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SDN-Based load balancing service for cloud servers

- Abdelaziz, Ahmed, Ahmed, Ejaz, Fong, Ang, Gani, Abdullah, Imran, Muhammad

  • Authors: Abdelaziz, Ahmed , Ahmed, Ejaz , Fong, Ang , Gani, Abdullah , Imran, Muhammad
  • Date: 2018
  • Type: Text , Journal article
  • Relation: IEEE Communications Magazine Vol. 56, no. 8 (2018), p. 106-111
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  • Description: With the continuous growth, heterogeneity, and ever increasing demand of services, load balancing of cloud servers is an emerging challenge to meet highly demanding requirements (e.g., data rates, latency, quality of service) of 5G network applications. Although various load balancing techniques have been proposed, some of these techniques either require installation of dedicated additional load balancers for each service, or manual reconfiguration of the device to handle new services is desired. These techniques are expensive, time-consuming, and impractical. Moreover, most of the existing load balancing schemes do not consider service types. This article presents an SDN-based load balancing (SBLB) service for cloud servers to maximize resource utilization and minimize response time of users. The constituents of the proposed scheme are an application module that runs on top of an SDN controller and server pools that connect to the controller through OpenFlow switches. The application module consists of a service classification module, a dynamic load balancing module, and a monitoring module. The controller handles all messages, manages host pools, and maintains the load of host in real time. Experimental results validate the performance of the proposed scheme. Through experimental results, SBLB demonstrates significant decrease in average response time and reply time. © 1979-2012 IEEE.

Machine learning for 5G security : architecture, recent advances, and challenges

- Afaq, Amir, Haider, Noman, Baig, Muhammad, Khan, Komal, Imran, Muhammad, Razzak, Imran

  • Authors: Afaq, Amir , Haider, Noman , Baig, Muhammad , Khan, Komal , Imran, Muhammad , Razzak, Imran
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Ad Hoc Networks Vol. 123, no. (2021), p.
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  • Description: The granularization of crucial network functions implementation using software-centric, and virtualized approaches in 5G networks have brought forth unprecedented security challenges in general and privacy concerns. Moreover, these software components’ premature deployment and compromised supply chain put the individual network components at risk and have a ripple effect for the rest of the network. Some of the novel threats to 5G assets include tampering in identity and access management, supply-chain poisoning, masquerade and bot attacks, loop-holes in source codes. Machine learning (ML) in this context can help to provide heavily dynamic and robust security mechanisms for the software-centric architecture of 5G Networks. ML models’ development and implementation also rely on programmable environments; hence, they can play a vital role in designing, modelling, and automating efficient security protocols. This article presents the threat landscape across 5G networks and discusses the feasibility and architecture of different ML-based models to counter these threats. Also, we present the architecture for automated threat intelligence using cooperative and coordinated ML to secure 5G assets and infrastructure. We also present the summary of closely related existing works along with future research challenges. © 2021 Elsevier B.V.

Formal verification of persistence and liveness in the trust-based blockchain crowdsourcing consensus protocol

- Afzaal, Hamra, Imran, Muhammad, Janjua, Muhammad

  • Authors: Afzaal, Hamra , Imran, Muhammad , Janjua, Muhammad
  • Date: 2022
  • Type: Text , Journal article
  • Relation: Computer Communications Vol. 192, no. (2022), p. 384-401
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  • Description: Crowdsourcing is a potential computing paradigm that exploits collective human intelligence to solve complex tasks, but it suffers from various safety and security problems. Blockchain has emerged as a promising technology to address most of the security issues, however, it is challenging to find an appropriate and trusted blockchain-based consensus protocol for crowdsourcing services. This work proposes a novel Trust-based Blockchain Crowdsourcing consensus protocol that selects a leader and validators based on various trust factors. The proposed protocol addresses a major issue of ensuring correctness associated with the safety and security-critical systems which has a vital importance because failure of such systems may lead to adverse consequences. Mainly it is focused on persistence and liveness properties preventing invalid block insertion and consensus delay attacks. Model checking technique is utilized because of its effectiveness and automatic nature to perform formal verification. The proposed protocol is specified using Communicating Sequential Programs, and the persistence and liveness properties are specified through Linear Temporal Logic. The model verification is performed by giving the formal model and the properties as input to the Process Analysis Toolkit which checks for the satisfaction or violation of the properties. © 2022 Elsevier B.V.

