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Aniket Mahanti is a Senior Lecturer (North America: Associate Professor) in computer science at the University of Auckland, New Zealand. He received his B.Sc. (Honours) in computer science from the University of New Brunswick, Saint John in 2004. Later, he moved to Calgary to pursue graduate studies and completed his Master's in 2006. He worked as a research associate for 2 years, and enrolled in the doctoral program in University of Calgary in 2008. He graduated with a Ph.D. in computer science in 2012. Since then, he has been working in the Department of Computer Science at the University of Auckland. His research interests are in the general area of computer networking with an emphasis on Internet measurements and performance evaluation. Aniket's research has appeared in top peer-reviewed conferences and journals. His publications can be found through well-known indexing services such as DBLP, Google Scholar, and SCOPUS. His work has been extensively cited in the research literature. He is actively involved with the research community through participation in prestigious conference TPCs, workshop organization, journal/conference reviewing, invited seminars, journal editing, international grant reviewing, and external M.Sc./Ph.D. examination, among other things.
This paper provides a comprehensive measurement study on three video streaming websites with social media features - ‘TED Talks’, ‘xHamster’ and ‘XVideos’. We have analysed 2685 TED videos from 2006 to 2018 to characterise the service. For xHamster and XVideos, active measurements were used to collect unique metadata on almost 3405 and 6721 channels from 2012 to 2019 respectively, which were then analysed. Through these characterisations we gained insight into the main players of the websites – viewers, uploaders and website owners. Our analysis involved the studying of video streaming characteristics such as views, number of uploads, ratings, tags etc. By this we aim to give an overview of the services' current state and compare them with other traditional video streaming services. Our results showed some similar trends to be observed in all three websites such as TED videos and adult channels getting a high number of views despite low injection rate, maintaining a power-law behaviour due to front page recommendations and ratings being underutilised as a feature.Other observations include adult streaming services having a higher number of subscribers per channel. The characterisation results obtained are of value to network operators, content providers, and protocol designers. These results can also be used by content providers to measure what type of content is being watched on their websites. Our study provides a glimpse at how video streaming services function today and the trends they seem to follow.
Saif Ahmed Adib; Aniket Mahanti; Ranesh Kumar Naha. Characterisation and comparative analysis of thematic video portals. Technology in Society 2021, 67, 101690 .
AMA StyleSaif Ahmed Adib, Aniket Mahanti, Ranesh Kumar Naha. Characterisation and comparative analysis of thematic video portals. Technology in Society. 2021; 67 ():101690.
Chicago/Turabian StyleSaif Ahmed Adib; Aniket Mahanti; Ranesh Kumar Naha. 2021. "Characterisation and comparative analysis of thematic video portals." Technology in Society 67, no. : 101690.
Technological advancements have led to increased confidence in the design of large-scale wireless networks that comprise small energy constraint devices. Despite the boost in technological advancements, energy dissipation and fault tolerance are amongst the key deciding factors while designing and deploying wireless sensor networks. This paper proposes a Fault-tolerant Energy-efficient Hierarchical Clustering Algorithm (FEHCA) for wireless sensor networks (WSNs), which demonstrates energy-efficient clustering and fault-tolerant operation of cluster heads (CHs). It treats CHs as no special node but equally prone to faults as normal sensing nodes of the cluster. The proposed scheme addresses some of the limitations of prominent hierarchical clustering algorithms, such as the randomized election of the cluster heads after each round, which results in significant energy dissipation; non-consideration of the residual energy of the sensing nodes while selecting cluster heads, etc. It utilizes the capability of vector quantization to partition the deployed sensors into an optimal number of clusters and ensures that almost the entire area to be monitored is alive for most of the network’s lifetime. This supports better decision-making compared to decisions made on the basis of limited area sensing data after a few rounds of communication. The scheme is implemented for both friendly as well as hostile deployments. The simulation results are encouraging and validate the proposed algorithm.
Ankur Choudhary; Santosh Kumar; Sharad Gupta; Mingwei Gong; Aniket Mahanti. FEHCA: A Fault-Tolerant Energy-Efficient Hierarchical Clustering Algorithm for Wireless Sensor Networks. Energies 2021, 14, 3935 .
