VLDB 2026 Research / reviewers in the wild / expert
Sahil Sholla
dblp:217/9702
· DBLP profile ↗
6ranked-venue papers
0as first author
6since 2021 · last 2026
0000-0001-7976-1889ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 2 · 2 since 2021Security and privacy · 2 · 2 since 2021Systems, architecture and hardware · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Efficient transaction processing within blockchain networks using parallel trust based distributed proof of authority model
Sheikh Moeen Ul Haque, Shabir Ahamd Sofi, Sahil Sholla |
Comput. Networks | 3 |
| 2024 | The blockchain conundrum: An in-depth examination of challenges, contributing technologies, and alternativesabstractSummary The accelerated development of information and communication technologies has generated a demand for data storage that is effective, transparent, immutable, and secure. Distributed ledger technology and encryption techniques such as hashing and blockchain technology revolutionised the landscape by meeting these requirements. However, blockchain must overcome obstacles such as low latency, throughput, and scalability for its full potential. Investigating blockchain's structure, types, challenges, promises, and variants is necessary to understand blockchain and its capabilities comprehensively. This paper overviews various aspects, such as emergent blockchain protocols, models, concepts, and trends. We classify blockchain variants into five essential categories, DAG, TDAG, Sharding, Consensus, and Combining methods, based on the structure each follows, and conduct a comparative analysis. In addition, we explore current research tendencies. As technology progresses, it is essential to comprehend the fundamental requirements for blockchain development. Iraq Ahmad Reshi, Sahil Sholla |
Concurr. Comput. Pract. Exp. | 2 |
| 2024 | Exploring Personalized Internet of Things (PIoT), social connectivity, and Artificial Social Intelligence (ASI): A surveyabstractPervasive Computing has become more personal with the widespread adoption of the Internet of Things(IoT) in our day-to-day lives. The emerging domain that encompasses devices, sensors, storage, and computing of personal use and surroundings leads to Personal IoT(PIoT). PIoT offers users high levels of personalization, automation, and convenience. This proliferation of PIoT technology has extended into society, social engagement, and the interconnectivity of PIoT objects, resulting in the emergence of the Social Internet of Things (SIoT). The combination of PIoT and SIoT has spurred the need for autonomous learning, comprehension, and understanding of both the physical and social worlds. Current research on PIoT is dedicated to enabling seamless communication among devices, striking a balance between observation, sensing, and perceiving the extended physical and social environment, and facilitating information exchange. Furthermore, the virtualization of independent learning from the social environment has given rise to Artificial Social Intelligence (ASI) in PIoT systems. However, autonomous data communication between different nodes within a social setup presents various resource management challenges that require careful consideration. This paper provides a comprehensive review of the evolving domains of PIoT, SIoT, and ASI. Moreover, the paper offers insightful modeling and a case study exploring the role of PIoT in post-COVID scenarios. This study contributes to a deeper understanding of the intricacies of PIoT and its various dimensions, paving the way for further advancements in this transformative field. Bisma Gulzar, Shabir Ahmad Sofi, Sahil Sholla |
High Confid. Comput. | 3 |
| 2024 | Erratum to "Exploring Personalized Internet of Things (PIoT), social connectivity, and Artificial Social Intelligence (ASI): A survey" [High-Confidence Computing 4 (2024) 100242]
Bisma Gulzar, Shabir Ahmad Sofi, Sahil Sholla |
High Confid. Comput. | 3 |
| 2024 | A privacy-preserving deep learning framework for highly authenticated blockchain secure storage system
Sheikh Moeen Ul Haque, Shabir Ahmad Sofi, Sahil Sholla |
Multim. Tools Appl. | 3 |
| 2024 | Securing IoT data: Fog computing, blockchain, and tailored privacy-enhancing technologies in action
Iraq Ahmad Reshi, Sahil Sholla |
Peer Peer Netw. Appl. | 2 |