• International Journal of Computer Science & Network Security
• /
• v.21 no.3
• /
• pp.1-10
• /
• 2021

In recent decades, the heterogeneous and dynamic behavior of Internet traffic has placed new demands on the adaptive resource allocation of the optical network infrastructure. However, the advent of multifiber elastic optical networks has led to a higher degree of spectrum fragmentation than conventional flexible grid networks due to the dynamic and random establishment and removal of optical connections. In this paper, we propose heuristic routing and dynamic slot allocation algorithms to minimize spectrum fragmentation and reduce the probability of blocking future connection requests by considering the power consumption in elastic multifiber elastic optical networks.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.8
• /
• pp.2626-2646
• /
• 2014

This study presents a power and Physical Resource Blocks (PRBs) joint allocation algorithm to coordinate uplink (UL) interference in the device-to-device (D2D) underlaying Long Term Evolution-Advanced (LTE-A) networks. The objective is to find a mechanism to mitigate the UL interference between the two subsystems and maximize the weighted sum throughput as well. This optimization problem is formulated as a mixed integer nonlinear programming (MINLP) which is further decomposed into PRBs assignment and transmission power allocation. Specifically, the scenario of applying imperfect channel state information (CSI) is also taken into account in our study. Analysis reveals that the proposed PRBs allocation strategy is energy efficient and it suppresses the interference not only suffered by the LTE-A system but also to the D2D users. In another side, a low-complexity technique is proposed to obtain the optimal power allocation which resides in one of at most three feasible power vectors. Simulations show that the optimal power allocation combined with the proposed PRBs assignment achieves a higher weighted sum throughput as compared to traditional algorithms even when imperfect CSI is utilized.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.4
• /
• pp.1837-1860
• /
• 2020

We propose a general framework for studying resource allocation problem and the tradeoff between spectral efficiency (SE) and energy efficiency (EE) for downlink traffic in power domain-non-orthogonal multiple access (PD-NOMA) and device to device (D2D) based heterogeneous cloud radio access networks (H-CRANs) under imperfect channel state information (CSI). The aim is jointly optimize radio remote head (RRH) selection, spectrum allocation and power control, which is formulated as a multi-objective optimization (MOO) problem that can be solved with weighted Tchebycheff method. We propose a low-complexity algorithm to solve user association, spectrum allocation and power coordination separately. We first compute the CSI for RRHs. Then we study allocating the cell users (CUs) and D2D groups to different subchannels by constructing a bipartite graph and Hungrarian algorithm. To solve the power control and EE-SE tradeoff problems, we decompose the target function into two subproblems. Then, we utilize successive convex program approach to lower the computational complexity. Moreover, we use Lagrangian method and KKT conditions to find the global optimum with low complexity, and get a fast convergence by subgradient method. Numerical simulation results demonstrate that by using PD-NOMA technique and H-CRAN with D2D communications, the system gets good EE-SE tradeoff performance.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.20 no.9
• /
• pp.624-630
• /
• 2008

When various kinds of outputs are produced from a single energy system, the methodology which allocates the common cost to each output cost is very important because it is directly related with the profit and loss of producers and purchasers. In the cost allocation methodology of the heat and the electricity on a cogeneration, there are energy method, work method, proportional method, benefit distribution method, exergetic methods, and so on. On the other hand, we have proposed a worth method which can be applied to any system. The definition of this methodology is that the unit cost of a product is proportion to the worth. Where, worth is a certain evaluating basis that can equalize the worth of products. In this study, we applied worth method to a steam-turbine cogeneration which produces 22.2 MW of electricity and 44.4 Gcal/h of heat, and then we allocated 2,578 $/h of common cost to electricity cost and heat cost. Also, we compared with various cost allocation methods. As the result, we conclude that exergy of various kinds of worth basis evaluates the worth of heat and electricity most reasonably on this system.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.7A
• /
• pp.660-668
• /
• 2010

In energy resource constrained networks, the network lifetime can be enhanced by optimally allocating energy resource among users based on the available channel state information and the residual energy information at each node. In this paper, we propose the relay selection scheme and power allocation scheme to maximize the network lifetime in wireless relay networks with capacity constraint. The computer simulation results show that the proposed scheme increase the network lifetime in comparison to the conventional schemes.

