Narrow Results

A wide variety of ways to analyze the end-to-end latency emerges due to the feature of component-based software. The researchers began to see that the latency is more sensitive to the data and control flows than the software architecture. However, for an embedded software, the latency depends upon the hardware heavily. To illuminate the feature clearly, we extend the atomic model of component-based software first. A way to specify the flows involved is further developed to identify the end-to-end latency. What is more, a novel methodology that bridges the gap between a constraint on latency and an execution platform is proposed for the embedded software. By constructing a hierarchical architecture, it is available to consider the methodology as a decision problem where the satisfiability module theory (SMT) can be applied. Experimental results demonstrate how the latency analysis conducts with the proposed model and methodology for the complex software architecture.

In recent times, many MAC protocols were implemented for boosting and improving energy efficiency (EE) in WSNs. Moreover, the cooperative MIMO method is found to be much capable of enhancing the EE of WSNs if configured properly. This paper intends to propose cross-layer design for multihop virtual MIMO system to enhance the end-to-end (ETE) reliability, EE, and QoS of the adopted WSN. The protocol is set here to focus on the energy utilization for transmission of data packets by optimal selection of transmission constraints for each node of the network. Moreover, the protocol’s ETE latency and throughput are also modeled as the dependent variables of BER performance of every link. To discover the improved BER criteria of each link that meets the ETE QoS requirement in reduced energy utilization, this paper employs a new hybrid optimization algorithm named Lion Mutated Dragonfly Algorithm (LM–DA) that is a hybrid variant of both Lion Algorithm (LA) and Dragonfly Algorithm (DA). Finally, the performance of the adopted scheme is validated over other state-of-the-art models. The results state that the energy consumed by the adopted LM–DA approach is about 2.65%, 1.77%, and 1.77% reduced over LA, PSO, and DA schemes, respectively.