FSKSM

The exact contribution of this paper is a review of existing state-of-the-art routing strategies for optical
burst switched networks developed by researchers to deal with burst contention before it happens. Routing
schemes are implemented in space domain, which make them simple and cost effective. Additionally, the
paper points out the importance of routing as an effective way to deal with burst contention compared to other
solutions. It also underlines the main differences between contention avoidance schemes and contention resolution
techniques for optical burst switched networks.We believe that this review will help different optical
burst switched researchers involved in the development of route optimization algorithms to control burst
contention.

In this study, the effects of time slot parameters on
the performance of time domain switching optical burst switched
networks (OBS) are studied. We investigate OBS networks where
all core nodes are able to receive and send data. Network throughput
is reduced when bursts are not able to secure necessary time
slots for their transmission due to heavy contention at the core
networks and lack of proper selection of time slot parameters.
In this paper, we investigate the performance of slotted OBS
when time slot parameters are varied. Time slot parameters
investigated are: frame size, time slot size. Additionally, we
analyse the effect of network size when time slot and other
parameters are kept constant. Metrics used for evaluation are
delay and throughput. Simulation results prove that given the
same route, wavelength and time slot assignment algorithm, time
slot parameters influence the overall network performance

Rapid innovative improvements in wireless communication technology have revolutionized wireless sensor networks (WSNs). A WSN is comprised of self-ruling sensors that are distributed spatially to monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion, or pollutants, and to pass this information through the network to a main area. Sensor nodes in wireless sensor networks experience the ill effects of resource constraints, such as energy deficits, buffers, and bandwidth issues. The expanding demand for real-time services in WSN applications means that interest in quality of service (QoS)-based routing has risen. Offering consistent QoS in sensor networks creates considerable challenges. In real time applications, it is important to deliver data as soon as it is sensed. If the network has multiple real and non-real-time applications, its ability to manage them will be challenging due to different requirements. In this study, we investigate QoS-based routing protocols for WSNs. Metrics of analysis are end-to-end delay, congestion, energy efficiency, and reliability. The aim of the study is to identify the limitations of relevant papers and show research direction in routing. This will not only help new comers to the field of WSN but also will ease the tasks of WSN researchers in developing appropriate routing solutions for WSNs.

Background/Objectives: This appraisal investigates the meta-heuristics resource allocation techniques for maximizing financial gains and minimizing the financial expenses of cloud users for IaaS in cloud computing environment. Methods/Statistical Analysis: Overall, a total of ninety-one studies from 1954 to 2015 have been reviewed in this paper. However, twenty-three studies are selected that focused on the meta-heuristic algorithms for their research. The selected papers are categorized into eight groups according to the optimization algorithms used. Findings: From the analytical study, we pointed out the various issues addressed (optimal and dynamically resource allocation, energy and QoS aware resource allocation, VM allocation and placement) through resource allocation meta-heuristics algorithms.Whereas, the improvement shows better performance concerns minimizing the execution and response time, energy consumption and cost while enhancing the efficiency and QoS in this environment. The comparison parameters (makespan 35%,execution time 13%, response time 26%, cost 22%, utilization21% and other 13% including energy, throughput etc) and also the experimental tools (CloudSim 43%, GridSim 5%, Simjava 9%, Matlab 9% and others 13%) used for evaluation of the various techniques for resource allocation in IaaS cloud computing. Applications/Improvements: The comprehensive review and systematic comparison of meta-heuristic resource allocation algorithms described in this appraisal will help researchers to analyze different techniques for future research directions.