Cloud computing offers its customers an economical and convenient pay-as-you-go service model, known also as usage-based pricing . Cloud customers1 pay only for the actual use of computing resources, storage, and bandwidth, according to their changing needs, utilizing the cloud’s scalable and elastic computational capabilities. In particular, data transfer costs (i.e., bandwidth) is an important issue when trying to minimize costs Several TRE techniques have been explored in recent years. A protocol-independent TRE was proposed. The paper describes a packet-level TRE, utilizing the algorithms presented. Several commercial TRE solutions described in and have combined the sender-based TRE ideas of with the algorithmic and implementation approach of along with protocol specific optimizations for middle-boxes solutions. In particular, describes how to get away with three-way handshake between the sender and the receiver if a full state synchronization is maintained. Cloud computing is expected to trigger high demand for TRE solutions as the amount of data exchanged between the cloud and its users is expected to dramatically increase. The cloud environment redefines the TRE system requirements, making proprietary middle-box solutions inadequate. Consequently, there is a rising need for a TRE solution that reduces the cloud’s operational cost while accounting for application latencies, user mobility, and cloud elasticity
You are here: Home / ieee projects 2013 / Processing the prediction queue and sending PRED ACK or raw data