Formal modeling and verification of a blockchain-based crowdsourcing consensus protocol

- Afzaal, Hamra, Imran, Muhammad, Janjua, Muhammad, Gochhayat, Sarada

  • Authors: Afzaal, Hamra , Imran, Muhammad , Janjua, Muhammad , Gochhayat, Sarada
  • Date: 2022
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 10, no. (2022), p. 8163-8183
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  • Description: Crowdsourcing is an effective technique that allows humans to solve complex problems that are hard to accomplish by automated tools. Some significant challenges in crowdsourcing systems include avoiding security attacks, effective trust management, and ensuring the system's correctness. Blockchain is a promising technology that can be efficiently exploited to address security and trust issues. The consensus protocol is a core component of a blockchain network through which all the blockchain peers achieve an agreement about the state of the distributed ledger. Therefore, its security, trustworthiness, and correctness have vital importance. This work proposes a Secure and Trustworthy Blockchain-based Crowdsourcing (STBC) consensus protocol to address these challenges. Model checking is an effective and automatic technique based on formal methods that is utilized to ensure the correctness of STBC consensus protocol. The proposed consensus protocol's formal specification is described using Communicating Sequential Programs (CSP#). Safety, fault tolerance, leader trust, and validators' trust are important properties for a consensus protocol, which are formally specified through Linear Temporal Logic (LTL) to prevent several security attacks, such as blockchain fork, selfish mining, and invalid block insertion. Process Analysis Toolkit (PAT) is utilized for the formal verification of the proposed consensus protocol. © 2022 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

Formal verification of fraud-resilience in a crowdsourcing consensus protocol

- Afzaal, Hamra, Imran, Muhammad, Janjua, Muhammad

  • Authors: Afzaal, Hamra , Imran, Muhammad , Janjua, Muhammad
  • Date: 2023
  • Type: Text , Journal article
  • Relation: Computers & security Vol. 131, no. (2023), p. 103290
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  • Description: •A Trust and Transactions Chain consensus protocol is proposed for a blockchain-based crowdsourcing system.•Communicating Sequential Programs language is utilized for the formal modeling of the proposed consensus protocol.•The properties of no sybil attack, no eclipse attack, and fraud-resilience are defined through Linear Temporal Logic.•Model checking is employed to ensure the correctness of the proposed consensus protocol.•The formal verification is performed by giving the formal model and properties as input to the Process Analysis Toolkit. [Display omitted] Crowdsourcing has emerged as a promising computing paradigm that utilizes human intelligence to achieve complex tasks, but it encounters several security and trust issues. Blockchain is a potential technology that can resolve most of these issues, however, it is difficult to find an appropriate consensus protocol applicable to crowdsourcing systems. Therefore, this work presents a Trust and Transactions Chain (TTC) consensus protocol built upon blockchain technology. It selects a trusted leader and validators considering a trust model which depends on deposit ratio, block generation and validation rate, and waiting rate. The TTC protocol addresses the main challenge of ensuring correctness related to critical systems of crowdsourcing which has extreme significance as their failure can result in disastrous consequences. This work is primarily focused on fraud-resilience avoiding double-spending attack. It also deals with sybil and eclipse attacks. Model checking is exploited because it is effective and automatic to conduct formal verification. The TTC protocol is formally modeled utilizing Communicating Sequential Programs, and the fraud-resilience property is specified using Linear Temporal Logic. The verification of the model is done using Process Analysis Toolkit that takes the formal model and specified properties as input to inspect the properties’ satisfaction or violation. The results of the formal verification are analyzed with respect to the verification time and the number of visited states.

