the environment. On the other hand, the rapid growth of the wide adoption of the Internet of Things (IoT) within the context of smart cities has motivated numerous number of studies investigating new solutions that could be helpful in mitigating and solving the waste management issue. Despite the existence of such methods have been introduced and used in managing waste’s location, volume and the optimal path for collection, yet these IoT based technologies are vulnerable to misinformation kinds of cyber attack. Consequently these types of attacks will yield crucial impact on the decided collection path and the frequency of garbage trucks visiting the fake reported waste points, which obviously costs money and time. Hence, this chapter proposes a trusted crowd associated network architecture that uses a group of components to monitor waste and provide optimum collection route for the garbage truck. Netlogo a multi-agent platform has been used to simulate a real time monitoring on waste management as a proof of concept. Our proposed approach measures the waste level data then updates and records them continuously. An optimal route will then be provided to the garbage truck for the optimal waste’s collection once a certain number of bins have reached a predefined threshold (combination of weight and height values). Three simulation scenarios are defined, implemented, and their results have been validated. The performance measure shows that our proposed solution could provide an aid waste management companies in reducing cost and time in the waste collection process, which supports the integration plans of IoT technology within smart cities

Identifying critical dimensions for project success in R&D public sector using Delphi study and validation techniques

© (2020) The Authors. Published by IEEE. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1109/ACCESS.2021.3112112In the current century, organizations face ever increasing dynamic ecosystems and are constantly devising strategies to meet their challenges. These include the implementation of the right organizational structure and avoid project schedule delays to achieve projects’ success. Unfortunately, the classification of significant project success dimensions in the R&D public sector environment is still an elusive concept. This study adopts a multi-dimensional qualitative and quantitative approach to explore the critical dimensions of organizational structure and schedule management that enhance or hinder the project success in R&D of public sector organizations. In Phase 1, a Delphi Study is conducted, and results of reliability and other tests are the input of Phase 2. On the basis of these tests, variables have been selected for the next phase or final questionnaire. In Phase 2, through a survey of 285 responses in a public sector R&D environment, the proposed framework is validated by conducting face, content and construct validity. The results indicated that formalization, specialization, differentiation, coordination mechanism, decentralization and authority of managers have a significant effect on the schedule management and successful execution of R&D projects; whereas, centralization and departmentalization do not correlate strongly. The results also imply that decentralized organizational structures (organic) are more preferable than centralized structures (mechanistic) for the execution of R&D projects when proposed timelines are to be met timely. The proposed framework will act as a supporting mechanism for engineering managers to deal with organizational structure and schedule management factors in a highly uncertain R&D environment where projects deviate frequently from their anticipated timeline