Sharif Digital Repository

This article presents a new optimization algorithm based on integrating the use of genetic algorithms and tabu search methods to optimal allocation of dispersed generation resources in distribution networks. The proposed algorithm finds how much distribution losses can be reduced if dispersed generations are optimally allocated at the demand side of power system. A significant improvement of the proposed algorithm results, over that obtained by genetic algorithm, has been achieved. Numerical examples also showed the superiority of the proposed algorithm compared with the simple genetic algorithm. Copyright © Taylor & Francis Inc  

Cloud Manufacturing (CM) as a successful manufacturing business model and a major driver of Industry 4.0 has attracted a lot of attention in recent years. CM idea aims to streamline the on-demand provisioning of manufacturing resources and capabilities as services, providing end-users with flexible and scalable services accessible through global networks. This idea created many opportunities and challenges. One of the critical challenges is resource allocation, which determines who interacts with whom and how in the CM platform. The type of the platform is a determining factor for the selection of the appropriate resource allocation. To analyze the impact of the allocation on the utilities,... 

Device-to-Device communication (D2D) integrated in cellular networks emerges as a new trend in response to notable rise in traffic demand. Resource allocation is one of the important challenges in deployment of D2D networks. In this paper, we formulate an optimization problem for optimal resource allocation and then propose a novel algorithm namely maximum clique based resource allocation (MCRA) for improving the spectral reuse based on graph theoretic concept of maximum clique. Practical application of D2D communications requires each node to receive and transmit signals during the communication process. We have considered this issue in constructing the interference graph and mathematical... 

Visible light communication (VLC) uses huge license-free spectral bandwidth of visible light for high-speed wireless communication. Since each VLC access point covers a small area, handovers of mobile users are inevitable. In order to deal with these handovers, developing fast and effective resource allocation algorithms is a challenge. This paper introduces the problem of mobility-aware optimization of resources in VLC networks using the T-step look-ahead policy and employing the notion of handover efficiency. It is shown that the handover efficiency can correlate the overall performance of the network with future actions based on the mobility of users. Due to the stationary nature of... 

Nowadays, we live in a Big Data world and many sectors of our economy are guided by data-driven decision processes. Big Data and Business Intelligence applications are facilitated by the MapReduce programming model, while, at infrastructural layer, cloud computing provides flexible and cost-effective solutions to provide on-demand large clusters. Capacity allocation in such systems, meant as the problem of providing computational power to support concurrent MapReduce applications in a cost-effective fashion, represents a challenge of paramount importance. In this paper we lay the foundation for a solution implementing admission control and capacity allocation for MapReduce jobs with a priori... 

As a promising solution for future indoor access networks, resource allocation in Visible light communication or LiFi networks is subject to lots of researches. An interesting approach for network algorithm design is to use some knowledge about the future of the network. With this regards, the anticipatory design may improve the performance of the system in terms of delay and throughput. This paper reviews the state-of-the-art anticipatory algorithms proposed in the literature, given different prediction capabilities. The key element that all of these algorithms share is to find an event that correlates the current actions to the performance of the network in the future. Apart from the... 

In this letter, we study the resource allocation for a multiuser intelligent reflecting surface (IRS)-aided simultaneous wireless information and power transfer (SWIPT) system. Specifically, a multi-antenna base station (BS) transmits energy and information signals simultaneously to multiple energy harvesting receivers (EHRs) and information decoding receivers (IDRs) assisted by an IRS. Under this setup, we introduce a multi-objective optimization (MOOP) framework to investigate the fundamental trade-off between the data sum-rate maximization and the total harvested energy maximization, by jointly optimizing the energy/information beamforming vectors at the BS and the phase shifts at the... 

5G networks are going to support a variety of vertical services, with a diverse set of key performance indicators (KPIs), by using enabling technologies such as software-defined networking and network function virtualization. It is the responsibility of the network operator to efficiently allocate the available resources to the service requests in such a way to honor KPI requirements, while accounting for the limited quantity of available resources and their cost. A critical challenge is that requests may be highly varying over time, requiring a solution that accounts for their dynamic generation and termination. With this motivation, we seek to make joint decisions for request admission,... 

The current state of device-to-device (D2D) communication in the presence of cellular network addresses two major challenges of interference as well as throughput inadequacy. Specifically, a D2D communication underlaying fractional frequency reuse (FFR) cellular network exhibits rather high interferences due to higher occurrence of band crossing within a shared spectrum. However, due to the considerable impact of D2D communications on spectral efficiency and system capacity, the remedy for those issues may include efficient techniques of interference mitigation and average spectral efficiency maximization. In this paper, we propose a resource block (RB) allocation scheme to reduce the... 

In this letter, we improve the tradeoff among the downlink (DL) rates of service providers (SPs), provided by a mobile virtual network operator (MVNO) using non-orthogonal multiple access (NOMA) technique. In this respect, NOMA provides a suitable opportunity for the MVNO to share resources among SPs more efficiently. Regarding interaction among the DL rates provided for SPs we formulate our resource allocation problem as a multiobjective optimization problem (MOOP) while taking into account user fairness. By using the weighted Tchebycheff technique, we are able to solve the formulated MOOP by considering different tradeoffs among DL rates of different SPs. Our numerical results show that by... 

In this letter, we improve the tradeoff among the downlink (DL) rates of service providers (SPs), provided by a mobile virtual network operator (MVNO) using non-orthogonal multiple access (NOMA) technique. In this respect, NOMA provides a suitable opportunity for the MVNO to share resources among SPs more efficiently. Regarding interaction among the DL rates provided for SPs we formulate our resource allocation problem as a multiobjective optimization problem (MOOP) while taking into account user fairness. By using the weighted Tchebycheff technique, we are able to solve the formulated MOOP by considering different tradeoffs among DL rates of different SPs. Our numerical results show that by... 

In this letter, we study a receiver architecture technique for joint resource allocation in a downlink (DL) multi-user multi-carrier non-orthogonal multiple access (MC-NOMA) network with simultaneous wireless information and power transfer (SWIPT). In this framework, the subcarrier set is partitioned into two groups that are assigned to perform information decoding (ID) and energy harvesting (EH) at the receiver side based on the optimization problem. This letter seeks to maximize energy harvesting while meeting a minimum data-rate requirement for each user. The underlying optimization problem is mixed-integer non-linear programming (MINLP). To that end, we employ the monotonic optimization... 

The purpose of this study is to apply managerial economics and methods of decision analysis to study the optimal pattern of innovation activities for development of new energy technologies in developing countries. For this purpose, a model of energy research and development (R&D) planning is developed and it is then linked to a bottom-up energy-systems model. The set of interlinked models provide a comprehensive analytical tool for assessment of energy technologies and innovation planning taking into account the specific conditions of developing countries. An energy-system model is used as a tool for the assessment and prioritization of new energy technologies. Based on the results of the...