Formal verification of justification and finalization in beacon chain

- Afzaal, Hamra, Zafar, Nazir, Tehseen, Aqsa, Kousar, Shaheen, Imran, Muhammad

  • Authors: Afzaal, Hamra , Zafar, Nazir , Tehseen, Aqsa , Kousar, Shaheen , Imran, Muhammad
  • Date: 2024
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 12, no. (2024), p. 55077-55102
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  • Description: In recent years, Beacon Chain known as the core of Ethereum 2.0, has gained considerable attention since its launch. Many validators have staked billions of Ether in the Proof of Stake (PoS) network. It is a mission critical system and its security and stability rely on the justification and finalization of checkpoints. These are essential elements of the Casper FFG consensus algorithm utilized by the Beacon Chain. This process is critical for establishing a trustworthy foundation and finalizing proposed blocks by confirming agreed upon checkpoints. Hence, ensuring the correctness of checkpoints in the Beacon Chain has significant importance because any bug in it can cause serious implications. To address this challenge, we employ formal methods, a popular mathematical approach used for verifying the correctness of such critical systems. In this work, we have done formal verification of the processes of Beacon Chain state initialization, justification and finalization of checkpoints using the Process Analysis Toolkit (PAT) model checker. The adoption of model checking through the PAT model checker presents a novel contribution of our work, as this approach is not previously utilized in the formal verification of Beacon Chain. The presented work is specified through the Communicating Sequential Programs, formal specification language, and the properties are described through Linear Temporal Logic. The PAT model checker takes the specified formal model and properties as input to assess whether the properties are satisfied. The properties are analyzed with respect to the verification time, visited states, total transitions, and memory used. Through this research, we aim to increase confidence in the correctness and reliability of the Beacon Chain. © 2013 IEEE.

An efficient network intrusion detection and classification system

- Ahmad, Iftikhar, Haq, Qazi, Imran, Muhammad, Alassafi, Madini, Alghamdi, Rayed

  • Authors: Ahmad, Iftikhar , Haq, Qazi , Imran, Muhammad , Alassafi, Madini , Alghamdi, Rayed
  • Date: 2022
  • Type: Text , Journal article
  • Relation: Mathematics Vol. 10, no. 3 (2022), p.
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  • Description: Intrusion detection in computer networks is of great importance because of its effects on the different communication and security domains. The detection of network intrusion is a challenge. Moreover, network intrusion detection remains a challenging task as a massive amount of data is required to train the state-of-the-art machine learning models to detect network intrusion threats. Many approaches have already been proposed recently on network intrusion detection. However, they face critical challenges owing to the continuous increase in new threats that current systems do not understand. This paper compares multiple techniques to develop a network intrusion detection system. Optimum features are selected from the dataset based on the correlation between the features. Furthermore, we propose an AdaBoost-based approach for network intrusion detection based on these selected features and present its detailed functionality and performance. Unlike most previous studies, which employ the KDD99 dataset, we used a recent and comprehensive UNSW-NB 15 dataset for network anomaly detection. This dataset is a collection of network packets exchanged between hosts. It comprises 49 attributes, including nine types of threats such as DoS, Fuzzers, Exploit, Worm, shellcode, reconnaissance, generic, and analysis Backdoor. In this study, we employ SVM and MLP for comparison. Finally, we propose AdaBoost based on the decision tree classifier to classify normal activity and possible threats. We monitored the network traffic and classified it into either threats or non-threats. The experimental findings showed that our proposed method effectively detects different forms of network intrusions on computer networks and achieves an accuracy of 99.3% on the UNSW-NB15 dataset. The proposed system will be helpful in network security applications and research domains. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Characterizing the role of vehicular cloud computing in road traffic management

- Ahmad, Iftikhar, Noor, Rafidah, Ali, Ihsan, Imran, Muhammad, Vasilakos, Athanasios