• Journal of Communications and Networks
• /
• v.18 no.4
• /
• pp.629-638
• /
• 2016

In this paper, we investigate an energy-efficient resource allocation problem in a two-way relay (TWR) network consisting of multiple user pairs and an amplify-and-forward (AF) relay. As the users and relay have individual energy efficiencies (EE), we formulate a multi-objective optimization problem (MOOP). A single-objective optimization problem (SOOP) of the MOOP is introduced using a weighted-sum method, which achieves a single Pareto optimal point of the MOOP. To derive the algorithm for the SOOP, we propose a more tractable equivalent problem using the Karush-Kuhn-Tucker conditions of the SOOP, which guarantees convergence at the local optimal points. The proposed equivalent problem can be efficiently solved by the proposed iterative algorithm. Numerical results demonstrate the effectiveness of the proposed algorithm in achieving the optimal EE in multi-user AF TWR networks.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.5
• /
• pp.917-922
• /
• 2016

Recently, energy harvesting, in which energy is collected from RF signals, has been regarded as a promising technology to improve the lifetime of sensors by alleviating the lack of power supply problem. In this paper, we try to propose an efficient algorithm for simultaneous wireless information and power transfer. At first, we find the lower bound of water-level using the probability density function of channel, and derive the solution of power allocation in energy harvesting networks. In addition, we derive an efficient power splitting method for satisfying the minimum required harvested energy constraint. The simulation results confirm that the proposed scheme improves the average data rate while guaranteeing the minimum required harvested energy constraint, compared with the conventional scheme. In addition, the proposed algorithm can reduce the computational complexity remarkably with insignificant performance degradation less than 10%, compared to the optimal solution.

• Journal of Information Processing Systems
• /
• v.6 no.3
• /
• pp.413-434
• /
• 2010

Wireless sensor networks are usually characterized by dense deployment of energy constrained nodes. Due to the usage of a large number of sensor nodes in uncontrolled hostile or harsh environments, node failure is a common event in these systems. Another common reason for node failure is the exhaustion of their energy resources and node inactivation. Such failures can have adverse effects on the quality of the real-time services in Wireless Sensor Networks (WSNs). To avoid such degradations, it is necessary that the failures be recovered in a proper manner to sustain network operation. In this paper we present a dynamic Energy efficient Real-Time Job Allocation (ERTJA) algorithm for handling node failures in a cluster of sensor nodes with the consideration of communication energy and time overheads besides the nodes' characteristics. ERTJA relies on the computation power of cluster members for handling a node failure. It also tries to minimize the energy consumption of the cluster by minimum activation of the sleeping nodes. The resulting system can then guarantee the Quality of Service (QoS) of the cluster application. Further, when the number of sleeping nodes is limited, the proposed algorithm uses the idle times of the active nodes to engage a graceful QoS degradation in the cluster. Simulation results show significant performance improvements of ERTJA in terms of the energy conservation and the probability of meeting deadlines compared with the other studied algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.3
• /
• pp.1313-1336
• /
• 2020

Cognitive radio (CR) is regarded as an effective approach to avoid the inefficient use of spectrum. However, CRNs have more special security problems compared with the traditional wireless communication systems due to its open and dynamic characteristics. Primary user emulation attack (PUEA) is a common method which can hinder secondary users (SUs) from accessing the spectrum by transmitting signals who has the similar characteristics of the primary users' (PUs) signals, and then the SUs' quality of service (QoS) cannot be guaranteed. To handle this issue, we first design a multiple-phase energy detection scheme based on the cooperation of multiple SUs to detect the PUEA more precisely. Second, a joint SUs scheduling and power allocation scheme is proposed to maximize the weighted effective capacity of multiple SUs with a constraint of the average interference to the PU. The simulation results show that the proposed method can effectively improve the effective capacity of the secondary users compared with the traditional overlay scheme which cannot be aware of the existence of PUEA. Also the good delay QoS guarantee for the secondary users is provided.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.21 no.4
• /
• pp.252-259
• /
• 2009

When various kinds of outputs are produced from a single energy system, the methodology which allocates the common cost to each output cost is very important because it is directly related with the profit and loss of producers and purchasers. In the cost allocation methodology of the heat and the electricity on a cogeneration, there are energy method, work method, proportional method, benefit distribution method, various exergetic methods, and so on. On the other hand, we have proposed a worth evaluation method which can be applied to any system. The definition of this methodology is that the unit cost of a product is proportion to the worth. Where, worth is a certain evaluating basis that can equalize the worth of products. In this study, we applied this methodology to a gas-turbine cogeneration which produces 119.2 GJ/h of electricity and 134.7 GJ/h of steam, and then we allocated 3,150 $/h of fuel cost to electricity cost and steam cost. Also, we compared with various cost allocation methods. As the result, we conclude that reversible work of various kinds of worth basis evaluates the worth of heat and electricity most reasonably.