Energy-aware Metrics Research Articles

Vehicular Formed Network Coding Conscious Connectivity for Sensor Networks

With wireless communication, resource efficiency is an important issue. Routing protocols has considered to be a successful technology in recent years, reducing transmission numbers, saving energy and improving network efficiency, especially appropriate for Wireless Networks that drive network coding expertise. However, current network coding knowing routing issues with failed network coding due to faulty conditions. Established network coding, on the other hand, typically takes into account the ideal traffic planning schedule and overlooked resource and load checkpoints that are critical for wireless communication. Therefore, current network coding in the information of routings on wireless sensor networks cannot be implemented explicitly. With regard to the problems mentioned above, this paper proposes the TSCAR for wireless sensor systems for routing in the context of a traffic system. A standard network coding criterion is set out in TSCAR to overcome the fake sequencing problem. In order to produce further coding behaviour as coding openings occur, a method for influencing the transport of various flows is also suggested. Furthermore, the TSCAR delay is analysed by the network calculus. In order to quantify the tracks found, a codification, load, also energy-aware metrics are also planned. Extensive simulation findings show that the TSCAR improves the amount of coding possibilities in addition the percentage of coded packages, boosts system efficiency, then extends wireless network sensor network life.

Survey on Energy Efficient Routing Issues in IOMT

IOT is going to offer large number of applications in various environments for improving the quality of our lives. Routing issues become more and more challenging for low-power and lossy radio-links, multi-hop mesh topologies, the battery supplied nodes and frequently changed network topologies. So that IOT routing protocols has some challenges like traffic Patterns, Energy efficiency, Scalability, Mobility Energy-aware metrics for routing protocol in IOT are node energy, throughput, latency, link quality. The multimedia transmission in IOT depends on a routing protocol to determine stable and resource efficient path, and to provide varying levels of QoS/QoE based on different requirements. The Quality- of-Service (QoS)/Quality-of- experience (QoE ) guarantee for multimedia in internet of things . The current research and development activities have been restricted to scalar sensor data based IOT systems and overlooked the challenges of provisioning multimedia devices over IOT.

Link-stability and Energy Aware Multipath Routing in MANET

Energy conservation is important for mobile ad hoc networks where devices are expected to work for longer periods of time without the need for charging their batteries. Therefore there is a need of an intelligent routing protocol that can minimize overhead and ensure the use of minimum energy routes. In Progressive Energy Efficient Routing, energy efficient shortest paths are selected with minimum energy consumption. Here due to the single path routing, there occur end-to-end delay, routing overhead and packet loss. Therefore to overcome these issues, PEER can be extended for multipath routing. Link-stability metrics and energy aware metrics can be applied for path selection. By this method, stable links are selected. In this study, energy efficient routing is done with maximum life time. The proposed Link-Stability and Energy Aware Multipath Routing gives good performance results in terms of packet delivery ratio, packet drop, energy consumption and delay compared with Progressive Energy Efficient Routing.

Energy-Aware Service Composition Algorithms for Service-Oriented Heterogeneous Wireless Sensor Networks

Wireless sensor networks are evolving with increasingly device heterogeneity, while the problem of effectively composing the platform-specific functionalities provided by heterogeneous sensor nodes to achieve specific goals still remains a challenge. Because of the constrained resources and unreliable communication in sensor networks, traditional service composition techniques in web services with adequate resources are insufficient. In this paper, focusing on the limited energy of sensor nodes, we propose an energy-aware service composition framework for developing various applications in heterogeneous wireless sensor networks. With both the energy-aware metrics: energy-aware load-balancing factor and overall energy consumption, we formulate the process of energy-aware sensor service composition into a combinatorial optimization problem; furthermore, an improved discrete particle swarm optimization (IDPSO) algorithm with inertia weights adjustment and extreme perturbation scheme is proposed to solve the combinatorial optimization problem. The experiment results have shown that the performance of the service route given by IDPSO is approximately equal to the best service route searched out by the exhaustive algorithm. Meanwhile, our proposed energy-aware service composition method is able to reduce the energy consumption and prolong the lifetime of the sensor network when providing stable service composition for various applications.

Energy-aware metrics for benchmarking heterogeneous systems

With the advent of heterogeneous computing systems consisting of multi-core CPUs and many-core GPUs, robust methods are needed to facilitate fair benchmark comparisons between different systems. In this paper we present a benchmarking methodology for measuring a number of performance metrics for heterogeneous systems. Methods for comparing performance and energy efficiency are included. Consideration is given to further metrics, such as associated runnings costs and even carbon emissions. We give a case study for these metrics applied to BUDE, a molecular mechanics-based docking application that has been ported to OpenCL at the University of Bristol.