We address the throughput maximization problem for downlink transmission in DF-relay-assisted cognitive radio networks (CRNs) based on simultaneous wireless information and power transfer (SWIPT) capability. In this envisioned network, multiple-input multiple-output (MIMO) relay and secondary user (SU) equipment are designed to handle both radio frequency (RF) signal energy harvesting and SWIPT functional tasks. Additionally, the cognitive base station (CBS) communicates with the SU only via the MIMO relay. Based on the considered network model, several combined constraints of the main problem complicate the solution. Therefore, in this paper, we apply heuristic guidelines within the convex optimization framework to handle this complexity. First, consider the problem of maximizing throughput on both sides of the relay separately. Second, each side progresses to solve the complex problem optimally by adopting strategies for solving sub-problems. Finally, these optimal solutions are synthesized by proposing a heuristic iterative power allocation algorithm that satisfies the combinatorial constraints with short convergence times. The performance of the optimal proposed algorithm (OPA) is evaluated against benchmark algorithms via numerical results on optimality, convergence time, constraints’ compliance, and imperfect channel state information (CSI) on the CBS-PU link.

Different types of contact, including contact between node pairs, any-contact of nodes, and contacts of the entire network, are used to characterize social relations in mobile social networks. Different modes of routing, from the point of view of message delivery semantics, encompass unicasting, multicasting, any-casting, and broadcasting. Studies have shown that using probability distribution functions of contact data, which is mainly assumed to be homogeneous for nodes, improves the performance of these networks. However, there exists an important challenge in studies on distributions. A lot of works apply the distribution of one type of contact to other types. Hence in routing applications, it causes to use of the distribution of one type of contact for any mode of routing. This study provides a complete solution to model each type of homogeneous contact data distribution and to use them in different modes of routing. We propose a routing algorithm that uses this new model. Results show that our solution improves the average latency of comparing methods Epidemic, TCCB, and DR about 3.5-times, 30%, and 45%, respectively. It achieves a delivery rate of about 5% and 6%, and average latency about 6% and 8% better than that of DR and TCCB, respectively.

The aim of this paper was to investigate the effect of agile capabilities of manufacturing companies on their manufacturing performance. Methodology of this investigation was causal modeling with Bayesian networks. Bayesian networks are graphical structures for representing probabilistic relationships of a number of variables and for doing probabilistic inference using the variables. The required data for the study were collected from a sample of auto parts manufacturers in cooperation with Andishe Farafan Engineering Co, Sazeh Gostar Co, and Bahman Group. Measurement scale conceptualization and validation methodology were used for the study questionnaire development. The categorical measurements for each concept were obtained from the application of K-means cluster analysis using questionnaire indicators as inputs. These measures were used for causal modeling and hypothesis testing with Bayesian networks. Further, optimal models were identified using Bayesian Information Criterion (BIC). This model represents the casual relationships within and between the agile capabilities and manufacturing performance measures, which can be used in agile manufacturing theory development and agile manufacturing implementation in organizations.

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%.

Social networks, networks that have come into existence, are on the Internet, whose purpose of the establishment is to communicate with different people from different societies. Social networks are a developed form whose information is not trusted by all individuals. Although, it is a popular network that can provide trusted information for some people. If one or more users receive some information from oth-ers, they should assure they have not recieved incorrect data from malicious users. Solutions to these prob-lems are confidence models. Provided that trust deals withpossibilities, Bayesian networks use possibilities to solve problems. As a result, the Bayesian network can improve the calculation of trust. In this study, the proposed model (BTSN) presents a model for calculating confidence using Bayesian networks for social networking. This model is able to calculate the confidence accurately and, in a large scale, can be used in social networks. In addition, the the performance and methods have been studied.