AMA StyleAnkur Choudhary, Santosh Kumar, Sharad Gupta, Mingwei Gong, Aniket Mahanti. FEHCA: A Fault-Tolerant Energy-Efficient Hierarchical Clustering Algorithm for Wireless Sensor Networks. Energies. 2021; 14 (13):3935.
Chicago/Turabian StyleAnkur Choudhary; Santosh Kumar; Sharad Gupta; Mingwei Gong; Aniket Mahanti. 2021. "FEHCA: A Fault-Tolerant Energy-Efficient Hierarchical Clustering Algorithm for Wireless Sensor Networks." Energies 14, no. 13: 3935.
Fog computing is an emerging computing paradigm that has come into consideration for the deployment of Internet of Things (IoT) applications amongst researchers and technology industries over the last few years. Fog is highly distributed and consists of a wide number of autonomous end devices, which contribute to the processing. However, the variety of devices offered across different users are not audited. Hence, the security of Fog devices is a major concern that should come into consideration. Therefore, to provide the necessary security for Fog devices, there is a need to understand what the security concerns are with regards to Fog. All aspects of Fog security, which have not been covered by other literature works, need to be identified and aggregated. On the other hand, privacy preservation for user’s data in Fog devices and application data processed in Fog devices is another concern. To provide the appropriate level of trust and privacy, there is a need to focus on authentication, threats and access control mechanisms as well as privacy protection techniques in Fog computing. In this paper, a survey along with a taxonomy is proposed, which presents an overview of existing security concerns in the context of the Fog computing paradigm. Moreover, the Blockchain-based solutions towards a secure Fog computing environment is presented and various research challenges and directions for future research are discussed.
Abdullah Patwary; Ranesh Naha; Saurabh Garg; Sudheer Battula; Anwarul Kaium Patwary; Erfan Aghasian; Muhammad Amin; Aniket Mahanti; Mingwei Gong. Towards Secure Fog Computing: A Survey on Trust Management, Privacy, Authentication, Threats and Access Control. Electronics 2021, 10, 1171 .
AMA StyleAbdullah Patwary, Ranesh Naha, Saurabh Garg, Sudheer Battula, Anwarul Kaium Patwary, Erfan Aghasian, Muhammad Amin, Aniket Mahanti, Mingwei Gong. Towards Secure Fog Computing: A Survey on Trust Management, Privacy, Authentication, Threats and Access Control. Electronics. 2021; 10 (10):1171.
Chicago/Turabian StyleAbdullah Patwary; Ranesh Naha; Saurabh Garg; Sudheer Battula; Anwarul Kaium Patwary; Erfan Aghasian; Muhammad Amin; Aniket Mahanti; Mingwei Gong. 2021. "Towards Secure Fog Computing: A Survey on Trust Management, Privacy, Authentication, Threats and Access Control." Electronics 10, no. 10: 1171.
In cloud storage systems, users must be able to shut down the application when not in use and restart it from the last consistent state when required. BlobSeer is a data storage application, specially designed for distributed systems, that was built as an alternative solution for the existing popular open-source storage system-Hadoop Distributed File System (HDFS). In a cloud model, all the components need to stop and restart from a consistent state when the user requires it. One of the limitations of BlobSeer DFS is the possibility of data loss when the system restarts. As such, it is important to provide a consistent start and stop state to BlobSeer components when used in a Cloud environment to prevent any data loss. In this paper, we investigate the possibility of BlobSeer providing a consistent state distributed data storage system with the integration of checkpointing restart functionality. To demonstrate the availability of a consistent state, we set up a cluster with multiple machines and deploy BlobSeer entities with checkpointing functionality on various machines. We consider uncoordinated checkpoint algorithms for their associated benefits over other alternatives while integrating the functionality to various BlobSeer components such as the Version Manager (VM) and the Data Provider. The experimental results show that with the integration of the checkpointing functionality, a consistent state can be ensured for a distributed storage system even when the system restarts, preventing any possible data loss after the system has encountered various system errors and failures.
