The emergence of low-power accelerators has enabled deep learning models to be
executed on mobile or embedded edge devices without relying on cloud resources. The …

Many edge applications rely on expensive Deep-Neural-Network (DNN) inference-based
video analytics. Typically, a single instance of an inference service analyzes multiple …

Many real-world applications are widely adopting the edge computing paradigm due to its
low latency and better privacy protection. With notable success in AI and deep learning (DL) …

Numerous edge applications that rely on video analytics demand precise, low-latency
processing of multiple video streams from cameras. When these cameras are mobile, such …

Cloud computing has drastically changed the delivery and consumption of live streaming
content. The designs, challenges, and possible uses of cloud computing for live streaming …

Edge intelligence is an emerging technology that integrates edge computing and deep
learning to bring AI to the network's edge. It has gained wide attention for its lower network …

Blockchain is a decentralized and distributed ledger technology that enables secure and
transparent recording of transactions across multiple participants. Hyperledger Fabric (HLF) …

With the growth of technology and people's dependency on smartphones, having a
technological control over industrial and residential applications using IoT to suit their …

Blockchain is a decentralized and distributed ledger technology that enables secure and
transparent recording of transactions across multiple participants. Hyperledger Fabric (HLF) …

Multi-tenant applications have been proliferating in recent years, supported by the
emergence of computing-as-service paradigms. Unfortunately, multi-tenancy induces new …