  • Authors: Ahmad, Iftikhar , Noor, Rafidah , Ali, Ihsan , Imran, Muhammad , Vasilakos, Athanasios
  • Date: 2017
  • Type: Text , Journal article
  • Relation: International Journal of Distributed Sensor Networks Vol. 13, no. 5 (2017), p.
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  • Description: Vehicular cloud computing is envisioned to deliver services that provide traffic safety and efficiency to vehicles. Vehicular cloud computing has great potential to change the contemporary vehicular communication paradigm. Explicitly, the underutilized resources of vehicles can be shared with other vehicles to manage traffic during congestion. These resources include but are not limited to storage, computing power, and Internet connectivity. This study reviews current traffic management systems to analyze the role and significance of vehicular cloud computing in road traffic management. First, an abstraction of the vehicular cloud infrastructure in an urban scenario is presented to explore the vehicular cloud computing process. A taxonomy of vehicular clouds that defines the cloud formation, integration types, and services is presented. A taxonomy of vehicular cloud services is also provided to explore the object types involved and their positions within the vehicular cloud. A comparison of the current state-of-the-art traffic management systems is performed in terms of parameters, such as vehicular ad hoc network infrastructure, Internet dependency, cloud management, scalability, traffic flow control, and emerging services. Potential future challenges and emerging technologies, such as the Internet of vehicles and its incorporation in traffic congestion control, are also discussed. Vehicular cloud computing is envisioned to have a substantial role in the development of smart traffic management solutions and in emerging Internet of vehicles. © The Author(s) 2017.

An optimized hybrid deep intrusion detection model (HD-IDM) for enhancing network security

- Ahmad, Iftikhar, Imran, Muhammad, Qayyum, Abdul, Ramzan, Muhammad, Alassafi, Madini

  • Authors: Ahmad, Iftikhar , Imran, Muhammad , Qayyum, Abdul , Ramzan, Muhammad , Alassafi, Madini
  • Date: 2023
  • Type: Text , Journal article
  • Relation: Mathematics Vol. 11, no. 21 (2023), p.
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  • Description: Detecting cyber intrusions in network traffic is a tough task for cybersecurity. Current methods struggle with the complexity of understanding patterns in network data. To solve this, we present the Hybrid Deep Learning Intrusion Detection Model (HD-IDM), a new way that combines GRU and LSTM classifiers. GRU is good at catching quick patterns, while LSTM handles long-term ones. HD-IDM blends these models using weighted averaging, boosting accuracy, especially with complex patterns. We tested HD-IDM on four datasets: CSE-CIC-IDS2017, CSE-CIC-IDS2018, NSL KDD, and CIC-DDoS2019. The HD-IDM classifier achieved remarkable performance metrics on all datasets. It attains an outstanding accuracy of 99.91%, showcasing its consistent precision across the dataset. With an impressive precision of 99.62%, it excels in accurately categorizing positive cases, crucial for minimizing false positives. Additionally, maintaining a high recall of 99.43%, it effectively identifies the majority of actual positive cases while minimizing false negatives. The F1-score of 99.52% emphasizes its robustness, making it the top choice for classification tasks requiring precision and reliability. It is particularly good at ROC and precision/recall curves, discriminating normal and harmful network activities. While HD-IDM is promising, it has limits. It needs labeled data and may struggle with new intrusion methods. Future work should find ways to handle unlabeled data and adapt to emerging threats. Also, making HD-IDM work faster for real-time use and dealing with scalability challenges is key for its broader use in changing network environments. © 2023 by the authors.

VANET–LTE based heterogeneous vehicular clustering for driving assistance and route planning applications