Laskhmi Talluri; Ragunathan Thirumalaisamy; Ramgopal Kota; Ram Sadi; Ujjwal Kc; Ranesh Naha; Aniket Mahanti. Providing Consistent State to Distributed Storage System. Computers 2021, 10, 23 .
AMA StyleLaskhmi Talluri, Ragunathan Thirumalaisamy, Ramgopal Kota, Ram Sadi, Ujjwal Kc, Ranesh Naha, Aniket Mahanti. Providing Consistent State to Distributed Storage System. Computers. 2021; 10 (2):23.
Chicago/Turabian StyleLaskhmi Talluri; Ragunathan Thirumalaisamy; Ramgopal Kota; Ram Sadi; Ujjwal Kc; Ranesh Naha; Aniket Mahanti. 2021. "Providing Consistent State to Distributed Storage System." Computers 10, no. 2: 23.
The number of IoT sensors and physical objects accommodated on the Internet is increasing day by day, and traditional Cloud Computing would not be able to host IoT data because of its high latency. Being challenged of processing all IoT big data on Cloud facilities, there is not enough study on automating components to deal with the big data and real-time tasks in the IoT–Fog–Cloud ecosystem. For instance, designing automatic data transfer from the fog layer to cloud layer, which contains enormous distributed devices is challenging. Considering fog as the supporting processing layer, dealing with decentralized devices in the IoT and fog layer leads us to think of other automatic mechanisms to manage the existing heterogeneity. The big data and heterogeneity challenges also motivated us to design other automatic components for Fog resiliency, which we address as the third challenge in the ecosystem. Fog resiliency makes the processing of IoT tasks independent to the Cloud layer. This survey aims to review, study, and analyze the automatic functions as a taxonomy to help researchers, who are implementing methods and algorithms for different IoT applications. We demonstrated the automatic functions through our research in accordance to each challenge. The study also discusses and suggests automating the tasks, methods, and processes of the ecosystem that still process the data manually.
Hossein Chegini; Ranesh Naha; Aniket Mahanti; Parimala Thulasiraman. Process Automation in an IoT–Fog–Cloud Ecosystem: A Survey and Taxonomy. IoT 2021, 2, 92 -118.
AMA StyleHossein Chegini, Ranesh Naha, Aniket Mahanti, Parimala Thulasiraman. Process Automation in an IoT–Fog–Cloud Ecosystem: A Survey and Taxonomy. IoT. 2021; 2 (1):92-118.
Chicago/Turabian StyleHossein Chegini; Ranesh Naha; Aniket Mahanti; Parimala Thulasiraman. 2021. "Process Automation in an IoT–Fog–Cloud Ecosystem: A Survey and Taxonomy." IoT 2, no. 1: 92-118.
Fog computing is an emerging computing paradigm which expands cloud-based computing services near the network edge. With this new computing paradigm, new challenges arise in terms of security and privacy. These concerns are due to the distributed ownership of Fog devices. Because of the large scale distributed nature of devices at the Fog layer, secure authentication for communication among these devices is a major challenge. The traditional authentication methods (password-based, certificate-based and biometric-based) are not directly applicable due to the unique architecture and characteristics of the Fog. Moreover, the traditional authentication methods consume significantly more computation power and incur high latency, and this does not meet the key requirements of the Fog. To fill this gap, this article proposes a secure decentralised location-based device to device (D2D) authentication model in which Fog devices can mutually authenticate each other at the Fog layer by using Blockchain. We considered an Ethereum Blockchain platform for the Fog device registration, authentication, attestation and data storage. We presented the overall system architecture, various participants and their transactions and message interaction between the participants. We validated the proposed model by comparing it with the existing method; results showed that the proposed authentication mechanism was efficient and secure. From the performance evaluation, it was found that the proposed method is computationally efficient and secure in a highly distributed Fog network.
Abdullah Al-Noman Patwary; Anmin Fu; Sudheer Kumar Battula; Ranesh Kumar Naha; Saurabh Garg; Aniket Mahanti. FogAuthChain: A secure location-based authentication scheme in fog computing environments using Blockchain. Computer Communications 2020, 162, 212 -224.
