Wireless sensor NETWORKs consisting of tens or hundreds of sensors that are based on intended use in a distributed environment and their main purpose is to record information. In numerous applications, sharing information in short period of time is gravely important. Also, sharning information would spend most of system’ s energy and considering the limitaions of energy resource in system, controlling the energy usage in NETWORK is a challenge. So, the most important problems in wireless sensor NETWORK are energy consumption and latency on the NETWORK. To optimize energy consumption and transmission DELAY, separately and hand-to-hand, meta-heuristic algorithms in wireless sensor NETWORK can be used. Based on results, hand-to-hand optimization of these two parameters can increase longevity and performance of the NETWORK. The results show that by repeating optimization algorithm, suggested Metaheuristic algorithm’ s results are more similar to results of Shortest path algorithm, in comare to results of Particle Swarm Optimization (PSO) algorithm.

Elastic optical NETWORK has recently raised immense research efforts to serve as a highlyflexible and scalable platform required by the emerging on-demand cloud applications. Besides, virtual NETWORK embedding on top of elastic optical NETWORK has been introduced as a promising solution to fine-grain sharing of node processing and optical bandwidth resources. Owing to the diverse DELAY sensitivity requirements of heterogeneous cloud applications, an efficient double queue scheduler is presented, to deliver differentiated setup DELAY embedding in a fair manner. Extensive numerical simulations carried out over two prototype substrate NETWORKs, demonstrated that our proposed scheme can concomitantly enhance blocking and fairness performance of the single queue scheduler over wide range of offered traffic loads.

One of the obvious reasons for most disorders in NETWORK service provisioning is NETWORK path congestion. Congestion avoidance in today's NETWORKs is too costly and sometimes impossible. With the introduction of SDN, centralizing the equipment's control plane has become possible. This paper presents an enhanced method named ESV-DBRA to avoid congestion in multi-tenant SDN NETWORKs. At first, ESV-DBRA monitors the traffic load and DELAY of all NETWORK paths for each tenant individually. Then, by merging the parameters obtained from the monitoring, the Service Level Agreements (SLA), and a novel proposed cost function, it calculates the cost of the NETWORK paths per tenant. As a result, traffic for each tenant is routed through the path/paths at the lowest possible cost from the tenant's perspective. Next, the bandwidth quotas will be calculated and assigned to the tenants over their optimal routes. Afterward, whenever congestion is likely to occur in a path, ESV-DBRA automatically changes the route or bandwidth of the tenants' traffic related to this path to avoid congestion. Related algorithms are also proposed.Eventually, simulations show that the proposed method effectively increases bandwidth utilization by 10.76%.

In the present study, we analyze dynamics and bifurcations of a discrete-time    Hopfield neural NETWORK  based on two neurons and the same time DELAY. We determine stability and bifurcations of the system consisting flip, pitchfork and Neimark-Sacker  bifurcations. The normal form coefficients for the all bifurcations are calculated using reducing to the corresponding  center manifold, then these coefficients are  numerically obtained using MatContM. Numerical analysis validates our analytical results and reveals more complex dynamical behaviors.

In this paper, the optimal control algorithm design is proposed for droplet generation. In the proposed algorithm, the redundancy in the microfluidic channel NETWORK for droplet generation is used to the optimization setting in order to determine volume flow rate of fluid for each input channel; an optimization problem is proposed for minimizing the volume flow rate of fluid such that the droplet formed in the outlet channel is produced at the desired size. Also, due to the importance of estimating the system state, the design of the Luenberger observer (reduced order observer) has been developed. Then, the proposed scheme is robust against output feedback DELAY with respect to the optimal LQR control structure for tracking the desired value. While designing for the observer and controller sections, the DELAYs in the measurement of the output feedback are considered, and the sustainability analysis for each of the sections has been performed due to the fixed DELAY in the output feedback. Output feedback is a measurable variable of the input volume flow of each channel. Finally, the optimal control algorithm of droplet generation for a microfluidic structure with a T shape has been stimulated.