- Ahmad, Iftikhar, Noor, Rafidah, Ahmedy, Ismail, Shah, Syed, Imran, Muhammad

  • Authors: Ahmad, Iftikhar , Noor, Rafidah , Ahmedy, Ismail , Shah, Syed , Imran, Muhammad
  • Date: 2018
  • Type: Text , Journal article
  • Relation: Computer Networks Vol. 145, no. (2018), p. 128-140
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  • Description: The Internet of vehicles incorporates multiple access networks and technologies to connect vehicles on roads. These vehicles usually require the use of individual long-term evolution (LTE) connections to send/receive data to/from a remote server to make smart decisions regarding route planning and driving. An increasing number of vehicles on the roads may not only overwhelm LTE network usage but also incur added cost. Clustering helps minimize LTE usage, but the high speed of vehicles renders connections unstable and unreliable not only among vehicles but also between vehicles and the LTE network. Moreover, non-cooperative behavior among vehicles within a cluster is a bottleneck in sharing costly data acquired from the Internet. To address these issues, we propose a novel destination- and interest-aware clustering (DIAC) mechanism. DIAC primarily incorporates a strategic game-theoretic algorithm and a self-location calculation algorithm. The former allows vehicles to participate/cooperate and enforces a fair-use policy among the cluster members (CMs), whereas the latter enables CMs to calculate their location coordinates in the absence of a global positioning system under an urban topography. DIAC strives to reduce the frequency of link failures not only among vehicles but also between each vehicle and the 3G/LTE network. The mechanism also considers vehicle mobility and LTE link quality and exploits common interests among vehicles in the cluster formation phase. The performance of the DIAC mechanism is validated through extensive simulations, whose results demonstrate that the performance of the proposed mechanism is superior to that of similar and existing approaches. © 2018 Elsevier B.V.

A cooperative heterogeneous vehicular clustering mechanism for road traffic management

- Ahmad, Iftikhar, Noor, Rafidah, Zaba, Muhammad, Qureshi, Muhammad, Imran, Muhammad, Shoaib, Muhammad

  • Authors: Ahmad, Iftikhar , Noor, Rafidah , Zaba, Muhammad , Qureshi, Muhammad , Imran, Muhammad , Shoaib, Muhammad
  • Date: 2020
  • Type: Text , Journal article
  • Relation: International Journal of Parallel Programming Vol. 48, no. 5 (2020), p. 870-889
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  • Description: The vehicular ad-hoc networks integrates with long-term evolution (LTE) forming a heterogeneous network, capable of providing seamless connectivity, which meets the communication requirements of intelligent transportation systems. However, heterogeneous network-based applications involve LTE resource (data and spectrum) usage cost and must be taken care while developing such a solution. One of the scenarios is the access of the information to/from remote server over the internet via LTE for road traffic management applications. Although clustering of the vehicle is significant to minimize the data and LTE network usage, however, the problem of non-cooperation of the vehicles in clustering process and within a cluster are major issues in sharing costly data acquired from the internet. Because, who and why one (vehicle) should pay the cost is the big question, proliferating the non-cooperative behavior among the cluster members. To solve these issues, strategic game-theoretic based clustering mechanism named as cooperative interest-aware clustering (CIAC) is developed. The proposed CIAC not only balance the cost of usage by controlling non-cooperative behavior among the vehicles within the cluster but at the same time motivate vehicles to participate in the clustering process to share the data and cost as well. It consists of a cluster head selection process based on the strategic game-theoretic approach and a fair-use policy. The implementation results show superiority in performance of our protocol over the existing approaches. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

Towards intrusion detection to secure VANET-assisted healthcare monitoring system

- Ahmad, Iftikhar, Ahmad, Irshad, Amin, Fazal, Imran, Muhammad, Sattar, Kashif

  • Authors: Ahmad, Iftikhar , Ahmad, Irshad , Amin, Fazal , Imran, Muhammad , Sattar, Kashif
  • Date: 2017
  • Type: Text , Journal article
  • Relation: Journal of Medical Imaging and Health Informatics Vol. 7, no. 6 (2017), p. 1391-1398
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  • Description: Remote healthcare monitoring (RHM) has been used in contemporary disease management to improve the quality of life. A Secure VANET-Assisted Remote Healthcare Monitoring System is very importance due to privacy and sensitivity of the health data. In wireless network different kind of attacks produce and involve the core functionality of VANET-Assisted Remote Healthcare Monitoring System. DoS and DDoS are two important attacks and both are related to the network availability. This study provides the detail description and working mechanism of DoS and DDoS attack in VANET-Assisted Remote Healthcare Monitoring System. Further, it proposes the possible solutions to detect and prevent such attacks in network and make sure for end users to continuous access the network. Moreover, the random forest algorithm is proposed and applied to the benchmarked dataset for the detection of the attacks that may improve the security of RHM systems. The performance is addressed in accuracy, precision and recall metrics. © 2017 American Scientific Publishers All rights reserved. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran” is provided in this record**