AMA StyleAbdullah Al-Noman Patwary, Anmin Fu, Sudheer Kumar Battula, Ranesh Kumar Naha, Saurabh Garg, Aniket Mahanti. FogAuthChain: A secure location-based authentication scheme in fog computing environments using Blockchain. Computer Communications. 2020; 162 ():212-224.
Chicago/Turabian StyleAbdullah Al-Noman Patwary; Anmin Fu; Sudheer Kumar Battula; Ranesh Kumar Naha; Saurabh Garg; Aniket Mahanti. 2020. "FogAuthChain: A secure location-based authentication scheme in fog computing environments using Blockchain." Computer Communications 162, no. : 212-224.
Video content on user-generated content services has redefined entertainment and business on the Internet. Adult video streaming services have embraced this evolution to form YouTube style porn sites which combine the features of video hosting websites and online social media services. This paper presents a comprehensive measurement study of one of the most popular new-age porn websites with social networking features—xHamster. Using active measurements, we have obtained metadata on almost 4 million unique videos that span the lifetime of xHamster from 2007 to 2018. An analysis of this corpus allowed us to characterize the service and gain insights into the key players of the website including the website owners, video uploaders, and the viewers. By studying the characteristics of videos such as views, duration, the number of uploads, tags, ratings and comments, we give an overview of xHamster’s current state, compare it to traditional and adult streaming services, and find the niche that xHamster occupies as an amateur content focused service. We find that there are significant differences between adult streaming services and traditional streaming services. The injection rate of new videos is lower but the website does not need a large number of new uploads as long as the front page is constantly refreshed. The length of an average adult video is shorter than that of the average video on traditional streaming services, and we find that there is minimal engagement with ratings and comments. Video tags are actively used to organize and filter through content, and we observe that the more tags a video has, the more views it is likely to obtain.
Cameron Wong; Yo-Der Song; Aniket Mahanti. YouTube of porn: longitudinal measurement, analysis, and characterization of a large porn streaming service. Social Network Analysis and Mining 2020, 10, 1 -19.
AMA StyleCameron Wong, Yo-Der Song, Aniket Mahanti. YouTube of porn: longitudinal measurement, analysis, and characterization of a large porn streaming service. Social Network Analysis and Mining. 2020; 10 (1):1-19.
Chicago/Turabian StyleCameron Wong; Yo-Der Song; Aniket Mahanti. 2020. "YouTube of porn: longitudinal measurement, analysis, and characterization of a large porn streaming service." Social Network Analysis and Mining 10, no. 1: 1-19.
In today’s modern era, the multi-path communication paradigm is becoming prominent in supporting multi-media applications due to its dazzling features of improved network’s resilience, reliability, and performance. Specifically, wireless (environments) networks are intended to become typically reliant on the idea of multi-pathing for efficient traffic balancing which ultimately helps in achieving good performance. Although single-path communication is a promising paradigm for supporting multi-media applications, due to its incompetence in providing significant fault-tolerance demands of such applications, it is unable to satisfy the good Quality of Service (QoS) and Quality of Experience (QoE) requirements for such applications. Hence, traffic allocation and provisioning in the Mobile Ad-hoc Networks (MANETs) environment, considering the dynamic and dissimilar wireless channel characteristics of paths’ and inadequate offered resources (i.e., buffer) in nodes over those paths’, is a challenging job. Nevertheless, current works on traffic allocation addresses the data scheduling provision without considering the dissimilar wireless channel characteristics and background traffic of paths’ respectively. To address the problem of abrupt data scheduling policy, we propose, a novel Adaptive-Congestion Aware Fibonacci Sequence based Data Scheduling Policy (A-CAFDSP) which takes care of each path’s data carrying capacity, dissimilar characteristics and background traffic intensity respectively and ultimately makes data scheduling adaptation decisions to select the efficient paths for concurrent transmissions. Indeed, A-CAFDSP includes the paradigm to concurrently distribute the data packets over multiple available network paths using Fibonacci sequence wisely and regulate the traffic of each available network path individually. Moreover, current works simply adopts and have evaluated their approach on the idealized propagation (radio) prototype without considering fading effects. However, we have evaluated our proposed method in fading environment and all the competent multiple available paths are within the interference ranges of each other hence, the inter-flow interference does exist in our simulation, which certainly gives us the correct idea that how our proposed method works in realistic wireless environment. The simulation results indicate that the performance of A-CAFDSP is better with existing conventional (single-path) and multi-path approaches in terms of average throughput, packet delivery ratio (PDR) and normalized load.