Internet-of-things-based smart environments : state of the art, taxonomy, and open research challenges

- Ahmed, Ejaz, Yaqoob, Ibrar, Gani, Abdullah, Imran, Muhammad, Guizani, Mohsen

  • Authors: Ahmed, Ejaz , Yaqoob, Ibrar , Gani, Abdullah , Imran, Muhammad , Guizani, Mohsen
  • Date: 2016
  • Type: Text , Journal article
  • Relation: IEEE Wireless Communications Vol. 23, no. 5 (2016), p. 10-16
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  • Description: The rapid advancements in communication technologies and the explosive growth of the Internet of Things have enabled the physical world to invisibly interweave with actuators, sensors, and other computational elements while maintaining continuous network connectivity. The continuously connected physical world with computational elements forms a smart environment. A smart environment aims to support and enhance the abilities of its dwellers in executing their tasks, such as navigating through unfamiliar space and moving heavy objects for the elderly, to name a few. Researchers have conducted a number of efforts to use IoT to facilitate our lives and to investigate the effect of IoT-based smart environments on human life. This article surveys the state-of-the-art research efforts to enable IoT-based smart environments. We categorize and classify the literature by devising a taxonomy based on communication enablers, network types, technologies, local area wireless standards, objectives, and characteristics. Moreover, the article highlights the unprecedented opportunities brought about by IoT-based smart environments and their effect on human life. Some reported case studies from different enterprises are also presented. Finally, we discuss open research challenges for enabling IoT-based smart environments. © 2016 IEEE.

Green industrial networking : recent advances, taxonomy, and open research challenges

- Ahmed, Ejaz, Yaqoob, Ibrar, Ahmed, Ahmed, Gani, Abdullah, Imran, Muhammad, Guizani, Sghaier

  • Authors: Ahmed, Ejaz , Yaqoob, Ibrar , Ahmed, Ahmed , Gani, Abdullah , Imran, Muhammad , Guizani, Sghaier
  • Date: 2016
  • Type: Text , Journal article
  • Relation: IEEE Communications Magazine Vol. 54, no. 10 (2016), p. 38-45
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  • Description: The consciousness of environmental problems has attracted the industry's attention toward the reduction of unnecessary energy emission by enabling green industrial networking. The reduction of unnecessary energy emitted by industrial networks can be a possible solution to many environmental issues. Green industrial networking is in its infancy, and an overview of the domain is still lacking. In this article, we discuss recent advances in industrial and green networking paradigms to investigate the impact on global communities. We also classify the literature by devising a taxonomy based on networking technologies, machines, network types, topologies, field bus types, transmission media, and hierarchical levels. Moreover, we identify and discuss key enablers (adaptive links, resource-based energy conservation, energy-efficient scheduling, energy-aware systems, energy-aware proxying, energy-conservative approaches, and low-power wireless protocols) for green industrial networking. Furthermore, we discuss challenges that remain to be addressed as future research directions. © 2016 IEEE.

Bringing Computation Closer toward the User Network: Is Edge Computing the Solution?

- Ahmed, Ejaz, Ahmed, Arif, Yaqoob, Ibrar, Shuja, Junaid, Imran, Muhammad

  • Authors: Ahmed, Ejaz , Ahmed, Arif , Yaqoob, Ibrar , Shuja, Junaid , Imran, Muhammad
  • Date: 2017
  • Type: Text , Journal article
  • Relation: IEEE Communications Magazine Vol. 55, no. 11 (2017), p. 138-144
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  • Description: The virtually unlimited available resources and wide range of services provided by the cloud have resulted in the emergence of new cloud-based applications, such as smart grids, smart building control, and virtual reality. These developments, however, have also been accompanied by a problem for delay-sensitive applications that have stringent delay requirements. The current cloud computing paradigm cannot realize the requirements of mobility support, location awareness, and low latency. Hence, to address the problem, an edge computing paradigm that aims to extend the cloud resources and services and enable them to be nearer the edge of an enterprise's network has been introduced. In this article, we highlight the significance of edge computing by providing real-life scenarios that have strict constraint requirements on application response time. From the previous literature, we devise a taxonomy to classify the current research efforts in the domain of edge computing. We also discuss the key requirements that enable edge computing. Finally, current challenges in realizing the vision of edge computing are discussed. © 1979-2012 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “ Muhammad Imran” is provided in this record**

Process state synchronization-based application execution management for mobile edge/cloud computing

- Ahmed, Ejaz, Naveed, Anjum, Gani, Abdullah, Hamid, Siti, Imran, Muhammad, Guizani, Mohsen

  • Authors: Ahmed, Ejaz , Naveed, Anjum , Gani, Abdullah , Hamid, Siti , Imran, Muhammad , Guizani, Mohsen
  • Date: 2019
  • Type: Text , Journal article
  • Relation: Future Generation Computer Systems Vol. 91, no. (2019), p. 579-589
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  • Description: Mobile cloud computing (MCC) and mobile edge computing (MEC) facilitate the mobile devices to augment their capabilities by utilizing the resources and services offered by Cloud and Edge Cloud, respectively. However, due to mobility, network connection becomes unstable that causes application execution disruption. Such disruption increases the execution time and in some cases restrain the mobile devices from getting execution results from the cloud. This research work analyzes the impact of user mobility on the execution of cloud-based mobile applications. We propose a Process State Synchronization (PSS)-based execution management to solve the aforementioned problem. We analytically compute a sufficient condition on synchronization interval that ensure reduction in mobile application execution time under PSS in case of disconnection. Similarly, we compute the upper bound on synchronization interval whereby a larger synchronization interval did not result in significant benefits in terms of execution time for the mobile application. The analytical results were confirmed by the sample implementation of PSS with the computed synchronization intervals. Moreover, we also compare the performance of proposed solution with the state-of-the-art solutions. The results show that the PSS-based execution outperforms the other contemporary solutions. © 2018 Elsevier B.V.

Recent advances and challenges in mobile big data

- Ahmed, Ejaz, Yaqoob, Ibrar, Hashem, Ibrahim, Shuja, Junaid, Imran, Muhammad

  • Authors: Ahmed, Ejaz , Yaqoob, Ibrar , Hashem, Ibrahim , Shuja, Junaid , Imran, Muhammad
  • Date: 2018
  • Type: Text , Journal article
  • Relation: IEEE Communications Magazine Vol. 56, no. 2 (2018), p. 102-108
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  • Description: The unabated flurry of research activities dedicated to gaining business insights from a flood of data generated by heterogeneous mobile sources, such as the Internet of Vehicles, sensors, and smartphones, has instigated a new research domain called MBD. At the core of this mobile environment, scalability, cost effectiveness, reliability, analytics, and security are important concerns. Coping with these issues in handling MBD requires understanding the challenges associated with it. Mobile computing and big data have been widely studied separately; however, very few studies have explored the convergence of these two domains. In this article, we critically review recent research efforts directed at MBD. We also classify the MBD by devising a thematic taxonomy that is based on source, analytics, applications, characteristics, security, and data type. Furthermore, we discuss the opportunities offered by MBD in terms of analytics. Some potential uses of MBD in healthcare, telecommunication, digital advertising, and transportation are also presented. Several open research challenges are discussed as future research directions. © 1979-2012 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran” is provided in this record**

Social-aware resource allocation and optimization for D2D communication

- Ahmed, Ejaz, Yaqoob, Ibrar, Gani, Abdullah, Imran, Muhammad, Guizani, Mohsen

  • Authors: Ahmed, Ejaz , Yaqoob, Ibrar , Gani, Abdullah , Imran, Muhammad , Guizani, Mohsen
  • Date: 2017
  • Type: Text , Journal article
  • Relation: IEEE Wireless Communications Vol. 24, no. 3 (2017), p. 122-129
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  • Description: The undiminished growth of research activities to converge social awareness with D2D communication has paved the way for facilitating and providing significant benefits to users. Realizing these benefits depends on efficiently addressing several main technical challenges associated with the convergence. Although there are many research studies related to social networks and D2D communication, convergence of these two areas leads to further research efforts to implement social-aware D2D communication. In this article, we discuss recent advances in the domain of D2D communication from the perspective of social-aware resource allocation and optimization. We also categorize and classify the literature by devising a taxonomy based on channel-centric attributes, objectives, solving approaches, networking technologies, characteristics, and communication types. Moreover, we also outline the key requirements with the aim of providing guidelines for the domain researchers and designers to enable the social-aware resource allocation for D2D communication. Several open research challenges are presented as future research directions. © 2002-2012 IEEE.