Varun Kumar Sharma; Lal Pratap Verma; Mahesh Kumar; Ranesh Kumar Naha; Aniket Mahanti. A-CAFDSP: An Adaptive-Congestion Aware Fibonacci Sequence based Data Scheduling Policy. Computer Communications 2020, 158, 141 -165.
AMA StyleVarun Kumar Sharma, Lal Pratap Verma, Mahesh Kumar, Ranesh Kumar Naha, Aniket Mahanti. A-CAFDSP: An Adaptive-Congestion Aware Fibonacci Sequence based Data Scheduling Policy. Computer Communications. 2020; 158 ():141-165.
Chicago/Turabian StyleVarun Kumar Sharma; Lal Pratap Verma; Mahesh Kumar; Ranesh Kumar Naha; Aniket Mahanti. 2020. "A-CAFDSP: An Adaptive-Congestion Aware Fibonacci Sequence based Data Scheduling Policy." Computer Communications 158, no. : 141-165.
Energy consumption is dependent on temperature, humidity, occupancy, occupant type, building area etc. All these factors collectively define the context of an energy meter. Once the context is known, the meters within the same context can be grouped and their behaviour can be analyzed together. This paper presents four heuristics, including one novel heuristic, to identify abnormal energy consumption. Using these heuristics, data collected from fifty smart meters deployed inside hostels of IIIT-Delhi was investigated for abnormal energy consumption detection. The anomalies and possible causes were discussed with IIIT-Delhi campus administrator. Energy consumption per occupant for one of the meters was found four times when compared to rest of the meters. The results demonstrated that the proposed heuristics successfully found abnormal energy consumption behaviour.
Ankur Sial; Amarjeet Singh; Aniket Mahanti. Detecting anomalous energy consumption using contextual analysis of smart meter data. Wireless Networks 2019, 27, 4275 -4292.
AMA StyleAnkur Sial, Amarjeet Singh, Aniket Mahanti. Detecting anomalous energy consumption using contextual analysis of smart meter data. Wireless Networks. 2019; 27 (6):4275-4292.
Chicago/Turabian StyleAnkur Sial; Amarjeet Singh; Aniket Mahanti. 2019. "Detecting anomalous energy consumption using contextual analysis of smart meter data." Wireless Networks 27, no. 6: 4275-4292.
Attack graph describes how an attacker can compromise with network security. To generate the attack graph, we required system as well as vulnerability information. The system information contains scanned data of a network, which is to be analyzed. The vulnerability data contain information about, how exploits can be generated due to multiple vulnerabilities and what effects can be of such exploitation. Multihost multistage vulnerability analysis (MulVAL) tool is used for generating attack graph in this work. MulVAL generated graphs are logical attack graphs based on logical programming and based on dependencies among attack goal and configuration information. The risk of network attack graph is measured through graph topology theoretic properties (connectivity, cycles, and depth), and analysis of possible attacks paths is carried out in this paper.
Keshav Prasad; Santosh Kumar; Anuradha Negi; Aniket Mahanti. Generation and Risk Analysis of Network Attack Graph. Advances in Intelligent Systems and Computing 2015, 507 -516.
AMA StyleKeshav Prasad, Santosh Kumar, Anuradha Negi, Aniket Mahanti. Generation and Risk Analysis of Network Attack Graph. Advances in Intelligent Systems and Computing. 2015; ():507-516.
Chicago/Turabian StyleKeshav Prasad; Santosh Kumar; Anuradha Negi; Aniket Mahanti. 2015. "Generation and Risk Analysis of Network Attack Graph." Advances in Intelligent Systems and Computing , no. : 507-516.