The role of big data analytics in internet of things

- Ahmed, Ejaz, Yaqoob, Ibrar, Hashem, Ibrahim, Khan, Imran, Imran, Muhammad

  • Authors: Ahmed, Ejaz , Yaqoob, Ibrar , Hashem, Ibrahim , Khan, Imran , Imran, Muhammad
  • Date: 2017
  • Type: Text , Journal article
  • Relation: Computer Networks Vol. 129, no. (2017), p. 459-471
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  • Description: The explosive growth in the number of devices connected to the Internet of Things (IoT) and the exponential increase in data consumption only reflect how the growth of big data perfectly overlaps with that of IoT. The management of big data in a continuously expanding network gives rise to non-trivial concerns regarding data collection efficiency, data processing, analytics, and security. To address these concerns, researchers have examined the challenges associated with the successful deployment of IoT. Despite the large number of studies on big data, analytics, and IoT, the convergence of these areas creates several opportunities for flourishing big data and analytics for IoT systems. In this paper, we explore the recent advances in big data analytics for IoT systems as well as the key requirements for managing big data and for enabling analytics in an IoT environment. We taxonomized the literature based on important parameters. We identify the opportunities resulting from the convergence of big data, analytics, and IoT as well as discuss the role of big data analytics in IoT applications. Finally, several open challenges are presented as future research directions. © 2017 Elsevier B.V. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran” is provided in this record**

A novel collaborative IoD-assisted VANET approach for coverage area maximization

- Ahmed, Gamil, Sheltami, Tarek, Mahmoud, Ashraf, Imran, Muhammad, Shoaib, Muhammad

  • Authors: Ahmed, Gamil , Sheltami, Tarek , Mahmoud, Ashraf , Imran, Muhammad , Shoaib, Muhammad
  • Date: 2021
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 9, no. (2021), p. 61211-61223
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  • Description: Internet of Drones (IoD) is an efficient technique that can be integrated with vehicular ad-hoc networks (VANETs) to provide terrestrial communications by acting as an aerial relay when terrestrial infrastructure is unreliable or unavailable. To fully exploit the drones' flexibility and superiority, we propose a novel dynamic IoD collaborative communication approach for urban VANETs. Unlike most of the existing approaches, the IoD nodes are dynamically deployed based on current locations of ground vehicles to effectively mitigate inevitable isolated cars in conventional VANETs. For efficiently coordinating IoD, we model IoD to optimize coverage based on the location of vehicles. The goal is to obtain an efficient IoD deployment to maximize the number of covered vehicles, i.e., minimize the number of isolated vehicles in the target area. More importantly, the proposed approach provides sufficient interconnections between IoD nodes. To do so, an improved version of succinct population-based meta-heuristic, namely Improved Particle Swarm Optimization (IPSO) inspired by food searching behavior of birds or fishes flock, is implemented for IoD assisted VANET (IoDAV). Moreover, the coverage, received signal quality, and IoD connectivity are achieved by IPSO's objective function for optimal IoD deployment at the same time. We carry out an extensive experiment based on the received signal at floating vehicles to examine the proposed IoDAV performance. We compare the results with the baseline VANET with no IoD (NIoD) and Fixed IoD assisted (FIoD). The comparisons are based on the coverage percentage of the ground vehicles and the quality of the received signal. The simulation results demonstrate that the proposed IoDAV approach allows finding the optimal IoD positions throughout the time based on the vehicle's movements and achieves better coverage and better quality of the received signal by finding the most appropriate IoD position compared with NIoD and FIoD schemes. © 2013 IEEE.